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.
Paul Leonardi is the Duca Family Professor of Technology Management at UC Santa Barbara. He holds appointments in the Technology Management Program (TMP) and the Department of Communication. He is also the Investment Group of Santa Barbara Founding Director of the Master of Technology Management Program.
Dr. Leonardi’s research, teaching, and consulting focus on helping companies to create and share knowledge more effectively. He is interested in how implementing new technologies and harnessing the power of informal social networks can help companies take advantage of their knowledge assets to create innovative products and services.
He has authored dozens of articles that have appeared in top journals across the fields of management, organization studies, communication studies, and information systems research. He is also the author of three books on innovation and organizational change. He has won major awards for his research from the Academy of Management, the American Sociological Association, the Alfred P. Sloan Foundation, the Association for Information Systems, the International Communication Association, the National Communication Association, and the National Science Foundation.
Over the past decade, he has consulted with for-profit and non-profit organizations about how to improve communication between departments, how to use social technologies to improve internal knowledge sharing, how to structure global product development operations, and how to manage the human aspects of new technology implementation.
Before coming to UCSB, Dr. Leonardi worked at Northwestern University on the faculties of the School of Communication, the McCormick School of Engineering, and the Kellogg School of Management. He received his Ph.D. in Management Science and Engineering from the Center for Work, Technology, and Organization at Stanford University.
Willem Buhrmann is an experienced mining professional that has extensive African and international experience in project management, strategy implementation and corporate finance. Willem was previously Business Development Manager (Africa) for Rio Tinto Energy and more recently consulted to the wider mining industry including majors and a variety of juniors. He holds degrees in finance (Chartered Accountant) and the legal world (LL.B.)