Scenarios are one of the most powerful tools available for the development of any strategic plan. With the wide adoption of the Elastic Cloud, the rise of Intelligent Indexing, and Machine Learning Systems and Artificial Intelligence (AI), scenario planning is entering into a new age of vastly improved flexibility and utility. Scenario concepts that enable companies to steer a course between the false certainties of a single forecast developed with lag data, and the confused paralysis that strikes when things don’t go as planned, for reasons nobody thought about – or measured.
In my work with organizations around strategic planning and scenario planning I’m often surprised about the lack of understanding regarding the difference between lag indicators and lead indicators and the role each should play in the development of strategy. I find more often than not that strategies are compromised by not using both lag and lead indicators in a balanced approach to get the right initiatives deployed to ensure the right outcomes. Most financial indicators such as revenue, profit, and costs are “lag indicators”. They are consequences of the activities of the company.
Lag indicators are typically “output” oriented, easy to measure but hard to use to improve or influence action. Lead indicators are “input” measures that indicate more about the actual performance that relate to processes. They may be hard to measure but are easy to influence. The primary drawback of strategic plans is that they generally use lag measures – either the planned outcome happens or not. When scenarios are used to predict future outcomes in a world that is increasingly interconnected and changing at an escalating velocity, lag measures don’t work. With new business models and disruptive technologies in the “connected world” are creating new opportunities and threatening established businesses at a faster rate than ever and lag measures are no longer sufficient to keep pace.
But now, recent developments in Big Data, Intelligent Indexing, Machine Learning, and Real-Time Analytics are being used to create new scenario planning applications that offer unprecedented integration, scale and real time, always updated, data availability for tremendous innovation optimizing operations or innovating new business models. These “digital scenarios” create new disruptive opportunities that will adapt and learn to provide users with robust, dynamic, narrative form for conveying data pattern and association analyses.
We are now collaborating with data scientists to develop scenarios that effectively model futures by endlessly iterating our scenarios based on real time, global data – basically anything reported are indexed and incorporated into the scenario planning software in real time. This will allow our users to use scenario-planning apps that constantly update lead measures and refine scenario models accordingly. The drive to use the new data capabilities to better manage and communicate organizations’ strategic response to future uncertainties will substantially increase the utility and management value of strategic planning.