Big Data and the Risk of Paralysis by Analysis: A CIO Perspective

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Over 70% of enterprises view advanced analytics as a vital strategic priority, but slightly less than 10% believe they’re achieving the potential strategic value of analytics. According to a recent quantitative NewtonX survey with 75 American Fortune 1000 CIOs, the biggest value realization gap comes from the “last mile” — or the final step in the supply chain before reaching the consumer. To address the gap between great analytical output and data-driven behavioral changes NewtonX conducted follow-up interviews with ten of the 50 executives surveyed, five of whom reported that they had successfully used analytics to drive behavior changes, and five of whom reported that they had access to great analytics, but couldn’t bridge the last mile gap.

These in-depth qualitative consultations, in addition to the quantitative survey yielded the following insights:

  • Analytics strategies tend to be designed without consideration of implementation at the last mile
  • There’s a gap between last mile teams and analytics teams in terms of drivers and motivations
  • A major difference between the two groups interviewed was a lack of training programs for the executives who struggled to drive data-driven behavior.

Companies tend to invest in new technology, such as big data analytics tools, without investing in the necessary organizational changes they will need to make to fully reap the benefits.  

The insights from this article are sourced from NewtonX surveys, panels, and expert consultations. To gain access to these services visit newtonx.com.

How to Turn Great Analytics Into Great Enterprise Value

The key to properly implementing innovative analytics programs is bridging gaps between different teams, and between the company and the customer. At its core, this is a problem of communication. Based on the interviews with executives who are successfully using data and analytics to drive behavior change, these are the top three most effective ways to bridge the gap.

1. Design Analytics With the Last-Mile Teams/Consumers in Mind

Having a great data-driven idea often isn’t enough to make other teams or consumers adopt the idea. The best guiding light for ensuring that the last mile team and consumers don’t reject analytics initiatives is to keep the end user as the guiding motivation for any organizational or structural change. For instance, while AI-powered systems and unstructured data may be useful for the analytics team, they’re not always intuitive for frontline employees who are under tight time constraints.

When designing an analytics program, think about how to make it user friendly for last mile employees and consumers. For instance, Disney dressed up its customer-tracking “MagicBands” to make them Instagram-worthy symbols of taking a Disney vacation. This promoted consumer adoption considerably, and helped the company gain valuable analytical insight into customer behavior.

2. Design Processes That Provide Incentives for Adoption

Front line employees are often under tight time constraints and have to deal with rapidly changing customer needs and individual complaints. Because of this, analytics-driven programs will often fail at this last touchpoint, as employees feel too busy and overwhelmed to adopt a new process.

Of the five executives NewtonX consulted who had successfully implemented data-driven behavior change, four indicated they had robust incentive programs for all employees to adopt new processes. These ranged from negative reinforcement for not following a new policy, to bonus incentives (if all frontline retailers in a store adhere to a new policy, that store wins a prize, for example), to team outings or recognition prizes.

3. Explain Motives and Accelerate Adoption

The last mile gap is a particularly significant problem in retail organizations, where merchants tend to override sophisticated forecasting and store assortment algorithms based on mitigating factors. This happens for a few reasons, many of which are attributable to the analytics team not following the above two suggestions. But an additional reason this can occur is because the last mile employees do not understand or buy into the motivation for changing their processes.

It’s important to outline the motives and proposed outcomes for any new process, particularly one that is customer-facing. This is a critical way to get every member of the organization on board and adherent to a new policy.  

Drive Great Analytics By Laying the Groundwork for Great Behavior

Big data and analytics programs don’t exist in a vacuum. They need to include incentive and training programs, and also be user friendly from a presentation standpoint. Before any new strategy can be adopted across an organization, and especially in the last mile, all of these factors must be considered and executed well.

 

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About Author

Germain Chastel is the CEO and Founder of NewtonX.

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