Humans have always wanted to know the future, whether it be the immediate future or millennials in advance. Whole disciplines, formal and semi-formal, have been developed in a quest to tell the future.
Businesses, as a matter of strategic imperative, need to forecast the future, to understand the various variables that impact or will impact their businesses, how these variables are likely to change in the future and their likely impact on one another, the business environment in which they operate and ultimately their businesses. The importance of this to businesses is, “…[not just] to predict what will in fact happen in the future. Its purpose [is also] to illuminate the road, to point out obstacles and potential pitfalls and so assist management to tailor events and to bend them in a desired direction. Forecasting should be used as a device to put both problems and opportunities into perspective,” according to Peter Cundill, a Canadian businessman.
Business and economic forecasting are the types that our Data Analytics course at Lagos Business School’s Executive MBA is interested in and teaches. But how does one tell the future?
Innovators, echoing Abraham Lincoln, believe that “the best way to predict your future is to create it.” This way, the forecaster is bringing into being what was not there and ensuring the future they envision materializes. On the other hand, economists and statisticians alike, subscribe to the philosophy of Anthony T. Hincks, a Welsh musicologist, editor and writer, who believes that, “to read your future, you need to understand your past.”
Indeed, both points of view are valid. If one envisions a future radically different from the past or believes that something which currently does not exist will be useful in the future, it makes sense to invent it and play a part in shaping the envisioned future. Alternatively, in a steady, incremental world, where it is reasonable to expect the future to look a lot like the past, it makes sense to try to see the future through the lens of the past. Either way, as Ian Wilson, former General Electric Chairman noted, “no amount of sophistication is going to allay the fact that all of your knowledge is about the past and all your decisions are about the future.”
Data Analytics did not just focus on predictions, but also understanding the attributes of data sets, analyzing data, understanding and modelling relationships between variables, clarifying when it makes sense to project using available data and of course, the all-important interpretation of data and output and how analysts can use the output to forecast future outcomes.
Analysts like me however, need to be conscious of that fact that the world is increasingly complex and interconnected, with significant implications for forecasting. As Andrew McAfee, a principal research scientist at MIT noted, “our world is increasingly complex, often chaotic, and always fast-flowing. This makes forecasting something between tremendously difficult and actually impossible, with a strong shift toward the latter as timescales get longer.” And so, we were thought to incorporate scenario analysis and recognize standard deviation in our analysis.
In the final analysis, the aim is to be better prepared and positioned for the most likely range of outcomes in the future as the precise outcome cannot be determined in advance. As Howard Marks, co-founder at Oaktree Capital, succinctly explained, “there are no facts about the future, just opinions.”
Kingdom Investment