Содержание метода сценариев

Понятие и сущность метода сценариев

Практика работы ситуационных центров в настоящее время не обходится без использования метода сценариев, который позволяет произвести оценку наиболее вероятного хода развития событий, а также наиболее вероятные последствия принимаемых решений. 

На основе разработанных специалистами сценариев развития анализируемых ситуаций становится возможным на определенном уровне достоверности определять возможные варианты и тенденции развития, а также взаимосвязь между действующими факторами, формировать картины событий, к которым ситуация может прийти под воздействием определенного рода воздействий. 

Благодаря профессионально разработанным сценариям происходит обеспечение более полного и отчетливого определения перспектив развития ситуации как в случае наличия управляющего воздействия, так и в ситуации их отсутствия. 

При этом, благодаря сценариям ожидаемого развития ситуаций становится возможным создание условий для своевременного обнаружения опасностей, которые могут приводить к неблагоприятным путям развития событий, либо к неудачному управленческому воздействию. 

Благодаря сопоставлению и оценки вероятных сценариев развития ситуации, которая вызвана различными фоновыми и управляющими воздействиями и факторами, которые не зависят от деятельности руководителя возникает ситуация принятия зачастую единственно верного решения. 

Принято считать, что сценарии для прогнозирования процессов развития разных сложных систем впервые были использованы Германом Каном. Первые разработанные им сценарии имели преимущественно описательный характер. Позднее, метод сценариев получил развитие преимущественно благодаря применению более точных количественных и качественных моделей. 

Метод сценариев представляет собой систему, в которой предполагается создание технологий разработки сценариев, которые позволят обеспечивать более высокий уровень вероятности выработки эффективных решений в тех ситуациях, когда это возможно, а также более высокую вероятность снижения к минимуму вероятных потерь в тех случаях, когда потери являются неизбежными. 

Варианты реализации метода сценариев в организации 

В настоящее время принято выделять большое количество различных стратегий реализации метода сценариев, среди которых: 

1. Метод получения согласованного мнения. 
2. Метод повторяющейся процедуры независимых сценариев. 
3. Метод использования матриц взаимодействия. 

Приведем более подробную их характеристику.

Метод получения согласованного мнения – это в сущности одна из разновидностей метода Делфи, которая ориентирована на получение коллективной позиции разных экспертных групп касательно различных важных событий в различных областях в конкретный временной промежуток будущего. 

В качестве недостатка данного метода следует выделить отсутствие должного внимания процессам взаимодействия и взаимосвязи различных факторов, которые влияют на динамику развития ситуации, и на развитие событий. 

Метод повторяющейся процедуры независимых сценариев заключается в формировании независимых сценариев для каждого аспекта, которые оказывают существенное воздействие на различные ситуации. Также, данный метод использует повторяющиеся итеративные процессы согласования сценариев развития разных вариантов ситуаций. 

Достоинством данного метода является усугубленный анализ взаимодействия различных моментов развития ситуации. В качестве недостатков метода выделяется недостаточная разработанность и методическая обеспеченность процедур согласования сценариев. 

Метод матриц взаимовлияния, который был разработан Хелмером и Гордоном нацелен на определение с учетом экспертной оценки потенциального взаимодействия событий данной совокупности. 

Оценки, которые связывают все возможные варианты развития событий в их силе, времени, распределении и прочем способствуют уточнению первоначальной оценки вероятностей событий, а также их комбинаций. 
Недостатком метода является сложность в получении больших объемов оценки, а также отсутствие корректной обработки этих оценок. 

Особенности методологии составления сценариев

Процессы составления сценариев предполагают предварительное определение системы параметров, которые описывают систему. 

Состояние системы в определенный момент времени «t» выступает в качестве точки 5 в данной системе параметров. На основании определения возможных тенденций развития ситуации становится возможным высчитать вероятные направления эволюции положения системы в пространстве этих параметров 5 в разные промежутки времени в будущем S(t+ 1), S(t + 2) и прочее. 

В случае отсутствия управляющего воздействия предполагается, что эволюция системы будет происходит в самом вероятном ключе. 

Управляющее воздействие является эквивалентным воздействию сил, которые способны изменять направления траектории S(t). 

Управляющие воздействия должны быть рассмотрены совместно с ограничениями, которые накладываются и внешними, и внутренними факторами. Данная технология выработки сценария предполагает исследование положения системы в различные дискретные отрезки времени t,t+ 1, t + 2.

Вместе с тем, предполагается, что точка, которая соответствует системе 5 в координатах параметров располагается в конусе, который расширяется в ситуации удаления от исходных моментов времени I. 

В определенных моментах времени t + Т  можно ожидать, что систему будут располагать в сечении конуса, который соответствует моменту времени t + Т.

Каждая точка этого сечения может трактоваться в качестве вероятного расположения системы в пространстве параметров. Естественно, что наиболее вероятным будет считаться положение системы на центральных осях конуса. 

За счет управляющих воздействий происходит смещение положения системы в пространстве параметров. В этом случае целесообразным также будет рассмотрение только дискретных точек, при уделении особого внимания вероятным точкам. В ситуации такого анализа важно уметь предвидеть возможности возникновения дополнительного внутреннего напряжения между элементами системы, так как они также могут изменять положение системы в пространстве параметров. 

Для произведение оценки напряжений можно использовать соответствующие социальные, либо экономические индикаторы, совместно с пороговыми значениями индикаторов, в ситуации превышения которых положение системы может быть существенным образом изменено. 

В некоторый случаях, управляющее воздействие может быть направлено на предотвращение превышения пороговых значений индикаторов, в случае, если целью является сохранение стабильности. 

В некоторых ситуациях можно специально стремиться к результату, превосходящему пороговые значения индикаторов, что целесообразно в тех случаях, когда это не противоречит поставленным перед системой задачам. 

В качестве одного из наиболее значимых результатов применения данной разновидности метода сценариев, также, как и иных его разновидностей, выступает более детальное понимание аспектов анализируемых ситуаций, а также особенностей ее развития и ее основных закономерностей. Внимание заслуживает и иная модель метода сценариев. Исследователями заявляется, что их метод выработки сценариев относится преимущественно к анализу возможного будущего, а не вероятного будущего. 

Правда, более детальное понимание ситуации, которое получается благодаря процессу тщательной работы, следующим шагом определяет формирование системы воздействий, которая сможет изменять рассмотренные сценарии развития ситуации. При этом вероятное будущее может подлежать корректировке. 

В этом методе предусматривается отбор только тех переменных, которые имеют непосредственное отношение к развитию анализируемых систем, вне зависимости, относится ли эта система к контролю за окружающей средой, либо она относится к управлению технологическими процессами в действующем производстве, или прочим вещам. 

В дальнейшем авторы предлагают разрабатывать достаточно детальные сценарии для обнаружения опасностей, которые угрожают системе, совместно с выработкой системы противодействия им. 

Предусматривается среди большого числа сценариев отбор наиболее пригодных из них для всей совокупности с целью последующего анализа, совместно с процедурой использования компьютерных технологий для выработки сценарных прогнозов, которые не являются искаженными. Проведем более детальный анализ перечисленных процедур.

Перед тем, как начинать разработку сценария, важно проводить анализ ситуации с определением конкретных базовых действующих единиц и отношений между факторами, являющимися важнейшими в ней. Кроме того, также важно выполнить структуризацию и детализацию ситуации. В этом методе отбор реализуют эксперты. 

Анализу подвергаются прогнозы развития ситуации с возможным применением контент-анализа, также происходит выделение переменных, которые представляют собой область логических рассуждений экспертов и их взаимосвязь. Ключевой задачей является получение набора существенных переменных, которые достаточно полно могут характеризовать развитие анализируемых ситуаций. 

Следующим этапом будет являться определение соответствующей шкалы для каждой переменной, в рамках которой она могла бы быть изменена. Так как в реальных условиях, вместе с количественными переменными могут быть использованы и качественные, важно разработать для каждой переменной вербально-числовую шкалу, в которой могут содержаться как численные значения градаций, так и их содержательное описание. 

Благодаря содержательному описанию становится возможным расширение состава переменных с помощью включения в него переменных, которые действительно могут отражать особенности анализируемых ситуаций, несмотря на то, что они и не обладают никакой качественной природой. Благодаря количественным значениям переменных становится возможным более надежная оценка опасностей. 

В случае, если переменные являются непрерывными, то целесообразным будет выделить их характерные значения с целью дальнейшего использования при анализе ситуаций. В некоторых ситуациях, сведения о переменных могут предоставляться в форме определенного тезауруса, который отразил бы основную количественную и качественную информацию, которая позволит достаточно полно представить переменные. 

Благодаря неоправданному увеличению числа переменных происходит затруднение анализа ситуаций. Вместе с тем, их избыточное агрегирование (обобщение) также может сильно затруднить анализ. 

Основной задачей сценария является выработка ключа к пониманию проблемы. В ситуации анализа конкретных ситуаций переменные, которые ее характеризуют, получают соответствующие значения в виде определенных градаций вербально-числовой шкалы каждой из переменных.

Определению подлежат все значения парного взаимодействия между переменными, которые могут оказать взаимное влияние в ситуации развития данной ситуации. Такой тип взаимодействия между переменными, чаще всего представляется в виде матрицы. 

После выработки и представления сценария с помощью переменных, а также оценки их внутренней согласованности и взаимодействия возможно использование, при включении вербально-числовых шкал, перс-хода к презентации сценария в форме содержательного описания. Данная форма чаще всего оказывается самой удобной при подготовке отчета о проделанных работах. 

В некоторых случаях целесообразным является включение предыстории развития анализируемых ситуаций в состав сценария. Отличительной особенностью данного метода является многовариативность – то есть изучение нескольких альтернативных вариантов вероятного развития ситуации при учете базисного сценария. 

На основании группирования сценариев в классы становится возможным определение рациональной стратегии воздействия на ситуации. 

Чаще всего, сведения о нескольких вероятных сценариях развития ситуации являются более информативными, чем единственный сценарий, кроме того, они позволяют принимать более эффективные решения. 

Еще одной особенностью этого метода является то, что он позволяет оценивать значения взаимодействия переменных только в рамках границ области допустимых значений, а не во всей области, как это предполагает метод, использующий матрицу влияния. 

Использование специализированных программ для ЭВМ и для датчиков случайных чисел с последующими отсечениями невозможных ситуаций для проработки альтернативных вариантов сценариев позволяет расширить горизонты анализа вероятных ситуаций в будущем. 

На основе разработанного широкого спектра возможных альтернативных вариантов развития ситуации становится возможным более полное определение критических ситуаций для принятия решений, совместно с определением возможных последствий предлагаемых альтернативных вариантов решения с целью их сопоставления и выбора среди них наиболее эффективного. 

Метод сценариев

При
разработке управленческих решений
широкое распространение нашел метод
сценариев, также дающий возможность
оценить наиболее вероятный ход развития
событий и возможные последствия
принимаемых решений. Этот метод можно
рассматривать как комбинацию методов
экспертных оценок (индивидуальных или
групповых) с методами имитационного
моделирования.

В
основе этого метода лежат разрабатываемые
специалистами сценарии развития
анализируемой ситуации. Это позволяет
с тем или иным уровнем достоверности
определить возможные тенденции развития,
взаимосвязи между действующими факторами,
сформировать картину возможных состояний,
к которым может прийти ситуация под
влиянием тех или иных воздействий.

Профессионально
разработанные сценарии позволяют более
полно и отчетливо определить перспективы
развития ситуации, как при наличии
различных управляющих воздействий, так
и при их отсутствии.

С
другой стороны, сценарии ожидаемого
развития ситуации позволяют своевременно
осознать опасности, которыми чреваты
неудачные управленческие воздействия
или неблагоприятное развитие событий.

Высказывается
мнение, что необходимость в предвидении
наиболее вероятного развития ситуации
впервые возникла с возникновением
промышленного производства, поскольку
при сезонно повторяющемся сельскохозяйственном
производстве в этом не было никакой
необходимости.

Полностью
согласиться с такой точкой зрения
трудно, поскольку испокон веков
человечество воевало, время от времени
вело грандиозное строительство. И без
представления возможного развития
ситуации такие, целенаправленные
действия вряд ли были бы возможны.

В
то же время прототипы метода сценариев
нередко мы находим в разные времена в
разных странах.

Так
Кутузов собравший военный совет в Филях,
и прослушавший различные варианты
возможных действий, оценивал различные
сценарии развития войны с французами,
предлагавшиеся военноначальниками.

Он
сопоставлял их сильные и слабые стороны
и пришел к тяжелому, но, пожалуй,
единственно верному решению оставить
Москву, обрекая ее на пожары и разрушения.

Однако
последующее развитие событий подтвердило
его правоту. Предпочтенный им сценарий
развития событий полностью себя оправдал.

Государственный
деятель, занимающий ответственный пост,
и бизнесмен, принимающий важное для
судьбы проекта решение, финансист,
анализирующий фондовый рынок, хирург
накануне сложной нетрадиционной
операции, конструктор, закладывающий
основы принципиально нового объекта
при принятии важных решений, как правило,
пытаются предугадать возможный сценарий
развития событий с тем, чтобы принять
решение, обеспечивающее успех.

Считается,
что первым сценарии для прогнозирования
развития сложных систем использовал
Герман Кан. Первые из разработанных
сценариев носили преимущественно
описательный характер.

Впоследствии
метод сценариев был в значительной
степени развит за счет использования
более точных качественно-количественных
моделей.

Метод
сценариев предполагает создание
технологий разработки сценариев,
обеспечивающих более высокую вероятность
выработки эффективного решения в тех
ситуациях, когда это возможно, и более
высокую вероятность сведения ожидаемых
потерь к минимуму в тех ситуациях, когда
потери неизбежны.

В
настоящее время известны различные
реализации метода сценариев такие, как:

• получение
  согласованного мнения,

• повторяющаяся
  процедура независимых сценариев,

• использование
  матриц взаимодействия и др.

Метод
получения согласованного мнения
является, по существу, одной из реализаций
метода Дельфи³,
ориентированной на получение коллективного
мнения различных групп экспертов
относительно крупных событий в той или
иной области в заданный период будущего.

К
недостаткам этого метода можно отнести
недостаточное внимание, уделяемое
взаимозависимости и взаимодействию
различных факторов, влияющих на развитие
событий, динамике развития ситуации.

Метод
повторяющегося объединения независимых
сценариев
состоит в составлении независимых
сценариев по каждому из аспектов,
оказывающих существенное влияние на
развитие ситуации, и повторяющемся
итеративном процессе согласования
сценариев развития различных аспектов
ситуации.

Достоинством
этого метода является более углубленный
анализ взаимодействия различных аспектов
развития ситуации.

К
его недостаткам можно отнести недостаточную
разработанность и методическую
обеспеченность процедур согласования
сценариев.

Метод
матриц взаимовлияний,
разработанный Гордоном и Хелмером,
предполагает определение на основании
экспертных оценок потенциального
взаимовлияния событий рассматриваемой
совокупности.

Оценки,
связывающие все возможные комбинации
событий по их силе, распределению во
времени и т.д., позволяют уточнить
первоначальные оценки вероятностей
событий и их комбинаций. К недостаткам
метода можно отнести трудоемкость
получения большого количества оценок
и корректной их обработки.

Для
примера приведём одну из методологий
составления сценариев, которая
предполагает предварительное определение
пространства параметров, характеризующих
систему.

Состояние
системы в момент времени t
является точкой S(t)
в этом пространстве параметров.
Определение возможных тенденций развития
ситуации позволяет определить вероятное
направление эволюции положения системы
в пространстве выявленных параметров
S(t)
в различные моменты времени в будущем
S(t+l),
S(t+2)
и т.д.

Если
управляющие воздействия отсутствуют,
то предполагается, что система будет
эволюционировать в наиболее вероятном
направлении.

Управляющие
воздействия эквивалентны воздействию
сил, способных изменить направление
траектории S(t).

Естественно,
что управляющие воздействия должны
рассматриваться как с учетом ограничений
накладываемых как внешними, так и
внутренними факторами.

Технология
разработки сценариев предполагает
рассмотрение положения системы в
дискретные моменты времени t,
t+1, t+2,
… .

При
этом предполагается, что точка,
соответствующая системе S(t)
в пространстве параметров расположенным
в конусе, расширяющемся при удалении
от исходного момента времени t.

В
некоторый момент времени t+T
ожидается, что система будет расположена
в сечении конуса, соответствующем
моменту времени
t+T.

Все
точки этого сечения могут считаться
вероятным расположением системы в
пространстве параметров. Естественно,
что наиболее вероятным считается
положение системы на центральной оси
конуса.

Управляющие
воздействия приводят к смещению положения
системы в пространстве параметров. В
этом случае также целесообразно
рассматривать лишь дискретные точки,
наибольшее внимание, уделяя при этом
наиболее вероятным точкам. При таком
анализе необходимо предвидеть возможность
возникновения дополнительных внутренних
напряжений между элементами системы,
поскольку они также могут изменять
положение системы в пространстве
параметров.

Для
оценки напряжений могут быть использованы
соответствующие индикаторы, в частности,
экономического или социального характера,
а также пороговые значения индикаторов,
при превышении которых положение системы
может значительно измениться.

Управляющие
воздействия в ряде случаев могут быть
направлены на предотвращение превышения
пороговых значений индикаторов, если
нашей целью является сохранение
стабильности.

В
некоторых случаях можно целенаправленно
стремиться к превышению пороговых
значений индикаторов, если это
соответствует поставленным перед
системой задачам.

Одним
из наиболее важных результатов
использования этой разновидности метода
сценариев, как впрочем, и других его
разновидностей, является лучшее понимание
анализируемой ситуации и основных
закономерностей и особенностей ее
развития.

Заслуживает
внимания разновидность метода сценариев,
предложенная Абтом, Фостером и Ри.

Авторы
подчеркивают, что их метод разработки
сценариев относится скорее к анализу
возможного, а не вероятного будущего.

Действительно,
полученное в процессе разработки
прогноза более глубокое понимание
ситуации предполагает в качестве
следующего шага выработку системы
воздействий, которая может изменить
рассмотренные сценарии развития
ситуации. И вероятное будущее может
оказаться скорректированным.

Разработанный
авторами метод предусматривает отбор
только тех переменных, которые имеют
непосредственное отношение к развитию
анализируемой системы, будь то система
контроля за окружающей средой или
система управления технологическим
процессом в действующем производстве
и т.д.

Далее
предполагается разработка достаточно
детальных сценариев для выявления
опасностей, угрожающих системе, и
необходимого противодействия им.
Предусматривается отбор среди множества
возможных сценариев наиболее пригодных
для последующего анализа, а также
процедуры использования компьютеров
для разработки неискаженных сценарных
прогнозов.

Рассмотрим
перечисленные процедуры более детально.
Прежде, чем приступить к разработке
сценария, предполагается провести
анализ ситуации с определением основных
действующих сил, основных взаимоотношений
между основными действующими в ней
факторами, необходимую детализацию и
структуризацию ситуации.

Отбор
переменных в этом методе предполагает
использование экспертов.

Анализируются,
с возможным использованием контент-анализа,
прогнозы экспертов развития ситуации
и выделяются переменные, являющиеся
частью логических рассуждений экспертов,
и их взаимосвязи.

Основной
задачей при этом является получение
набора существенных переменных,
достаточно полно определяющих развитие
анализируемой ситуации.

Следующим
этапом является определение для каждой
переменной соответствующей шкалы, в
которой она могла бы быть измерена.

Поскольку
в реальных ситуациях, наряду с
количественными переменными, используются
и качественные, предполагается разработка
для каждой переменной вербально числовой
шкалы, содержащей как численные значения
градаций, так и их содержательное
описание.

Содержательное
описание позволяет расширить состав
переменных, включая в него переменные,
действительно отражающие характер
анализируемой ситуации, хотя и не имеющие
количественной природы.

Количественные
значения переменных позволяют более
надежно определять возможные опасности.

Если
переменные непрерывны, то целесообразно
выделение характерных их значений, для
использования при анализе ситуации.

В
некоторых случаях информация о переменных
может представляться в виде некоторого
тезауруса, в котором отражается основная
информация как количественная, так и
описательная, позволяющая достаточно
полно представить переменную.

Неоправданное
увеличение числа переменных затрудняет
возможность анализа ситуации, в то же
время излишнее их обобщение (агрегирование)
также затрудняет проведение анализа.

Основная
задача сценария — дать ключ к пониманию
проблемы. При анализе конкретной ситуации
переменные ее характеризующие принимают
соответствующие значения — те или иные
градации вербально числовых шкал каждой
из переменных.

Определяются
все значения парных взаимодействий
между переменными, которые оказывают
взаимное влияние при развитии данной
ситуации.

Такое
взаимодействие между переменными, как
правило, представляется в матричном
виде.

После
разработки и представления сценария с
помощью переменных и оценки их
взаимодействия и внутренней согласованности
возможен, с использованием вербально
— числовых шкал, переход к представлению
сценария в виде содержательного описания.

Такая
форма нередко оказывается более удобной
при подготовке отчета о проделанной
работе. Иногда целесообразно включение
в состав сценария предыстории развития
анализируемой ситуации.

Отличительной
особенностью излагаемого метода является
многовариантность, т.е. рассмотрение
нескольких альтернативных вариантов
возможного развития ситуации с учетом
базисных сценариев.

Группируя
сценарии в классы можно определить
рациональную стратегию воздействия на
ситуацию.

Как
правило, данные о нескольких возможных
сценариях развития ситуации более
информативны, чем один единственный
сценарий и способствуют принятию более
эффективных решений.

Особенность
этого метода состоит также в том, что,
возможно, оценивать значения взаимодействия
переменных лишь на границах области
допустимых значений, а не по всей области,
как это предполагается в методе,
использующем матрицы взаимовлияний.

Использование
специальных программ для компьютеров,
а так же датчиков случайных чисел с
последующим отсечением невозможных
ситуаций для генерирования альтернативных
вариантов сценариев расширяет горизонт
анализа возможных в будущем ситуаций.

Разработанный
широкий спектр возможных альтернативных
вариантов развития ситуации позволяет
более полно определить критические
ситуации для принятия решений, а также
определить возможные последствия
предлагаемы; альтернативных вариантов
решений с целью их сопоставления и
выбора наиболее эффективного.

Профессионально
разработанный и периодически
актуализируемый прогноз — неотъемлемая
составляющая процесса выработки и
принятия важных управленческих решений.

Выводы

Основным
методом, использующимся в нормативном
прогнозировании, является метод
горизонтальных матриц решений. Обычно
используются двумерные и трехмерные
матрицы. Кроме метода горизонтальных
матриц решений используются методы
построения деревьев целей.

Метод
сценариев можно рассматривать как
комбинацию методов экспертных оценок
с методами имитационного моделирования.
В основе метода лежат разрабатываемые
специалистами сценарии развития
анализируемой ситуации. Существуют
различные реализации метода сценариев:

• получение
  согласованного мнения,

• повторяющаяся
  процедура независимых сценариев,

• использование
  матриц взаимодействия.

Использование
специальных компьютерных программ, а
также датчиков случайных чисел для
создания моделей объекта прогнозирования
дает возможность разработки альтернативных
вариантов сценариев. Альтернативные
варианты развития позволяют определить
критические ситуации для принятия
решений.

Scenario planning, scenario thinking, scenario analysis,^[1] scenario prediction^[2] and the scenario method^[3] all describe a strategic planning method that some organizations use to make flexible long-term plans. It is in large part an adaptation and generalization of classic methods used by military intelligence.^[4]

In the most common application of the method, analysts generate simulation games for policy makers. The method combines known facts, such as demographics, geography and mineral reserves, with military, political, and industrial information, and key driving forces identified by considering social, technical, economic, environmental, and political («STEEP») trends.

In business applications, the emphasis on understanding the behavior of opponents has been reduced while more attention is now paid to changes in the natural environment. At Royal Dutch Shell for example, scenario planning has been described as changing mindsets about the exogenous part of the world prior to formulating specific strategies.^[5][6]

Scenario planning may involve aspects of systems thinking, specifically the recognition that many factors may combine in complex ways to create sometimes surprising futures (due to non-linear feedback loops). The method also allows the inclusion of factors that are difficult to formalize, such as novel insights about the future, deep shifts in values, and unprecedented regulations or inventions.^[7] Systems thinking used in conjunction with scenario planning leads to plausible scenario storylines because the causal relationship between factors can be demonstrated.^[8] These cases, in which scenario planning is integrated with a systems thinking approach to scenario development, are sometimes referred to as «dynamic scenarios».

Critics of using a subjective and heuristic methodology to deal with uncertainty and complexity argue that the technique has not been examined rigorously, nor influenced sufficiently by scientific evidence. They caution against using such methods to «predict» based on what can be described as arbitrary themes and «forecasting techniques».

A challenge and a strength of scenario-building is that «predictors are part of the social context about which they are trying to make a prediction and may influence that context in the process».^[9] As a consequence, societal predictions can become self-destructing. For example, a scenario in which a large percentage of a population will become HIV infected based on existing trends may cause more people to avoid risky behavior and thus reduce the HIV infection rate, invalidating the forecast (which might have remained correct if it had not been publicly known). Or, a prediction that cybersecurity will become a major issue may cause organizations to implement more secure cybersecurity measures, thus limiting the issue.^[9]

Principle[edit]

Crafting scenarios[edit]

Combinations and permutations of fact and related social changes are called «scenarios». Scenarios usually include plausible, but unexpectedly important, situations and problems that exist in some nascent form in the present day. Any particular scenario is unlikely. However, futures studies analysts select scenario features so they are both possible and uncomfortable. Scenario planning helps policy-makers and firms anticipate change, prepare responses, and create more robust strategies.^[10][11]

Scenario planning helps a firm anticipate the impact of different scenarios and identify weaknesses. When anticipated years in advance, those weaknesses can be avoided or their impacts reduced more effectively than when similar real-life problems are considered under the duress of an emergency. For example, a company may discover that it needs to change contractual terms to protect against a new class of risks, or collect cash reserves to purchase anticipated technologies or equipment. Flexible business continuity plans with «PREsponse protocols» can help cope with similar operational problems and deliver measurable future value.

Zero-sum game scenarios[edit]

Strategic military intelligence organizations also construct scenarios. The methods and organizations are almost identical, except that scenario planning is applied to a wider variety of problems than merely military and political problems.

As in military intelligence, the chief challenge of scenario planning is to find out the real needs of policy-makers, when policy-makers may not themselves know what they need to know, or may not know how to describe the information that they really want.

Good analysts design wargames so that policy makers have great flexibility and freedom to adapt their simulated organisations.^[12] Then these simulated organizations are «stressed» by the scenarios as a game plays out. Usually, particular groups of facts become more clearly important. These insights enable intelligence organizations to refine and repackage real information more precisely to better serve the policy-makers’ real-life needs. Usually the games’ simulated time runs hundreds of times faster than real life, so policy-makers experience several years of policy decisions, and their simulated effects, in less than a day.

This chief value of scenario planning is that it allows policy-makers to make and learn from mistakes without risking career-limiting failures in real life. Further, policymakers can make these mistakes in a safe, unthreatening, game-like environment, while responding to a wide variety of concretely presented situations based on facts. This is an opportunity to «rehearse the future», an opportunity that does not present itself in day-to-day operations where every action and decision counts.

How military scenario planning or scenario thinking is done[edit]

1. Decide on the key question to be answered by the analysis. By doing this, it is possible to assess whether scenario planning is preferred over the other methods. If the question is based on small changes or a very small number of elements, other more formalized methods may be more useful.
2. Set the time and scope of the analysis. Take into consideration how quickly changes have happened in the past, and try to assess to what degree it is possible to predict common trends in demographics, product life cycles. A usual timeframe can be five to 10 years.
3. Identify major stakeholders. Decide who will be affected and have an interest in the possible outcomes. Identify their current interests, whether and why these interests have changed over time in the past.
4. Map basic trends and driving forces. This includes industry, economic, political, technological, legal, and societal trends. Assess to what degree these trends will affect your research question. Describe each trend, how and why it will affect the organisation. In this step of the process, brainstorming is commonly used, where all trends that can be thought of are presented before they are assessed, to capture possible group thinking and tunnel vision.
5. Find key uncertainties. Map the driving forces on two axes, assessing each force on an uncertain/(relatively) predictable and important/unimportant scale. All driving forces that are considered unimportant are discarded. Important driving forces that are relatively predictable (ex. demographics) can be included in any scenario, so the scenarios should not be based on these. This leaves you with a number of important and unpredictable driving forces. At this point, it is also useful to assess whether any linkages between driving forces exist, and rule out any «impossible» scenarios (ex. full employment and zero inflation).
6. Check for the possibility to group the linked forces and if possible, reduce the forces to the two most important. (To allow the scenarios to be presented in a neat xy-diagram)
7. Identify the extremes of the possible outcomes of the two driving forces and check the dimensions for consistency and plausibility. Three key points should be assessed:
   1. Time frame: are the trends compatible within the time frame in question?
   2. Internal consistency: do the forces describe uncertainties that can construct probable scenarios.
   3. Vs the stakeholders: are any stakeholders currently in disequilibrium compared to their preferred situation, and will this evolve the scenario? Is it possible to create probable scenarios when considering the stakeholders? This is most important when creating macro-scenarios where governments, large organisations et al. will try to influence the outcome.
8. Define the scenarios, plotting them on a grid if possible. Usually, two to four scenarios are constructed. The current situation does not need to be in the middle of the diagram (inflation may already be low), and possible scenarios may keep one (or more) of the forces relatively constant, especially if using three or more driving forces. One approach can be to create all positive elements into one scenario and all negative elements (relative to the current situation) in another scenario, then refining these. In the end, try to avoid pure best-case and worst-case scenarios.
9. Write out the scenarios. Narrate what has happened and what the reasons can be for the proposed situation. Try to include good reasons why the changes have occurred as this helps the further analysis. Finally, give each scenario a descriptive (and catchy) name to ease later reference.
10. Assess the scenarios. Are they relevant for the goal? Are they internally consistent? Are they archetypical? Do they represent relatively stable outcome situations?
11. Identify research needs. Based on the scenarios, assess where more information is needed. Where needed, obtain more information on the motivations of stakeholders, possible innovations that may occur in the industry and so on.
12. Develop quantitative methods. If possible, develop models to help quantify consequences of the various scenarios, such as growth rate, cash flow etc. This step does of course require a significant amount of work compared to the others, and may be left out in back-of-the-envelope-analyses.
13. Converge towards decision scenarios. Retrace the steps above in an iterative process until you reach scenarios which address the fundamental issues facing the organization. Try to assess upsides and downsides of the possible scenarios.

Use by managers[edit]

The basic concepts of the process are relatively simple. In terms of the overall approach to forecasting, they can be divided into three main groups of activities (which are, generally speaking, common to all long range forecasting processes):^[13]

1. Environmental analysis
2. Scenario planning
3. Corporate strategy

The first of these groups quite simply comprises the normal environmental analysis. This is almost exactly the same as that which should be undertaken as the first stage of any serious long-range planning. However, the quality of this analysis is especially important in the context of scenario planning.

The central part represents the specific techniques – covered here – which differentiate the scenario forecasting process from the others in long-range planning.

The final group represents all the subsequent processes which go towards producing the corporate strategy and plans. Again, the requirements are slightly different but in general they follow all the rules of sound long-range planning.

Applications[edit]

Business[edit]

In the past, strategic plans have often considered only the «official future», which was usually a straight-line graph of current trends carried into the future. Often the trend lines were generated by the accounting department, and lacked discussions of demographics, or qualitative differences in social conditions.^[5]

These simplistic guesses are surprisingly good most of the time, but fail to consider qualitative social changes that can affect a business or government. Paul J. H. Schoemaker offers a strong managerial case for the use of scenario planning in business and had wide impact.^[14]

The approach may have had more impact outside Shell than within, as many others firms and consultancies started to benefit as well from scenario planning. Scenario planning is as much art as science, and prone to a variety of traps (both in process and content) as enumerated by Paul J. H. Schoemaker.^[14] More recently scenario planning has been discussed as a tool to improve the strategic agility, by cognitively preparing not only multiple scenarios but also multiple consistent strategies.^[10]

Military[edit]

Scenario planning is also extremely popular with military planners. Most states’ department of war maintains a continuously updated series of strategic plans to cope with well-known military or strategic problems. These plans are almost always based on scenarios, and often the plans and scenarios are kept up-to-date by war games, sometimes played out with real troops. This process was first carried out (arguably the method was invented by) the Prussian general staff of the mid-19th century.

Finance[edit]

In economics and finance, a financial institution might use scenario analysis to forecast several possible scenarios for the economy (e.g. rapid growth, moderate growth, slow growth) and for financial market returns (for bonds, stocks and cash) in each of those scenarios. It might consider sub-sets of each of the possibilities. It might further seek to determine correlations and assign probabilities to the scenarios (and sub-sets if any). Then it will be in a position to consider how to distribute assets between asset types (i.e. asset allocation); the institution can also calculate the scenario-weighted expected return (which figure will indicate the overall attractiveness of the financial environment). It may also perform stress testing, using adverse scenarios.^[15]

Depending on the complexity of the problem, scenario analysis can be a demanding exercise. It can be difficult to foresee what the future holds (e.g. the actual future outcome may be entirely unexpected), i.e. to foresee what the scenarios are, and to assign probabilities to them; and this is true of the general forecasts never mind the implied financial market returns. The outcomes can be modeled mathematically/statistically e.g. taking account of possible variability within single scenarios as well as possible relationships between scenarios. In general, one should take care when assigning probabilities to different scenarios as this could invite a tendency to consider only the scenario with the highest probability.^[16]

Geopolitics[edit]

In politics or geopolitics, scenario analysis involves reflecting on the possible alternative paths of a social or political environment and possibly diplomatic and war risks.

History of use by academic and commercial organizations[edit]

Most authors attribute the introduction of scenario planning to Herman Kahn through his work for the US Military in the 1950s at the RAND Corporation where he developed a technique of describing the future in stories as if written by people in the future. He adopted the term «scenarios» to describe these stories. In 1961 he founded the Hudson Institute where he expanded his scenario work to social forecasting and public policy.^{[17][18][19][20][21]} One of his most controversial uses of scenarios was to suggest that a nuclear war could be won.^[22] Though Kahn is often cited as the father of scenario planning, at the same time Kahn was developing his methods at RAND, Gaston Berger was developing similar methods at the Centre d’Etudes Prospectives which he founded in France. His method, which he named ‘La Prospective’, was to develop normative scenarios of the future which were to be used as a guide in formulating public policy. During the mid-1960s various authors from the French and American institutions began to publish scenario planning concepts such as ‘La Prospective’ by Berger in 1964^[23] and ‘The Next Thirty-Three Years’ by Kahn and Wiener in 1967.^[24] By the 1970s scenario planning was in full swing with a number of institutions now established to provide support to business including the Hudson Foundation, the Stanford Research Institute (now SRI International), and the SEMA Metra Consulting Group in France. Several large companies also began to embrace scenario planning including DHL Express, Dutch Royal Shell and General Electric.^{[19][21][25][26]}

Possibly as a result of these very sophisticated approaches, and of the difficult techniques they employed (which usually demanded the resources of a central planning staff), scenarios earned a reputation for difficulty (and cost) in use. Even so, the theoretical importance of the use of alternative scenarios, to help address the uncertainty implicit in long-range forecasts, was dramatically underlined by the widespread confusion which followed the Oil Shock of 1973. As a result, many of the larger organizations started to use the technique in one form or another. By 1983 Diffenbach reported that ‘alternate scenarios’ were the third most popular technique for long-range forecasting – used by 68% of the large organizations he surveyed.^[27]

Practical development of scenario forecasting, to guide strategy rather than for the more limited academic uses which had previously been the case, was started by Pierre Wack in 1971 at the Royal Dutch Shell group of companies – and it, too, was given impetus by the Oil Shock two years later. Shell has, since that time, led the commercial world in the use of scenarios – and in the development of more practical techniques to support these. Indeed, as – in common with most forms of long-range forecasting – the use of scenarios has (during the depressed trading conditions of the last decade) reduced to only a handful of private-sector organisations, Shell remains almost alone amongst them in keeping the technique at the forefront of forecasting.^[28]

There has only been anecdotal evidence offered in support of the value of scenarios, even as aids to forecasting; and most of this has come from one company – Shell. In addition, with so few organisations making consistent use of them – and with the timescales involved reaching into decades – it is unlikely that any definitive supporting evidenced will be forthcoming in the foreseeable future. For the same reasons, though, a lack of such proof applies to almost all long-range planning techniques. In the absence of proof, but taking account of Shell’s well documented experiences of using it over several decades (where, in the 1990s, its then CEO ascribed its success to its use of such scenarios), can be significant benefit to be obtained from extending the horizons of managers’ long-range forecasting in the way that the use of scenarios uniquely does.^[13]

Process[edit]

The part of the overall process which is radically different from most other forms of long-range planning is the central section, the actual production of the scenarios. Even this, though, is relatively simple, at its most basic level. As derived from the approach most commonly used by Shell,^[29] it follows six steps:^[30]

1. Decide drivers for change/assumptions
2. Bring drivers together into a viable framework
3. Produce 7–9 initial mini-scenarios
4. Reduce to 2–3 scenarios
5. Draft the scenarios
6. Identify the issues arising

Step 1 – decide assumptions/drivers for change[edit]

The first stage is to examine the results of environmental analysis to determine which are the most important factors that will decide the nature of the future environment within which the organisation operates. These factors are sometimes called ‘variables’ (because they will vary over the time being investigated, though the terminology may confuse scientists who use it in a more rigorous manner). Users tend to prefer the term ‘drivers’ (for change), since this terminology is not laden with quasi-scientific connotations and reinforces the participant’s commitment to search for those forces which will act to change the future. Whatever the nomenclature, the main requirement is that these will be informed assumptions.

This is partly a process of analysis, needed to recognise what these ‘forces’ might be. However, it is likely that some work on this element will already have taken place during the preceding environmental analysis. By the time the formal scenario planning stage has been reached, the participants may have already decided – probably in their sub-conscious rather than formally – what the main forces are.

In the ideal approach, the first stage should be to carefully decide the overall assumptions on which the scenarios will be based. Only then, as a second stage, should the various drivers be specifically defined. Participants, though, seem to have problems in separating these stages.

Perhaps the most difficult aspect though, is freeing the participants from the preconceptions they take into the process with them. In particular, most participants will want to look at the medium term, five to ten years ahead rather than the required longer-term, ten or more years ahead. However, a time horizon of anything less than ten years often leads participants to extrapolate from present trends, rather than consider the alternatives which might face them. When, however, they are asked to consider timescales in excess of ten years they almost all seem to accept the logic of the scenario planning process, and no longer fall back on that of extrapolation. There is a similar problem with expanding participants horizons to include the whole external environment.

Brainstorming

In any case, the brainstorming which should then take place, to ensure that the list is complete, may unearth more variables – and, in particular, the combination of factors may suggest yet others.

A very simple technique which is especially useful at this – brainstorming – stage, and in general for handling scenario planning debates is derived from use in Shell where this type of approach is often used. An especially easy approach, it only requires a conference room with a bare wall and copious supplies of 3M Post-It Notes.

The six to ten people ideally taking part in such face-to-face debates should be in a conference room environment which is isolated from outside interruptions. The only special requirement is that the conference room has at least one clear wall on which Post-It notes will stick. At the start of the meeting itself, any topics which have already been identified during the environmental analysis stage are written (preferably with a thick magic marker, so they can be read from a distance) on separate Post-It Notes. These Post-It Notes are then, at least in theory, randomly placed on the wall. In practice, even at this early stage the participants will want to cluster them in groups which seem to make sense. The only requirement (which is why Post-It Notes are ideal for this approach) is that there is no bar to taking them off again and moving them to a new cluster.

A similar technique – using 5″ by 3″ index cards – has also been described (as the ‘Snowball Technique’), by Backoff and Nutt, for grouping and evaluating ideas in general.^[31]

As in any form of brainstorming, the initial ideas almost invariably stimulate others. Indeed, everyone should be encouraged to add their own Post-It Notes to those on the wall. However it differs from the ‘rigorous’ form described in ‘creative thinking’ texts, in that it is much slower paced and the ideas are discussed immediately. In practice, as many ideas may be removed, as not being relevant, as are added. Even so, it follows many of the same rules as normal brainstorming and typically lasts the same length of time – say, an hour or so only.

It is important that all the participants feel they ‘own’ the wall – and are encouraged to move the notes around themselves. The result is a very powerful form of creative decision-making for groups, which is applicable to a wide range of situations (but is especially powerful in the context of scenario planning). It also offers a very good introduction for those who are coming to the scenario process for the first time. Since the workings are largely self-evident, participants very quickly come to understand exactly what is involved.

Important and uncertain

This step is, though, also one of selection – since only the most important factors will justify a place in the scenarios. The 80:20 Rule here means that, at the end of the process, management’s attention must be focused on a limited number of most important issues. Experience has proved that offering a wider range of topics merely allows them to select those few which interest them, and not necessarily those which are most important to the organisation.

In addition, as scenarios are a technique for presenting alternative futures, the factors to be included must be genuinely ‘variable’. They should be subject to significant alternative outcomes. Factors whose outcome is predictable, but important, should be spelled out in the introduction to the scenarios (since they cannot be ignored). The Important Uncertainties Matrix, as reported by Kees van der Heijden of Shell, is a useful check at this stage.^[32]

At this point it is also worth pointing out that a great virtue of scenarios is that they can accommodate the input from any other form of forecasting. They may use figures, diagrams or words in any combination. No other form of forecasting offers this flexibility.

Step 2 – bring drivers together into a viable framework[edit]

The next step is to link these drivers together to provide a meaningful framework. This may be obvious, where some of the factors are clearly related to each other in one way or another. For instance, a technological factor may lead to market changes, but may be constrained by legislative factors. On the other hand, some of the ‘links’ (or at least the ‘groupings’) may need to be artificial at this stage. At a later stage more meaningful links may be found, or the factors may then be rejected from the scenarios. In the most theoretical approaches to the subject, probabilities are attached to the event strings. This is difficult to achieve, however, and generally adds little – except complexity – to the outcomes.

This is probably the most (conceptually) difficult step. It is where managers’ ‘intuition’ – their ability to make sense of complex patterns of ‘soft’ data which more rigorous analysis would be unable to handle – plays an important role. There are, however, a range of techniques which can help; and again the Post-It-Notes approach is especially useful:

Thus, the participants try to arrange the drivers, which have emerged from the first stage, into groups which seem to make sense to them. Initially there may be many small groups. The intention should, therefore, be to gradually merge these (often having to reform them from new combinations of drivers to make these bigger groups work). The aim of this stage is eventually to make 6–8 larger groupings; ‘mini-scenarios’. Here the Post-It Notes may be moved dozens of times over the length – perhaps several hours or more – of each meeting. While this process is taking place the participants will probably want to add new topics – so more Post-It Notes are added to the wall. In the opposite direction, the unimportant ones are removed (possibly to be grouped, again as an ‘audit trail’ on another wall). More important, the ‘certain’ topics are also removed from the main area of debate – in this case they must be grouped in clearly labelled area of the main wall.

As the clusters – the ‘mini-scenarios’ – emerge, the associated notes may be stuck to each other rather than individually to the wall; which makes it easier to move the clusters around (and is a considerable help during the final, demanding stage to reducing the scenarios to two or three).

The great benefit of using Post-It Notes is that there is no bar to participants changing their minds. If they want to rearrange the groups – or simply to go back (iterate) to an earlier stage – then they strip them off and put them in their new position.

Step 3 – produce initial mini-scenarios[edit]

The outcome of the previous step is usually between seven and nine logical groupings of drivers. This is usually easy to achieve. The ‘natural’ reason for this may be that it represents some form of limit as to what participants can visualise.

Having placed the factors in these groups, the next action is to work out, very approximately at this stage, what is the connection between them. What does each group of factors represent?

Step 4 – reduce to two or three scenarios[edit]

The main action, at this next stage, is to reduce the seven to nine mini-scenarios/groupings detected at the previous stage to two or three larger scenarios

There is no theoretical reason for reducing to just two or three scenarios, only a practical one. It has been found that the managers who will be asked to use the final scenarios can only cope effectively with a maximum of three versions! Shell started, more than three decades ago, by building half a dozen or more scenarios – but found that the outcome was that their managers selected just one of these to concentrate on. As a result, the planners reduced the number to three, which managers could handle easily but could no longer so easily justify the selection of only one! This is the number now recommended most frequently in most of the literature.

Complementary scenarios

As used by Shell, and as favoured by a number of the academics, two scenarios should be complementary; the reason being that this helps avoid managers ‘choosing’ just one, ‘preferred’, scenario – and lapsing once more into single-track forecasting (negating the benefits of using ‘alternative’ scenarios to allow for alternative, uncertain futures). This is, however, a potentially difficult concept to grasp, where managers are used to looking for opposites; a good and a bad scenario, say, or an optimistic one versus a pessimistic one – and indeed this is the approach (for small businesses) advocated by Foster. In the Shell approach, the two scenarios are required to be equally likely, and between them to cover all the ‘event strings’/drivers. Ideally they should not be obvious opposites, which might once again bias their acceptance by users, so the choice of ‘neutral’ titles is important. For example, Shell’s two scenarios at the beginning of the 1990s were titled ‘Sustainable World’ and ‘Global Mercantilism'[xv]. In practice, we found that this requirement, much to our surprise, posed few problems for the great majority, 85%, of those in the survey; who easily produced ‘balanced’ scenarios. The remaining 15% mainly fell into the expected trap of ‘good versus bad’. We have found that our own relatively complex (OBS) scenarios can also be made complementary to each other; without any great effort needed from the teams involved; and the resulting two scenarios are both developed further by all involved, without unnecessary focusing on one or the other.

Testing

Having grouped the factors into these two scenarios, the next step is to test them, again, for viability. Do they make sense to the participants? This may be in terms of logical analysis, but it may also be in terms of intuitive ‘gut-feel’. Once more, intuition often may offer a useful – if academically less respectable – vehicle for reacting to the complex and ill-defined issues typically involved. If the scenarios do not intuitively ‘hang together’, why not? The usual problem is that one or more of the assumptions turns out to be unrealistic in terms of how the participants see their world. If this is the case then you need to return to the first step – the whole scenario planning process is above all an iterative one (returning to its beginnings a number of times until the final outcome makes the best sense).

Step 5 – write the scenarios[edit]

The scenarios are then ‘written up’ in the most suitable form. The flexibility of this step often confuses participants, for they are used to forecasting processes which have a fixed format. The rule, though, is that you should produce the scenarios in the form most suitable for use by the managers who are going to base their strategy on them. Less obviously, the managers who are going to implement this strategy should also be taken into account. They will also be exposed to the scenarios, and will need to believe in these. This is essentially a ‘marketing’ decision, since it will be very necessary to ‘sell’ the final results to the users. On the other hand, a not inconsiderable consideration may be to use the form the author also finds most comfortable. If the form is alien to him or her the chances are that the resulting scenarios will carry little conviction when it comes to the ‘sale’.

Most scenarios will, perhaps, be written in word form (almost as a series of alternative essays about the future); especially where they will almost inevitably be qualitative which is hardly surprising where managers, and their audience, will probably use this in their day to day communications. Some, though use an expanded series of lists and some enliven their reports by adding some fictional ‘character’ to the material – perhaps taking literally the idea that they are stories about the future – though they are still clearly intended to be factual. On the other hand, they may include numeric data and/or diagrams – as those of Shell do (and in the process gain by the acid test of more measurable ‘predictions’).

Step 6 – identify issues arising[edit]

The final stage of the process is to examine these scenarios to determine what are the most critical outcomes; the ‘branching points’ relating to the ‘issues’ which will have the greatest impact (potentially generating ‘crises’) on the future of the organisation. The subsequent strategy will have to address these – since the normal approach to strategy deriving from scenarios is one which aims to minimise risk by being ‘robust’ (that is it will safely cope with all the alternative outcomes of these ‘life and death’ issues) rather than aiming for performance (profit) maximisation by gambling on one outcome.

Use of scenarios[edit]

It is important to note that scenarios may be used in a number of ways:

a) Containers for the drivers/event strings

Most basically, they are a logical device, an artificial framework, for presenting the individual factors/topics (or coherent groups of these) so that these are made easily available for managers’ use – as useful ideas about future developments in their own right – without reference to the rest of the scenario. It should be stressed that no factors should be dropped, or even given lower priority, as a result of producing the scenarios. In this context, which scenario contains which topic (driver), or issue about the future, is irrelevant.

b) Tests for consistency

At every stage it is necessary to iterate, to check that the contents are viable and make any necessary changes to ensure that they are; here the main test is to see if the scenarios seem to be internally consistent – if they are not then the writer must loop back to earlier stages to correct the problem. Though it has been mentioned previously, it is important to stress once again that scenario building is ideally an iterative process. It usually does not just happen in one meeting – though even one attempt is better than none – but takes place over a number of meetings as the participants gradually refine their ideas.

c) Positive perspectives

Perhaps the main benefit deriving from scenarios, however, comes from the alternative ‘flavors’ of the future their different perspectives offer. It is a common experience, when the scenarios finally emerge, for the participants to be startled by the insight they offer – as to what the general shape of the future might be – at this stage it no longer is a theoretical exercise but becomes a genuine framework (or rather set of alternative frameworks) for dealing with that.

Scenario planning compared to other techniques[edit]

The flowchart to the right provides a process for classifying a phenomenon as a scenario in the intuitive logics tradition.^[33]

Scenario planning differs from contingency planning, sensitivity analysis and computer simulations.^[34]

Contingency planning is a «What if» tool, that only takes into account one uncertainty. However, scenario planning considers combinations of uncertainties in each scenario. Planners also try to select especially plausible but uncomfortable combinations of social developments.

Sensitivity analysis analyzes changes in one variable only, which is useful for simple changes, while scenario planning tries to expose policy makers to significant interactions of major variables.

While scenario planning can benefit from computer simulations, scenario planning is less formalized, and can be used to make plans for qualitative patterns that show up in a wide variety of simulated events.

During the past 5 years, computer supported Morphological Analysis has been employed as aid in scenario development by the Swedish Defence Research Agency in Stockholm.^[35] This method makes it possible to create a multi-variable morphological field which can be treated as an inference model – thus integrating scenario planning techniques with contingency analysis and sensitivity analysis.

Scenario analysis[edit]

Scenario analysis is a process of analyzing future events by considering alternative possible outcomes (sometimes called «alternative worlds»). Thus, scenario analysis, which is one of the main forms of projection, does not try to show one exact picture of the future. Instead, it presents several alternative future developments. Consequently, a scope of possible future outcomes is observable. Not only are the outcomes observable, also the development paths leading to the outcomes. In contrast to prognoses, the scenario analysis is not based on extrapolation of the past or the extension of past trends. It does not rely on historical data and does not expect past observations to remain valid in the future. Instead, it tries to consider possible developments and turning points, which may only be connected to the past. In short, several scenarios are fleshed out in a scenario analysis to show possible future outcomes. Each scenario normally combines optimistic, pessimistic, and more and less probable developments. However, all aspects of scenarios should be plausible. Although highly discussed, experience has shown that around three scenarios are most appropriate for further discussion and selection. More scenarios risks making the analysis overly complicated.^[36][37] Scenarios are often confused with other tools and approaches to planning. The flowchart to the right provides a process for classifying a phenomenon as a scenario in the intuitive logics tradition.^[38]

Principle[edit]

Scenario-building is designed to allow improved decision-making by allowing deep consideration of outcomes and their implications.

A scenario is a tool used during requirements analysis to describe a specific use of a proposed system. Scenarios capture the system, as viewed from the outside

Scenario analysis can also be used to illuminate «wild cards.» For example, analysis of the possibility of the earth being struck by a meteor suggests that whilst the probability is low, the damage inflicted is so high that the event is much more important (threatening) than the low probability (in any one year) alone would suggest. However, this possibility is usually disregarded by organizations using scenario analysis to develop a strategic plan since it has such overarching repercussions.

Combination of Delphi and scenarios[edit]

Scenario planning concerns planning based on the systematic examination of the future by picturing plausible and consistent images of that future. The Delphi method attempts to develop systematically expert opinion consensus concerning future developments and events. It is a judgmental forecasting procedure in the form of an anonymous, written, multi-stage survey process, where feedback of group opinion is provided after each round.

Numerous researchers have stressed that both approaches are best suited to be combined.^[39][40] Due to their process similarity, the two methodologies can be easily combined. The output of the different phases of the Delphi method can be used as input for the scenario method and vice versa. A combination makes a realization of the benefits of both tools possible. In practice, usually one of the two tools is considered the dominant methodology and the other one is added on at some stage.

The variant that is most often found in practice is the integration of the Delphi method into the scenario process (see e.g. Rikkonen, 2005;^[41] von der Gracht, 2008;^[42]). Authors refer to this type as Delphi-scenario (writing), expert-based scenarios, or Delphi panel derived scenarios. Von der Gracht (2010)^[43] is a scientifically valid example of this method. Since scenario planning is “information hungry”, Delphi research can deliver valuable input for the process. There are various types of information output of Delphi that can be used as input for scenario planning. Researchers can, for example, identify relevant events or developments and, based on expert opinion, assign probabilities to them. Moreover, expert comments and arguments provide deeper insights into relationships of factors that can, in turn, be integrated into scenarios afterwards. Also, Delphi helps to identify extreme opinions and dissent among the experts. Such controversial topics are particularly suited for extreme scenarios or wildcards.

In his doctoral thesis, Rikkonen (2005)^[41] examined the utilization of Delphi techniques in scenario planning and, concretely, in construction of scenarios. The author comes to the conclusion that the Delphi technique has instrumental value in providing different alternative futures and the argumentation of scenarios. It is therefore recommended to use Delphi in order to make the scenarios more profound and to create confidence in scenario planning. Further benefits lie in the simplification of the scenario writing process and the deep understanding of the interrelations between the forecast items and social factors.

Critique[edit]

While there is utility in weighting hypotheses and branching potential outcomes from them, reliance on scenario analysis without reporting some parameters of measurement accuracy (standard errors, confidence intervals of estimates, metadata, standardization and coding, weighting for non-response, error in reportage, sample design, case counts, etc.) is a poor second to traditional prediction. Especially in “complex” problems, factors and assumptions do not correlate in lockstep fashion. Once a specific sensitivity is undefined, it may call the entire study into question.

It is faulty logic to think, when arbitrating results, that a better hypothesis will render empiricism unnecessary. In this respect, scenario analysis tries to defer statistical laws (e.g., Chebyshev’s inequality Law), because the decision rules occur outside a constrained setting. Outcomes are not permitted to “just happen”; rather, they are forced to conform to arbitrary hypotheses ex post, and therefore there is no footing on which to place expected values. In truth, there are no ex ante expected values, only hypotheses, and one is left wondering about the roles of modeling and data decision. In short, comparisons of «scenarios» with outcomes are biased by not deferring to the data; this may be convenient, but it is indefensible.

“Scenario analysis” is no substitute for complete and factual exposure of survey error in economic studies. In traditional prediction, given the data used to model the problem, with a reasoned specification and technique, an analyst can state, within a certain percentage of statistical error, the likelihood of a coefficient being within a certain numerical bound. This exactitude need not come at the expense of very disaggregated statements of hypotheses. R Software, specifically the module “WhatIf,”^[44] (in the context, see also Matchit and Zelig) has been developed for causal inference, and to evaluate counterfactuals. These programs have fairly sophisticated treatments for determining model dependence, in order to state with precision how sensitive the results are to models not based on empirical evidence.

Another challenge of scenario-building is that «predictors are part of the social context about which they are trying to make a prediction and may influence that context in the process».^[45] As a consequence, societal predictions can become self-destructing.^[45] For example, a scenario in which a large percentage of a population will become HIV infected based on existing trends may cause more people to avoid risky behavior and thus reduce the HIV infection rate, invalidating the forecast (which might have remained correct if it had not been publicly known). Or, a prediction that cybersecurity will become a major issue may cause organizations to implement more secure cybersecurity measures, thus limiting the issue.

Critique of Shell’s use of scenario planning[edit]

In the 1970s, many energy companies were surprised by both environmentalism and the OPEC cartel, and thereby lost billions of dollars of revenue by mis-investment. The dramatic financial effects of these changes led at least one organization, Royal Dutch Shell, to implement scenario planning. The analysts of this company publicly estimated that this planning process made their company the largest in the world.^[46] However other observers^[who?] of Shell’s use of scenario planning have suggested that few if any significant long-term business advantages accrued to Shell from the use of scenario methodology^{[citation needed]}. Whilst the intellectual robustness of Shell’s long term scenarios was seldom in doubt their actual practical use was seen as being minimal by many senior Shell executives^{[citation needed]}. A Shell insider has commented «The scenario team were bright and their work was of a very high intellectual level. However neither the high level «Group scenarios» nor the country level scenarios produced with operating companies really made much difference when key decisions were being taken».^{[citation needed]}

The use of scenarios was audited by Arie de Geus’s team in the early 1980s and they found that the decision-making processes following the scenarios were the primary cause of the lack of strategic implementation^{[clarification needed]}), rather than the scenarios themselves. Many practitioners today spend as much time on the decision-making process as on creating the scenarios themselves.^[47]

See also[edit]

• ACEGES – an agent-based model for scenario analysis
• Counter-revolutionary
• Decentralized planning (economics)
• Disruptive innovation
• Hoshin Kanri#Hoshin planning
• Futures studies
• Global Scenario Group
• Resilience (organizational)
• Robust decision-making
• Scenario (computing)

Similar terminology[edit]

• Feedback loop
• System dynamics (also known as Stock and flow)
• System thinking

Analogous concepts[edit]

• Delphi method, including Real-time Delphi
• Game theory
• Horizon scanning
• Morphological analysis
• Rational choice theory
• Stress testing
• Twelve leverage points

Examples[edit]

• CIM-10 Bomarc (relied on Semi-Automatic Ground Environment)
• Climate change mitigation scenarios – possible futures in which global warming is reduced by deliberate actions
• Covert United States foreign regime change actions
• Dynamic Analysis and Replanning Tool
• Energy modeling – the process of building computer models of energy systems
• Floodplain
• Nijinomatsubara
• Pentagon Papers

References[edit]

Additional Bibliography[edit]

• D. Erasmus, The future of ICT in financial services: The Rabobank ICT scenarios (2008).
• M. Godet, Scenarios and Strategic Management, Butterworths (1987).
• M. Godet, From Anticipation to Action: A Handbook of Strategic Prospective. Paris: Unesco, (1993).
• Adam Kahane, Solving Tough Problems: An Open Way of Talking, Listening, and Creating New Realities (2007)
• H. Kahn, The Year 2000, Calman-Levy (1967).
• Herbert Meyer, «Real World Intelligence», Weidenfeld & Nicolson, 1987,
• National Intelligence Council (NIC) Archived 2012-07-28 at the Wayback Machine, «Mapping the Global Future», 2005,
• M. Lindgren & H. Bandhold, Scenario planning – the link between future and strategy, Palgrave Macmillan, 2003
• G. Wright& G. Cairns, Scenario thinking: practical approaches to the future, Palgrave Macmillan, 2011
• A. Schuehly, F. Becker t& F. Klein, Real Time Strategy: When Strategic Foresight Meets Artificial Intelligence, Emerald, 2020*
• A. Ruser, Sociological Quasi-Labs: The Case for Deductive Scenario Development, Current Sociology Vol63(2): 170-181, https://journals.sagepub.com/doi/pdf/10.1177/0011392114556581

Scientific Journals[edit]

• Foresight
• Futures
• Futures & Foresight Science
• Journal of Futures Studies
• Technological Forecasting and Social Change

External links[edit]

• Wikifutures wiki; Scenario page—wiki also includes several scenarios (GFDL licensed)
• ScenarioThinking.org —more than 100 scenarios developed on various global issues, on a wiki for public use
• Shell Scenarios Resources—Resources on what scenarios are, Shell’s new and old scenario’s, explorer’s guide and other scenario resources
• Learn how to use Scenario Manager in Excel to do Scenario Analysis

Further reading[edit]

• «Learning from the Future: Competitive Foresight Scenarios», Liam Fahey and Robert M. Randall, Published by John Wiley and Sons, 1997, ISBN 0-471-30352-6, Google book
• «Shirt-sleeve approach to long-range plans.», Linneman, Robert E, Kennell, John D.; Harvard Business Review; Mar/Apr77, Vol. 55 Issue 2, p141

Scenario planning, scenario thinking, scenario analysis,^[1] scenario prediction^[2] and the scenario method^[3] all describe a strategic planning method that some organizations use to make flexible long-term plans. It is in large part an adaptation and generalization of classic methods used by military intelligence.^[4]

In the most common application of the method, analysts generate simulation games for policy makers. The method combines known facts, such as demographics, geography and mineral reserves, with military, political, and industrial information, and key driving forces identified by considering social, technical, economic, environmental, and political («STEEP») trends.

In business applications, the emphasis on understanding the behavior of opponents has been reduced while more attention is now paid to changes in the natural environment. At Royal Dutch Shell for example, scenario planning has been described as changing mindsets about the exogenous part of the world prior to formulating specific strategies.^[5][6]

Scenario planning may involve aspects of systems thinking, specifically the recognition that many factors may combine in complex ways to create sometimes surprising futures (due to non-linear feedback loops). The method also allows the inclusion of factors that are difficult to formalize, such as novel insights about the future, deep shifts in values, and unprecedented regulations or inventions.^[7] Systems thinking used in conjunction with scenario planning leads to plausible scenario storylines because the causal relationship between factors can be demonstrated.^[8] These cases, in which scenario planning is integrated with a systems thinking approach to scenario development, are sometimes referred to as «dynamic scenarios».

Critics of using a subjective and heuristic methodology to deal with uncertainty and complexity argue that the technique has not been examined rigorously, nor influenced sufficiently by scientific evidence. They caution against using such methods to «predict» based on what can be described as arbitrary themes and «forecasting techniques».

A challenge and a strength of scenario-building is that «predictors are part of the social context about which they are trying to make a prediction and may influence that context in the process».^[9] As a consequence, societal predictions can become self-destructing. For example, a scenario in which a large percentage of a population will become HIV infected based on existing trends may cause more people to avoid risky behavior and thus reduce the HIV infection rate, invalidating the forecast (which might have remained correct if it had not been publicly known). Or, a prediction that cybersecurity will become a major issue may cause organizations to implement more secure cybersecurity measures, thus limiting the issue.^[9]

Principle[edit]

Crafting scenarios[edit]

Combinations and permutations of fact and related social changes are called «scenarios». Scenarios usually include plausible, but unexpectedly important, situations and problems that exist in some nascent form in the present day. Any particular scenario is unlikely. However, futures studies analysts select scenario features so they are both possible and uncomfortable. Scenario planning helps policy-makers and firms anticipate change, prepare responses, and create more robust strategies.^[10][11]

Scenario planning helps a firm anticipate the impact of different scenarios and identify weaknesses. When anticipated years in advance, those weaknesses can be avoided or their impacts reduced more effectively than when similar real-life problems are considered under the duress of an emergency. For example, a company may discover that it needs to change contractual terms to protect against a new class of risks, or collect cash reserves to purchase anticipated technologies or equipment. Flexible business continuity plans with «PREsponse protocols» can help cope with similar operational problems and deliver measurable future value.

Zero-sum game scenarios[edit]

Strategic military intelligence organizations also construct scenarios. The methods and organizations are almost identical, except that scenario planning is applied to a wider variety of problems than merely military and political problems.

As in military intelligence, the chief challenge of scenario planning is to find out the real needs of policy-makers, when policy-makers may not themselves know what they need to know, or may not know how to describe the information that they really want.

Good analysts design wargames so that policy makers have great flexibility and freedom to adapt their simulated organisations.^[12] Then these simulated organizations are «stressed» by the scenarios as a game plays out. Usually, particular groups of facts become more clearly important. These insights enable intelligence organizations to refine and repackage real information more precisely to better serve the policy-makers’ real-life needs. Usually the games’ simulated time runs hundreds of times faster than real life, so policy-makers experience several years of policy decisions, and their simulated effects, in less than a day.

This chief value of scenario planning is that it allows policy-makers to make and learn from mistakes without risking career-limiting failures in real life. Further, policymakers can make these mistakes in a safe, unthreatening, game-like environment, while responding to a wide variety of concretely presented situations based on facts. This is an opportunity to «rehearse the future», an opportunity that does not present itself in day-to-day operations where every action and decision counts.

How military scenario planning or scenario thinking is done[edit]

1. Decide on the key question to be answered by the analysis. By doing this, it is possible to assess whether scenario planning is preferred over the other methods. If the question is based on small changes or a very small number of elements, other more formalized methods may be more useful.
2. Set the time and scope of the analysis. Take into consideration how quickly changes have happened in the past, and try to assess to what degree it is possible to predict common trends in demographics, product life cycles. A usual timeframe can be five to 10 years.
3. Identify major stakeholders. Decide who will be affected and have an interest in the possible outcomes. Identify their current interests, whether and why these interests have changed over time in the past.
4. Map basic trends and driving forces. This includes industry, economic, political, technological, legal, and societal trends. Assess to what degree these trends will affect your research question. Describe each trend, how and why it will affect the organisation. In this step of the process, brainstorming is commonly used, where all trends that can be thought of are presented before they are assessed, to capture possible group thinking and tunnel vision.
5. Find key uncertainties. Map the driving forces on two axes, assessing each force on an uncertain/(relatively) predictable and important/unimportant scale. All driving forces that are considered unimportant are discarded. Important driving forces that are relatively predictable (ex. demographics) can be included in any scenario, so the scenarios should not be based on these. This leaves you with a number of important and unpredictable driving forces. At this point, it is also useful to assess whether any linkages between driving forces exist, and rule out any «impossible» scenarios (ex. full employment and zero inflation).
6. Check for the possibility to group the linked forces and if possible, reduce the forces to the two most important. (To allow the scenarios to be presented in a neat xy-diagram)
7. Identify the extremes of the possible outcomes of the two driving forces and check the dimensions for consistency and plausibility. Three key points should be assessed:
   1. Time frame: are the trends compatible within the time frame in question?
   2. Internal consistency: do the forces describe uncertainties that can construct probable scenarios.
   3. Vs the stakeholders: are any stakeholders currently in disequilibrium compared to their preferred situation, and will this evolve the scenario? Is it possible to create probable scenarios when considering the stakeholders? This is most important when creating macro-scenarios where governments, large organisations et al. will try to influence the outcome.
8. Define the scenarios, plotting them on a grid if possible. Usually, two to four scenarios are constructed. The current situation does not need to be in the middle of the diagram (inflation may already be low), and possible scenarios may keep one (or more) of the forces relatively constant, especially if using three or more driving forces. One approach can be to create all positive elements into one scenario and all negative elements (relative to the current situation) in another scenario, then refining these. In the end, try to avoid pure best-case and worst-case scenarios.
9. Write out the scenarios. Narrate what has happened and what the reasons can be for the proposed situation. Try to include good reasons why the changes have occurred as this helps the further analysis. Finally, give each scenario a descriptive (and catchy) name to ease later reference.
10. Assess the scenarios. Are they relevant for the goal? Are they internally consistent? Are they archetypical? Do they represent relatively stable outcome situations?
11. Identify research needs. Based on the scenarios, assess where more information is needed. Where needed, obtain more information on the motivations of stakeholders, possible innovations that may occur in the industry and so on.
12. Develop quantitative methods. If possible, develop models to help quantify consequences of the various scenarios, such as growth rate, cash flow etc. This step does of course require a significant amount of work compared to the others, and may be left out in back-of-the-envelope-analyses.
13. Converge towards decision scenarios. Retrace the steps above in an iterative process until you reach scenarios which address the fundamental issues facing the organization. Try to assess upsides and downsides of the possible scenarios.

Use by managers[edit]

The basic concepts of the process are relatively simple. In terms of the overall approach to forecasting, they can be divided into three main groups of activities (which are, generally speaking, common to all long range forecasting processes):^[13]

1. Environmental analysis
2. Scenario planning
3. Corporate strategy

The first of these groups quite simply comprises the normal environmental analysis. This is almost exactly the same as that which should be undertaken as the first stage of any serious long-range planning. However, the quality of this analysis is especially important in the context of scenario planning.

The central part represents the specific techniques – covered here – which differentiate the scenario forecasting process from the others in long-range planning.

The final group represents all the subsequent processes which go towards producing the corporate strategy and plans. Again, the requirements are slightly different but in general they follow all the rules of sound long-range planning.

Applications[edit]

Business[edit]

In the past, strategic plans have often considered only the «official future», which was usually a straight-line graph of current trends carried into the future. Often the trend lines were generated by the accounting department, and lacked discussions of demographics, or qualitative differences in social conditions.^[5]

These simplistic guesses are surprisingly good most of the time, but fail to consider qualitative social changes that can affect a business or government. Paul J. H. Schoemaker offers a strong managerial case for the use of scenario planning in business and had wide impact.^[14]

The approach may have had more impact outside Shell than within, as many others firms and consultancies started to benefit as well from scenario planning. Scenario planning is as much art as science, and prone to a variety of traps (both in process and content) as enumerated by Paul J. H. Schoemaker.^[14] More recently scenario planning has been discussed as a tool to improve the strategic agility, by cognitively preparing not only multiple scenarios but also multiple consistent strategies.^[10]

Military[edit]

Scenario planning is also extremely popular with military planners. Most states’ department of war maintains a continuously updated series of strategic plans to cope with well-known military or strategic problems. These plans are almost always based on scenarios, and often the plans and scenarios are kept up-to-date by war games, sometimes played out with real troops. This process was first carried out (arguably the method was invented by) the Prussian general staff of the mid-19th century.

Finance[edit]

In economics and finance, a financial institution might use scenario analysis to forecast several possible scenarios for the economy (e.g. rapid growth, moderate growth, slow growth) and for financial market returns (for bonds, stocks and cash) in each of those scenarios. It might consider sub-sets of each of the possibilities. It might further seek to determine correlations and assign probabilities to the scenarios (and sub-sets if any). Then it will be in a position to consider how to distribute assets between asset types (i.e. asset allocation); the institution can also calculate the scenario-weighted expected return (which figure will indicate the overall attractiveness of the financial environment). It may also perform stress testing, using adverse scenarios.^[15]

Depending on the complexity of the problem, scenario analysis can be a demanding exercise. It can be difficult to foresee what the future holds (e.g. the actual future outcome may be entirely unexpected), i.e. to foresee what the scenarios are, and to assign probabilities to them; and this is true of the general forecasts never mind the implied financial market returns. The outcomes can be modeled mathematically/statistically e.g. taking account of possible variability within single scenarios as well as possible relationships between scenarios. In general, one should take care when assigning probabilities to different scenarios as this could invite a tendency to consider only the scenario with the highest probability.^[16]

Geopolitics[edit]

In politics or geopolitics, scenario analysis involves reflecting on the possible alternative paths of a social or political environment and possibly diplomatic and war risks.

History of use by academic and commercial organizations[edit]

Most authors attribute the introduction of scenario planning to Herman Kahn through his work for the US Military in the 1950s at the RAND Corporation where he developed a technique of describing the future in stories as if written by people in the future. He adopted the term «scenarios» to describe these stories. In 1961 he founded the Hudson Institute where he expanded his scenario work to social forecasting and public policy.^{[17][18][19][20][21]} One of his most controversial uses of scenarios was to suggest that a nuclear war could be won.^[22] Though Kahn is often cited as the father of scenario planning, at the same time Kahn was developing his methods at RAND, Gaston Berger was developing similar methods at the Centre d’Etudes Prospectives which he founded in France. His method, which he named ‘La Prospective’, was to develop normative scenarios of the future which were to be used as a guide in formulating public policy. During the mid-1960s various authors from the French and American institutions began to publish scenario planning concepts such as ‘La Prospective’ by Berger in 1964^[23] and ‘The Next Thirty-Three Years’ by Kahn and Wiener in 1967.^[24] By the 1970s scenario planning was in full swing with a number of institutions now established to provide support to business including the Hudson Foundation, the Stanford Research Institute (now SRI International), and the SEMA Metra Consulting Group in France. Several large companies also began to embrace scenario planning including DHL Express, Dutch Royal Shell and General Electric.^{[19][21][25][26]}

Possibly as a result of these very sophisticated approaches, and of the difficult techniques they employed (which usually demanded the resources of a central planning staff), scenarios earned a reputation for difficulty (and cost) in use. Even so, the theoretical importance of the use of alternative scenarios, to help address the uncertainty implicit in long-range forecasts, was dramatically underlined by the widespread confusion which followed the Oil Shock of 1973. As a result, many of the larger organizations started to use the technique in one form or another. By 1983 Diffenbach reported that ‘alternate scenarios’ were the third most popular technique for long-range forecasting – used by 68% of the large organizations he surveyed.^[27]

Practical development of scenario forecasting, to guide strategy rather than for the more limited academic uses which had previously been the case, was started by Pierre Wack in 1971 at the Royal Dutch Shell group of companies – and it, too, was given impetus by the Oil Shock two years later. Shell has, since that time, led the commercial world in the use of scenarios – and in the development of more practical techniques to support these. Indeed, as – in common with most forms of long-range forecasting – the use of scenarios has (during the depressed trading conditions of the last decade) reduced to only a handful of private-sector organisations, Shell remains almost alone amongst them in keeping the technique at the forefront of forecasting.^[28]

There has only been anecdotal evidence offered in support of the value of scenarios, even as aids to forecasting; and most of this has come from one company – Shell. In addition, with so few organisations making consistent use of them – and with the timescales involved reaching into decades – it is unlikely that any definitive supporting evidenced will be forthcoming in the foreseeable future. For the same reasons, though, a lack of such proof applies to almost all long-range planning techniques. In the absence of proof, but taking account of Shell’s well documented experiences of using it over several decades (where, in the 1990s, its then CEO ascribed its success to its use of such scenarios), can be significant benefit to be obtained from extending the horizons of managers’ long-range forecasting in the way that the use of scenarios uniquely does.^[13]

Process[edit]

The part of the overall process which is radically different from most other forms of long-range planning is the central section, the actual production of the scenarios. Even this, though, is relatively simple, at its most basic level. As derived from the approach most commonly used by Shell,^[29] it follows six steps:^[30]

1. Decide drivers for change/assumptions
2. Bring drivers together into a viable framework
3. Produce 7–9 initial mini-scenarios
4. Reduce to 2–3 scenarios
5. Draft the scenarios
6. Identify the issues arising

Step 1 – decide assumptions/drivers for change[edit]

The first stage is to examine the results of environmental analysis to determine which are the most important factors that will decide the nature of the future environment within which the organisation operates. These factors are sometimes called ‘variables’ (because they will vary over the time being investigated, though the terminology may confuse scientists who use it in a more rigorous manner). Users tend to prefer the term ‘drivers’ (for change), since this terminology is not laden with quasi-scientific connotations and reinforces the participant’s commitment to search for those forces which will act to change the future. Whatever the nomenclature, the main requirement is that these will be informed assumptions.

This is partly a process of analysis, needed to recognise what these ‘forces’ might be. However, it is likely that some work on this element will already have taken place during the preceding environmental analysis. By the time the formal scenario planning stage has been reached, the participants may have already decided – probably in their sub-conscious rather than formally – what the main forces are.

In the ideal approach, the first stage should be to carefully decide the overall assumptions on which the scenarios will be based. Only then, as a second stage, should the various drivers be specifically defined. Participants, though, seem to have problems in separating these stages.

Perhaps the most difficult aspect though, is freeing the participants from the preconceptions they take into the process with them. In particular, most participants will want to look at the medium term, five to ten years ahead rather than the required longer-term, ten or more years ahead. However, a time horizon of anything less than ten years often leads participants to extrapolate from present trends, rather than consider the alternatives which might face them. When, however, they are asked to consider timescales in excess of ten years they almost all seem to accept the logic of the scenario planning process, and no longer fall back on that of extrapolation. There is a similar problem with expanding participants horizons to include the whole external environment.

Brainstorming

In any case, the brainstorming which should then take place, to ensure that the list is complete, may unearth more variables – and, in particular, the combination of factors may suggest yet others.

A very simple technique which is especially useful at this – brainstorming – stage, and in general for handling scenario planning debates is derived from use in Shell where this type of approach is often used. An especially easy approach, it only requires a conference room with a bare wall and copious supplies of 3M Post-It Notes.

The six to ten people ideally taking part in such face-to-face debates should be in a conference room environment which is isolated from outside interruptions. The only special requirement is that the conference room has at least one clear wall on which Post-It notes will stick. At the start of the meeting itself, any topics which have already been identified during the environmental analysis stage are written (preferably with a thick magic marker, so they can be read from a distance) on separate Post-It Notes. These Post-It Notes are then, at least in theory, randomly placed on the wall. In practice, even at this early stage the participants will want to cluster them in groups which seem to make sense. The only requirement (which is why Post-It Notes are ideal for this approach) is that there is no bar to taking them off again and moving them to a new cluster.

A similar technique – using 5″ by 3″ index cards – has also been described (as the ‘Snowball Technique’), by Backoff and Nutt, for grouping and evaluating ideas in general.^[31]

As in any form of brainstorming, the initial ideas almost invariably stimulate others. Indeed, everyone should be encouraged to add their own Post-It Notes to those on the wall. However it differs from the ‘rigorous’ form described in ‘creative thinking’ texts, in that it is much slower paced and the ideas are discussed immediately. In practice, as many ideas may be removed, as not being relevant, as are added. Even so, it follows many of the same rules as normal brainstorming and typically lasts the same length of time – say, an hour or so only.

It is important that all the participants feel they ‘own’ the wall – and are encouraged to move the notes around themselves. The result is a very powerful form of creative decision-making for groups, which is applicable to a wide range of situations (but is especially powerful in the context of scenario planning). It also offers a very good introduction for those who are coming to the scenario process for the first time. Since the workings are largely self-evident, participants very quickly come to understand exactly what is involved.

Important and uncertain

This step is, though, also one of selection – since only the most important factors will justify a place in the scenarios. The 80:20 Rule here means that, at the end of the process, management’s attention must be focused on a limited number of most important issues. Experience has proved that offering a wider range of topics merely allows them to select those few which interest them, and not necessarily those which are most important to the organisation.

In addition, as scenarios are a technique for presenting alternative futures, the factors to be included must be genuinely ‘variable’. They should be subject to significant alternative outcomes. Factors whose outcome is predictable, but important, should be spelled out in the introduction to the scenarios (since they cannot be ignored). The Important Uncertainties Matrix, as reported by Kees van der Heijden of Shell, is a useful check at this stage.^[32]

At this point it is also worth pointing out that a great virtue of scenarios is that they can accommodate the input from any other form of forecasting. They may use figures, diagrams or words in any combination. No other form of forecasting offers this flexibility.

Step 2 – bring drivers together into a viable framework[edit]

The next step is to link these drivers together to provide a meaningful framework. This may be obvious, where some of the factors are clearly related to each other in one way or another. For instance, a technological factor may lead to market changes, but may be constrained by legislative factors. On the other hand, some of the ‘links’ (or at least the ‘groupings’) may need to be artificial at this stage. At a later stage more meaningful links may be found, or the factors may then be rejected from the scenarios. In the most theoretical approaches to the subject, probabilities are attached to the event strings. This is difficult to achieve, however, and generally adds little – except complexity – to the outcomes.

This is probably the most (conceptually) difficult step. It is where managers’ ‘intuition’ – their ability to make sense of complex patterns of ‘soft’ data which more rigorous analysis would be unable to handle – plays an important role. There are, however, a range of techniques which can help; and again the Post-It-Notes approach is especially useful:

Thus, the participants try to arrange the drivers, which have emerged from the first stage, into groups which seem to make sense to them. Initially there may be many small groups. The intention should, therefore, be to gradually merge these (often having to reform them from new combinations of drivers to make these bigger groups work). The aim of this stage is eventually to make 6–8 larger groupings; ‘mini-scenarios’. Here the Post-It Notes may be moved dozens of times over the length – perhaps several hours or more – of each meeting. While this process is taking place the participants will probably want to add new topics – so more Post-It Notes are added to the wall. In the opposite direction, the unimportant ones are removed (possibly to be grouped, again as an ‘audit trail’ on another wall). More important, the ‘certain’ topics are also removed from the main area of debate – in this case they must be grouped in clearly labelled area of the main wall.

As the clusters – the ‘mini-scenarios’ – emerge, the associated notes may be stuck to each other rather than individually to the wall; which makes it easier to move the clusters around (and is a considerable help during the final, demanding stage to reducing the scenarios to two or three).

The great benefit of using Post-It Notes is that there is no bar to participants changing their minds. If they want to rearrange the groups – or simply to go back (iterate) to an earlier stage – then they strip them off and put them in their new position.

Step 3 – produce initial mini-scenarios[edit]

The outcome of the previous step is usually between seven and nine logical groupings of drivers. This is usually easy to achieve. The ‘natural’ reason for this may be that it represents some form of limit as to what participants can visualise.

Having placed the factors in these groups, the next action is to work out, very approximately at this stage, what is the connection between them. What does each group of factors represent?

Step 4 – reduce to two or three scenarios[edit]

The main action, at this next stage, is to reduce the seven to nine mini-scenarios/groupings detected at the previous stage to two or three larger scenarios

There is no theoretical reason for reducing to just two or three scenarios, only a practical one. It has been found that the managers who will be asked to use the final scenarios can only cope effectively with a maximum of three versions! Shell started, more than three decades ago, by building half a dozen or more scenarios – but found that the outcome was that their managers selected just one of these to concentrate on. As a result, the planners reduced the number to three, which managers could handle easily but could no longer so easily justify the selection of only one! This is the number now recommended most frequently in most of the literature.

Complementary scenarios

As used by Shell, and as favoured by a number of the academics, two scenarios should be complementary; the reason being that this helps avoid managers ‘choosing’ just one, ‘preferred’, scenario – and lapsing once more into single-track forecasting (negating the benefits of using ‘alternative’ scenarios to allow for alternative, uncertain futures). This is, however, a potentially difficult concept to grasp, where managers are used to looking for opposites; a good and a bad scenario, say, or an optimistic one versus a pessimistic one – and indeed this is the approach (for small businesses) advocated by Foster. In the Shell approach, the two scenarios are required to be equally likely, and between them to cover all the ‘event strings’/drivers. Ideally they should not be obvious opposites, which might once again bias their acceptance by users, so the choice of ‘neutral’ titles is important. For example, Shell’s two scenarios at the beginning of the 1990s were titled ‘Sustainable World’ and ‘Global Mercantilism'[xv]. In practice, we found that this requirement, much to our surprise, posed few problems for the great majority, 85%, of those in the survey; who easily produced ‘balanced’ scenarios. The remaining 15% mainly fell into the expected trap of ‘good versus bad’. We have found that our own relatively complex (OBS) scenarios can also be made complementary to each other; without any great effort needed from the teams involved; and the resulting two scenarios are both developed further by all involved, without unnecessary focusing on one or the other.

Testing

Having grouped the factors into these two scenarios, the next step is to test them, again, for viability. Do they make sense to the participants? This may be in terms of logical analysis, but it may also be in terms of intuitive ‘gut-feel’. Once more, intuition often may offer a useful – if academically less respectable – vehicle for reacting to the complex and ill-defined issues typically involved. If the scenarios do not intuitively ‘hang together’, why not? The usual problem is that one or more of the assumptions turns out to be unrealistic in terms of how the participants see their world. If this is the case then you need to return to the first step – the whole scenario planning process is above all an iterative one (returning to its beginnings a number of times until the final outcome makes the best sense).

Step 5 – write the scenarios[edit]

The scenarios are then ‘written up’ in the most suitable form. The flexibility of this step often confuses participants, for they are used to forecasting processes which have a fixed format. The rule, though, is that you should produce the scenarios in the form most suitable for use by the managers who are going to base their strategy on them. Less obviously, the managers who are going to implement this strategy should also be taken into account. They will also be exposed to the scenarios, and will need to believe in these. This is essentially a ‘marketing’ decision, since it will be very necessary to ‘sell’ the final results to the users. On the other hand, a not inconsiderable consideration may be to use the form the author also finds most comfortable. If the form is alien to him or her the chances are that the resulting scenarios will carry little conviction when it comes to the ‘sale’.

Most scenarios will, perhaps, be written in word form (almost as a series of alternative essays about the future); especially where they will almost inevitably be qualitative which is hardly surprising where managers, and their audience, will probably use this in their day to day communications. Some, though use an expanded series of lists and some enliven their reports by adding some fictional ‘character’ to the material – perhaps taking literally the idea that they are stories about the future – though they are still clearly intended to be factual. On the other hand, they may include numeric data and/or diagrams – as those of Shell do (and in the process gain by the acid test of more measurable ‘predictions’).

Step 6 – identify issues arising[edit]

The final stage of the process is to examine these scenarios to determine what are the most critical outcomes; the ‘branching points’ relating to the ‘issues’ which will have the greatest impact (potentially generating ‘crises’) on the future of the organisation. The subsequent strategy will have to address these – since the normal approach to strategy deriving from scenarios is one which aims to minimise risk by being ‘robust’ (that is it will safely cope with all the alternative outcomes of these ‘life and death’ issues) rather than aiming for performance (profit) maximisation by gambling on one outcome.

Use of scenarios[edit]

It is important to note that scenarios may be used in a number of ways:

a) Containers for the drivers/event strings

Most basically, they are a logical device, an artificial framework, for presenting the individual factors/topics (or coherent groups of these) so that these are made easily available for managers’ use – as useful ideas about future developments in their own right – without reference to the rest of the scenario. It should be stressed that no factors should be dropped, or even given lower priority, as a result of producing the scenarios. In this context, which scenario contains which topic (driver), or issue about the future, is irrelevant.

b) Tests for consistency

At every stage it is necessary to iterate, to check that the contents are viable and make any necessary changes to ensure that they are; here the main test is to see if the scenarios seem to be internally consistent – if they are not then the writer must loop back to earlier stages to correct the problem. Though it has been mentioned previously, it is important to stress once again that scenario building is ideally an iterative process. It usually does not just happen in one meeting – though even one attempt is better than none – but takes place over a number of meetings as the participants gradually refine their ideas.

c) Positive perspectives

Perhaps the main benefit deriving from scenarios, however, comes from the alternative ‘flavors’ of the future their different perspectives offer. It is a common experience, when the scenarios finally emerge, for the participants to be startled by the insight they offer – as to what the general shape of the future might be – at this stage it no longer is a theoretical exercise but becomes a genuine framework (or rather set of alternative frameworks) for dealing with that.

Scenario planning compared to other techniques[edit]

The flowchart to the right provides a process for classifying a phenomenon as a scenario in the intuitive logics tradition.^[33]

Scenario planning differs from contingency planning, sensitivity analysis and computer simulations.^[34]

Contingency planning is a «What if» tool, that only takes into account one uncertainty. However, scenario planning considers combinations of uncertainties in each scenario. Planners also try to select especially plausible but uncomfortable combinations of social developments.

Sensitivity analysis analyzes changes in one variable only, which is useful for simple changes, while scenario planning tries to expose policy makers to significant interactions of major variables.

While scenario planning can benefit from computer simulations, scenario planning is less formalized, and can be used to make plans for qualitative patterns that show up in a wide variety of simulated events.

During the past 5 years, computer supported Morphological Analysis has been employed as aid in scenario development by the Swedish Defence Research Agency in Stockholm.^[35] This method makes it possible to create a multi-variable morphological field which can be treated as an inference model – thus integrating scenario planning techniques with contingency analysis and sensitivity analysis.

Scenario analysis[edit]

Scenario analysis is a process of analyzing future events by considering alternative possible outcomes (sometimes called «alternative worlds»). Thus, scenario analysis, which is one of the main forms of projection, does not try to show one exact picture of the future. Instead, it presents several alternative future developments. Consequently, a scope of possible future outcomes is observable. Not only are the outcomes observable, also the development paths leading to the outcomes. In contrast to prognoses, the scenario analysis is not based on extrapolation of the past or the extension of past trends. It does not rely on historical data and does not expect past observations to remain valid in the future. Instead, it tries to consider possible developments and turning points, which may only be connected to the past. In short, several scenarios are fleshed out in a scenario analysis to show possible future outcomes. Each scenario normally combines optimistic, pessimistic, and more and less probable developments. However, all aspects of scenarios should be plausible. Although highly discussed, experience has shown that around three scenarios are most appropriate for further discussion and selection. More scenarios risks making the analysis overly complicated.^[36][37] Scenarios are often confused with other tools and approaches to planning. The flowchart to the right provides a process for classifying a phenomenon as a scenario in the intuitive logics tradition.^[38]

Principle[edit]

Scenario-building is designed to allow improved decision-making by allowing deep consideration of outcomes and their implications.

A scenario is a tool used during requirements analysis to describe a specific use of a proposed system. Scenarios capture the system, as viewed from the outside

Scenario analysis can also be used to illuminate «wild cards.» For example, analysis of the possibility of the earth being struck by a meteor suggests that whilst the probability is low, the damage inflicted is so high that the event is much more important (threatening) than the low probability (in any one year) alone would suggest. However, this possibility is usually disregarded by organizations using scenario analysis to develop a strategic plan since it has such overarching repercussions.

Combination of Delphi and scenarios[edit]

Scenario planning concerns planning based on the systematic examination of the future by picturing plausible and consistent images of that future. The Delphi method attempts to develop systematically expert opinion consensus concerning future developments and events. It is a judgmental forecasting procedure in the form of an anonymous, written, multi-stage survey process, where feedback of group opinion is provided after each round.

Numerous researchers have stressed that both approaches are best suited to be combined.^[39][40] Due to their process similarity, the two methodologies can be easily combined. The output of the different phases of the Delphi method can be used as input for the scenario method and vice versa. A combination makes a realization of the benefits of both tools possible. In practice, usually one of the two tools is considered the dominant methodology and the other one is added on at some stage.

The variant that is most often found in practice is the integration of the Delphi method into the scenario process (see e.g. Rikkonen, 2005;^[41] von der Gracht, 2008;^[42]). Authors refer to this type as Delphi-scenario (writing), expert-based scenarios, or Delphi panel derived scenarios. Von der Gracht (2010)^[43] is a scientifically valid example of this method. Since scenario planning is “information hungry”, Delphi research can deliver valuable input for the process. There are various types of information output of Delphi that can be used as input for scenario planning. Researchers can, for example, identify relevant events or developments and, based on expert opinion, assign probabilities to them. Moreover, expert comments and arguments provide deeper insights into relationships of factors that can, in turn, be integrated into scenarios afterwards. Also, Delphi helps to identify extreme opinions and dissent among the experts. Such controversial topics are particularly suited for extreme scenarios or wildcards.

In his doctoral thesis, Rikkonen (2005)^[41] examined the utilization of Delphi techniques in scenario planning and, concretely, in construction of scenarios. The author comes to the conclusion that the Delphi technique has instrumental value in providing different alternative futures and the argumentation of scenarios. It is therefore recommended to use Delphi in order to make the scenarios more profound and to create confidence in scenario planning. Further benefits lie in the simplification of the scenario writing process and the deep understanding of the interrelations between the forecast items and social factors.

Critique[edit]

While there is utility in weighting hypotheses and branching potential outcomes from them, reliance on scenario analysis without reporting some parameters of measurement accuracy (standard errors, confidence intervals of estimates, metadata, standardization and coding, weighting for non-response, error in reportage, sample design, case counts, etc.) is a poor second to traditional prediction. Especially in “complex” problems, factors and assumptions do not correlate in lockstep fashion. Once a specific sensitivity is undefined, it may call the entire study into question.

It is faulty logic to think, when arbitrating results, that a better hypothesis will render empiricism unnecessary. In this respect, scenario analysis tries to defer statistical laws (e.g., Chebyshev’s inequality Law), because the decision rules occur outside a constrained setting. Outcomes are not permitted to “just happen”; rather, they are forced to conform to arbitrary hypotheses ex post, and therefore there is no footing on which to place expected values. In truth, there are no ex ante expected values, only hypotheses, and one is left wondering about the roles of modeling and data decision. In short, comparisons of «scenarios» with outcomes are biased by not deferring to the data; this may be convenient, but it is indefensible.

“Scenario analysis” is no substitute for complete and factual exposure of survey error in economic studies. In traditional prediction, given the data used to model the problem, with a reasoned specification and technique, an analyst can state, within a certain percentage of statistical error, the likelihood of a coefficient being within a certain numerical bound. This exactitude need not come at the expense of very disaggregated statements of hypotheses. R Software, specifically the module “WhatIf,”^[44] (in the context, see also Matchit and Zelig) has been developed for causal inference, and to evaluate counterfactuals. These programs have fairly sophisticated treatments for determining model dependence, in order to state with precision how sensitive the results are to models not based on empirical evidence.

Another challenge of scenario-building is that «predictors are part of the social context about which they are trying to make a prediction and may influence that context in the process».^[45] As a consequence, societal predictions can become self-destructing.^[45] For example, a scenario in which a large percentage of a population will become HIV infected based on existing trends may cause more people to avoid risky behavior and thus reduce the HIV infection rate, invalidating the forecast (which might have remained correct if it had not been publicly known). Or, a prediction that cybersecurity will become a major issue may cause organizations to implement more secure cybersecurity measures, thus limiting the issue.

Critique of Shell’s use of scenario planning[edit]

In the 1970s, many energy companies were surprised by both environmentalism and the OPEC cartel, and thereby lost billions of dollars of revenue by mis-investment. The dramatic financial effects of these changes led at least one organization, Royal Dutch Shell, to implement scenario planning. The analysts of this company publicly estimated that this planning process made their company the largest in the world.^[46] However other observers^[who?] of Shell’s use of scenario planning have suggested that few if any significant long-term business advantages accrued to Shell from the use of scenario methodology^{[citation needed]}. Whilst the intellectual robustness of Shell’s long term scenarios was seldom in doubt their actual practical use was seen as being minimal by many senior Shell executives^{[citation needed]}. A Shell insider has commented «The scenario team were bright and their work was of a very high intellectual level. However neither the high level «Group scenarios» nor the country level scenarios produced with operating companies really made much difference when key decisions were being taken».^{[citation needed]}

The use of scenarios was audited by Arie de Geus’s team in the early 1980s and they found that the decision-making processes following the scenarios were the primary cause of the lack of strategic implementation^{[clarification needed]}), rather than the scenarios themselves. Many practitioners today spend as much time on the decision-making process as on creating the scenarios themselves.^[47]

See also[edit]

• ACEGES – an agent-based model for scenario analysis
• Counter-revolutionary
• Decentralized planning (economics)
• Disruptive innovation
• Hoshin Kanri#Hoshin planning
• Futures studies
• Global Scenario Group
• Resilience (organizational)
• Robust decision-making
• Scenario (computing)

Similar terminology[edit]

• Feedback loop
• System dynamics (also known as Stock and flow)
• System thinking

Analogous concepts[edit]

• Delphi method, including Real-time Delphi
• Game theory
• Horizon scanning
• Morphological analysis
• Rational choice theory
• Stress testing
• Twelve leverage points

Examples[edit]

• CIM-10 Bomarc (relied on Semi-Automatic Ground Environment)
• Climate change mitigation scenarios – possible futures in which global warming is reduced by deliberate actions
• Covert United States foreign regime change actions
• Dynamic Analysis and Replanning Tool
• Energy modeling – the process of building computer models of energy systems
• Floodplain
• Nijinomatsubara
• Pentagon Papers

References[edit]

Additional Bibliography[edit]

• D. Erasmus, The future of ICT in financial services: The Rabobank ICT scenarios (2008).
• M. Godet, Scenarios and Strategic Management, Butterworths (1987).
• M. Godet, From Anticipation to Action: A Handbook of Strategic Prospective. Paris: Unesco, (1993).
• Adam Kahane, Solving Tough Problems: An Open Way of Talking, Listening, and Creating New Realities (2007)
• H. Kahn, The Year 2000, Calman-Levy (1967).
• Herbert Meyer, «Real World Intelligence», Weidenfeld & Nicolson, 1987,
• National Intelligence Council (NIC) Archived 2012-07-28 at the Wayback Machine, «Mapping the Global Future», 2005,
• M. Lindgren & H. Bandhold, Scenario planning – the link between future and strategy, Palgrave Macmillan, 2003
• G. Wright& G. Cairns, Scenario thinking: practical approaches to the future, Palgrave Macmillan, 2011
• A. Schuehly, F. Becker t& F. Klein, Real Time Strategy: When Strategic Foresight Meets Artificial Intelligence, Emerald, 2020*
• A. Ruser, Sociological Quasi-Labs: The Case for Deductive Scenario Development, Current Sociology Vol63(2): 170-181, https://journals.sagepub.com/doi/pdf/10.1177/0011392114556581

Scientific Journals[edit]

• Foresight
• Futures
• Futures & Foresight Science
• Journal of Futures Studies
• Technological Forecasting and Social Change

External links[edit]

• Wikifutures wiki; Scenario page—wiki also includes several scenarios (GFDL licensed)
• ScenarioThinking.org —more than 100 scenarios developed on various global issues, on a wiki for public use
• Shell Scenarios Resources—Resources on what scenarios are, Shell’s new and old scenario’s, explorer’s guide and other scenario resources
• Learn how to use Scenario Manager in Excel to do Scenario Analysis

Further reading[edit]

• «Learning from the Future: Competitive Foresight Scenarios», Liam Fahey and Robert M. Randall, Published by John Wiley and Sons, 1997, ISBN 0-471-30352-6, Google book
• «Shirt-sleeve approach to long-range plans.», Linneman, Robert E, Kennell, John D.; Harvard Business Review; Mar/Apr77, Vol. 55 Issue 2, p141

ВикиЧтение

Исследование систем управления: конспект лекций
Шевчук Денис Александрович

МЕТОД СЦЕНАРИЕВ В СТРАТЕГИЧЕСКОМ УПРАВЛЕНИИ

© Анохина Ю.А.*

Московский государственный технический университет гражданской авиации, г. Москва

В данной статье рассматривается сущность метода сценариев и преимущества его применения при разработке стратегии компании в условиях нестабильной конъюнктуры рынка.

Цикличность развития экономики, быстрая смена и слабая предсказуемость политических, экономических и социальных условий требуют от авиакомпании адекватной реакции на неожиданные изменения во внешней среде.

Традиционные методы управления, основанные на простой экстраполяции прошлого опыта, в современных условиях оказываются неэффективными. Попытки справиться с возникшими проблемами за счет мобилизации лишь внутренних ресурсов предприятия, улучшения внутрифирменного управления не приводят к решающему успеху.

Таким образом, концепция управления компании для достижения поставленных целей в долгосрочном плане должна быть основана на возможности наиболее эффективно использовать не только имеющиеся внутренние ресурсы, но и ситуацию, возникшую в динамично развивающейся внешней среде.

Анализ и прогнозирование возможных состояний внешней среды, отслеживание возможных последствий изменений рыночной ситуации позволяет обоснованно выбирать наиболее эффективную стратегию, адаптированную к прогнозным состояниям рыночной конъюнктуры.

В рамках решения задач стратегического развития для фирмы особенно важны результаты анализа влияния внешних факторов, поскольку они мало поддаются регулированию со стороны фирмы. Единственно возможные действия в отношении этих факторов — максимальное приспособление к их возможному влиянию. Состояние, характер динамики и взаимодействия этих факторов представляют собой информационное поле, для анализа которого наиболее эффективным инструментом является сценарный подход (метод сценариев).

Метод сценариев предполагает создание технологий разработки сценариев, обеспечивающих более высокую вероятность выработки эффективного решения в тех ситуациях, когда это возможно, и более высокую вероятность сведения ожидаемых потерь к минимуму в тех ситуациях, когда потери неизбежны.

* Аспирант кафедры Менеджмента.

Разработку сценариев можно отнести к методам долго- и среднесрочного прогнозирования. Однако, рассматривая сценарный подход как метод прогнозирования, можно сказать, что, с одной стороны, сами сценарии прогнозами не являются, а с другой — сценарный подход является лишь отдельным этапом прогнозирования.

Метод сценариев можно отнести не только к области прогнозирования, но и к области стратегического планирования. Любому виду бизнеса присущи определенные азарт и риск. Уязвимость выбранной стратегии в значительной степени зависит от масштаба риска и возможности обеспечить контроль этого риска со стороны руководства. Требуется учитывать изменения, происходящие во внешней среде и внутри фирмы, в частности изменение потребительского спроса на товары и услуги, действия конкурентов и государственных органов, политическую и социальную ситуацию, конфликтные ситуации при формировании корпоративной культуры на предприятии и т.п. Их внезапное проявление может означать кризис для бизнес-системы. Здесь сценарии являются полезной отправной точкой при стратегическом планировании. Каждый руководитель при любых раскладах должен иметь свой сценарий развития предприятия, который позволил бы ему нарисовать мысленную картину будущего, оценить совокупность шансов и угроз для предприятия, наметить стратегические альтернативы его развития.

Необходимо отметить, что наличие хорошей стратегии в сочетании с успешным ходом ее реализации не гарантирует, что фирме удастся избежать спадов и неустойчивости, так как может появиться целый ряд различного рода непредвиденных и неблагоприятных обстоятельств, носящих форс-мажорный и случайных характер. С учетом этого должна быть предусмотрена стратегическая защита, позволяющая создать потенциал сопротивления кризису и обеспечение адаптации бизнес-системы для преодоления возникающих внешних и внутренних проблем.

В качестве основных параметров сценария целесообразно рассматривать состояние конъюнктуры целевого рынка, стратегический потенциал предприятия, вид выбираемой стратегии, степень риска в условиях неопределенности и неустойчивости внешней среды, а также чувствительность и устойчивость предприятия как бизнес-системы к негативным воздействиям.

Сценарий заставляет размышлять и обеспечивает:

— лучшее понимание рыночной ситуации и ее эволюции в прошлом, настоящем и будущем;

— оценку потенциальных угроз для фирмы;

— выявление благоприятных возможностей для фирмы;

— выявление возможных, наиболее целесообразных направлений деятельности фирмы;

— повышение уровня адаптированности фирмы к изменениям внешней среды.

Таким образом, метод сценариев позволяет повысить способность к предвидению и развить гибкость и адаптивность фирмы к переменам. Этот метод, который исходит из убеждения о том, что будущее никогда не может быть полностью измерено и управляемо, обладает, с точки зрения управления, рядом важных достоинств.

1. Прежде всего, он заостряет внимание фирмы на неопределенности, которая характеризует любую рыночную ситуацию: управление в турбулентной среде подразумевает способность предвидеть эволюция этой среды.

Состояние неопределенности может быть вызвано следующими обстоятельствами:

— неполнота имеющейся информации об исследуемом объекте;

— ограниченная способность исследователя переработать поступающую информацию;

— объективная неопределенность протекания процессов во времени;

— неопределенность воздействия среды на систему;

— неопределенность, связанная с процессом принятия решений.

В связи с этим, построение прогнозных сценариев преследует две основные цели в отношении неопределенности:

— максимально возможное в рамках данного подхода снижение неопределенности,

— описание не устраненной части неопределенности с помощью нескольких сценарных вариантов.

Анализ неопределенности во времени — это основной вопрос сценарных исследований. Для целей долгосрочного планирования возможна следующая структуризация временного горизонта развития систем: период инерции, выбора и неопределенности. Период инерции — промежуток времени, когда система движется в направлении сложившихся тенденций, и на нее не оказывают влияния, принимаемые в настоящий момент решения и происходящие внешние события. Период выбора — временной отрезок, где траектория развития системы складывается под влиянием принимаемых в настоящий момент решений и происходящих событий. Период неопределенности характеризуется лавинообразным ростом числа возможных вариантов развития и появления новых, непредсказуемых альтернатив.

2. Метод сценариев облегчает интеграцию данных, полученных разными методами, качественными или количественными.

3. Реализация этого метода вносит в управление дополнительную гибкость и способствует разработке альтернативных планов и системы быстрого реагирования на изменения внешней среды.

4. Кроме того, сценарии могут служить для выявления целей и стратегий компании, которые в краткосрочном плане кажутся оптимальными, а долгосрочной перспективе могут привести к неблагоприятным последствиям.

Сценарный подход может применяться к анализу системы, ее элементов, а также к анализу воздействия внешней среды на систему. Анализ среды позволяет выявить совокупность причин, определяющих функционирование и развитие системы и ее элементов. Эти причины называются факторами. Факторы не остаются всегда неизменными, их состояние, сила и направление влияния могут со временем изменяться, образуя так называемое поле сценариев. Границами поля сценариев являются:

— оптимистический сценарий, в котором все рассматриваемые факторы благоприятно сказываются на эволюции прогнозируемой системы;

— пессимистический сценарий, в котором все факторы отрицательно сказываются на изменении системы. Этот сценарий отражает наихудший вариант развития событий.

Вероятность исполнения как оптимистического, так и пессимистического варианта сценария крайне мала. Наиболее вероятным является сочетание положительных и отрицательных событий. Поэтому выделяют также наиболее вероятные сценарии, число которых может быть достаточно большим. Имеет смысл выделение как можно большего количества вариантов, которые охватывали бы весь спектр возможных направлений развития компании.

Вклад сценарного подхода в разработку стратегии заключается в том, что метод сценариев позволяет разработать разумный набор стратегий, способствующий достижению лучшего результата деятельности организации. В частности, сценарное планирование позволяет разработать стратегию организации, реализация которой приведет к удовлетворению специфических интересов организации или решению выявленной проблемы.

Оптимальным считается разработка такой стратегии, когда достигнутые результаты были бы благоприятны при любом рассматриваемом сценарии развития ситуации. Обычно каждому рассматриваемому сценарию соответствует единственная наиболее благоприятная стратегия. В данном случае необходимо выбрать такую стратегию, которая максимизировала бы выигрыш компании при любом варианте развития ситуации и обеспечивала бы минимальный уровень риска. В том случае, если вероятность реализации одного из предполагаемых сценариев намного выше вероятности реализации остальных, возможно выбрать стратегию, наиболее благоприятную для данного сценария.

В своих исследованиях М. Портер отмечает, что согласование сценариев со стратегией может быть осуществлено несколькими способами, но при этом необходимо помнить, что построение стратегии на базе только одного из сценариев достаточно рискованно. Выбор стратегии, предусматривающей все возможные сценарии развития, если и возможен, то требует значительных издержек.

По мнению Портера, существует пять основных подходов к выбору стратегии:

— придерживаться наиболее вероятного сценария развития;

— придерживаться наилучшего сценария;

— идти на компромисс;

— сохранять гибкость;

— воздействовать на исходы сценариев.

Выбор того или иного подхода индивидуален и зависит от лица, выбирающего стратегию. Считается возможным сочетание нескольких подходов. К примеру, можно придерживаться политики наиболее вероятного сценария и в то же время сохранять гибкость. Однако в любом случае необходимо осуществлять постоянный мониторинг за соответствием используемых организацией ресурсов выбранной стратегии, действиями конкурентов на рынке, а также максимально использовать конкурентные преимущества компании.

Применение метода сценариев играет особую роль при подготовке стратегии компании. Он дает возможность по-новому взглянуть на происходящее вокруг, увидеть зарождающиеся проблемы, подготовить компанию к будущим изменениям. Разработка стратегии развития бизнеса с помощью сценарного планирования заметно снижает уровень неопределенности, придает больше уверенности в правильности выбранной стратегии, позволяя снизить риски масштабных инвестиций, улучшить качество принимаемых стратегических решений.

Список литературы:

1. Артамонов Б.В. Методологические аспекты формирования стратегии предприятия // Научный вестник МГТУ ГА. — 2008. — № 131. — С. 31-36.

2. Бандурин А.В., Чуб Б.А., Процесс планирования стратегии [Электронный ресурс]. — Режим доступа: www.eduhmao.rU/info/1/4340/35034.

3. Лаева Т.В. Сценарный анализ как основа стратегического планирования в организации // Менеджмент в России и за рубежом. — 2006. — № 2.

ОСОБЕННОСТИ ФОРМИРОВАНИЯ РЫНКА СЕЛЬСКОХОЗЯЙСТВЕННОЙ ПРОДУКЦИИ НА ТЕРРИТОРИИ ЦЕНТРАЛЬНО-ЧЕРНОЗЕМНОГО

РЕГИОНА

© Бакуменко Л.С.*

Тамбовский государственный университет им. Г.Р. Державина, г. Тамбов

Аграрный сектор российского рынка сельскохозяйственных товаров и услуг экономики страны в целом — динамично развивающаяся, мощ-

* Аспирант.