The idea that data and analytics should be a component of your strategy has become part of business orthodoxy. That should come as no surprise considering how common data and analytics are in both our personal and professional life.
There is no shortage of instances of companies supporting their strategies with data and analysis. One example is Google’s plan to base the cost of ads on an analytical feedback loop.
However, what if you could directly determine your approach through data and analytics?
In an era where analytics is rapidly expanding the ability to explore scenarios, too many executives rely too heavily on their expertise and business intuition when making crucial decisions that could directly impact the organization’s strategy or even its future.
Leaders appear to recognize that when it comes to key decision-making, something is lacking. Primary research with 400 senior leaders undertaken by my firm, L.E.K. Consulting, revealed an average success rate of less than 50% when making the most important decisions. Despite having a wealth of data and clear decision-making processes in place, many businesses fail to make efficient use of their knowledge.
When strategy is driven by data, it usually leads to improved execution and clarity. Of course, there are examples of success when the strategy was developed with significant data involvement rather than merely being vetted and validated.
Hewlett Packard’s Strategic Split: Under then-CEO Meg Whitman, the decision to divide HP into HP Inc. and Hewlett Packard Enterprise was based on a clear understanding of the company’s extensive activities and the need for agility to remain competitive in a fast changing technology world. This decision, backed up by rigorous analysis and forecasting across a variety of scenarios, exemplifies how data-driven, decisive leadership can turn around a faltering corporation. The success of this strategic choice, which resulted in a considerable comeback for HP, demonstrates the value of leadership bravery and vision, backed up by strong facts.
Spotify’s Subscription Model choice: After conducting extensive research on user behavior and market developments, Spotify made the strategic choice to transition to a subscription-based streaming model. This move not only capitalized on consumers’ rising desire for streaming access over ownership, but it also transformed the music industry by proving the ability of data to force fundamental shifts in business models and industry standards.
Starbucks’ Location Strategy: Starbucks uses advanced analytics and geographic information systems to determine the best sites for new stores. This data-driven approach takes into account local demographics, traffic patterns, and current store performance to ensure that each new location is well-positioned for success. Starbucks’ rigorous use of data to inform expansion decisions highlights the importance of analytics in boosting operational success and market positioning.
Data-driven decisions perform better
This strategy is endorsed by leaders who use it. Our study shows that adopting this strategy gives firms a big edge, especially when making important or transformative decisions. The largest proportion of leaders—31 percent—had a data-rational style, surpassing all other approaches, among the organizations that thought they were the best in class at making important decisions. In comparison, only 18% supported a strategy based on consensus.
Navigating Barriers to Data-Driven Decisions
Given the obvious benefits of data-rational decision-making, why isn’t this approach more popular? Why don’t more leaders use this approach when the stakes are at their highest?
One major obstacle is the burdensome approval processes; some executives believe that if they introduce too much data, it would lead to more questioning. But as far as the executives we spoke with are concerned, decision overload is a bigger obstacle to making good decisions. More than half (54%) said they spend too much time making tactical judgments, which leaves them unable to use enough data and scenario analysis, even for the most important choices where survival or strategy are at risk.
External variables, macroeconomic issues, and the global pace of change likely to exacerbate the situation—65% of leaders indicated that increased uncertainty has made effective decision-making more difficult.
Two steps Towards Better Decision-Making
To overcome these barriers, consider two important steps:
Invest In Analytic Systems And personnel: Over the next three years, three out of five leaders intend to improve their decision-making abilities by investing in analytics and data science personnel. Strategic investments such as these are critical for establishing a solid foundation for data-driven decision-making.
Prioritize Versatility: While data-driven decision-making should be the default, flexibility in decision approaches is still required. It is not about choose between data-rational and other approaches, but about knowing how and when to combine them.
For example, ethically delicate judgments may benefit from a consensus-driven strategy that considers multiple viewpoints. The end result will be a more extensive set of insights. Versatility complements rather than competes with a data-driven foundation, allowing leaders to tailor their decision-making approach to the characteristics of the scenario.
A cultural shift
Most businesses should make data-driven decisions by default, especially when they reach key stages in their life cycles. This necessitates a purposeful change in culture and approach. By investing in analytics skills, cultivating a culture that values data-driven insights, and embracing adaptability, your organization will be better positioned to manage the challenges of the current business world. As the pace of change quickens, the ability to adapt, guided by good facts and flexible decision-making approaches, will distinguish effective leaders and assure on-time decisions in an increasingly unpredictable world.
