3 Things Are Holding Back Your Analytics, and Technology Isn’t One of Them

Many firms continue to struggle with business analytics. This has nothing to do with technology. We’ve found three main obstacles to realizing analytics’ full value: the organization’s structure, culture and approach to problem solving. Structurally, analytics departments can range between two opposite but equally challenging extremes. On the one hand are data science groups that are too independent of the business. These tend to produce impressive and complex models that prove few actionable insights. On the other hand, analysts who are too deeply embedded in business functions tend to be biased toward the status quo or leadership’s thinking. Culturally, organizations that are too data-driven (yes, they exist) will blindly follow the implications of flawed models even if they defy common sense or run counter to business goals. Alternatively, organizations that rely too heavily on gut instinct resist adjusting their assumptions even when the data clearly indicates that those assumptions are wrong. The dichotomy continues when it comes to methodology. At one extreme, we see analytics groups that create overly complex models with long lead times and limited adaptability to changing inputs. On the other side of the coin, some teams create models that are too simplistic and fail to capture the nuances of the problems they’re trying to solve.