Most organizations are capturing large amounts of data from their customers and prospects; however, they have not yet evolved their digital analytics practices to make decisions based on the data. In their 2012 feature on big data, Andrew McAfee and Erik Brynjolfsson describe the opportunity and report that “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors” even after accounting for several confounding factors.
Digital analytics is a lot like a self-driving car. You can customer behavioral data and models to steer your business.
You Do Not Drive Forward While Looking in the Rear View Mirror
Driving while looking in the rear-view mirror is fine if you need to go backwards! Yet most organizations only look at historical data. You will be far more effective if you analyze data from what lies ahead. This means developing predictive models that help you navigate you business along the best path.
A Self-Driving Car Synthesizes Multiple Sources in the Central Computer
A self driving car synthesizes data from multiple sources and centralizes into a single decision engine.
Digital Analytics Should Use Data and Models That Optimize Decision-Making
Like a self driving car, your business is most successful when you leverage data from multiple sources. This shouldn’t come as a surprise – companies must be able to identify, combine, and manage multiple sources of data. Data and algorithms have a tendency to outperform human intuition in a wide variety of circumstances.
A clear vision of the desired business impact must shape the integrated approach to data sourcing, model building, and decision-making. That helps you avoid the common trap of starting by asking what the data can do for you. Leaders should invest sufficient time and energy in developing this system in support of the mission.