You might remember that strategy’s roots are military and on the battlefield you could count on a few constants:
- The past was a good predictor of the future.
- Good data was scarce and hard to get & rely upon.
The primary purpose of strategic planning is to devise a synchronized strategy by ensuring that the key decision makers have a solid understanding of the business, share a common fact base, and agree on important assumptions. Thus, we lay our strategic plan on a set of strategic assumptions. How do we make assumptions? We make assumptions by using conventional wisdom, measuring new market potential using surveys/expert opinions, identifying and analyzing current market trends, predicting the future using data analytics, etc. Most of these assumptions are either based on facts (competitor's performance in the last quarter) or statistics (35% potential customers do not have a bank account in New Jersey).
Based on a statistical survey, management at a large bank attributed fast growth and share gains to superior customer perceptions and satisfaction. Examining the bank’s markets at a more granular level suggested that 90% (fact) of its performance could be attributed to a relatively high exposure to one fast-growing city and to its presence in a fast-growing product segment. This insight helped the bank avoid building its strategy on false assumptions about what was and was not working for the operation as a whole.
Generally, at the end of many statistic-based statements you find a disclaimer '*' which says that "The study was conducted on 2000 residents of ABC area in XYZ city" or something similar. If this statistic works in the favor of an executive he/she uses it to gain maximum advantage wherever possible but the other more-aware executives would point to the disclaimer '*' to question his/her assumption. The problem is, most of them do not even know that there exists a '*' and would just consume this statement as a fact and reproduce it in front of their seniors as basis of their assumptions. There you go.
In today's world of uncertainty, we need to make assumptions, and statistics definitely play a key role. But, the question is should we rely on statistics? If yes, how much and when?