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The Data Culture Balancing Act

February 5th, 2015 | Posted by Joel Read in Financial Services

McKinsey & Company recently posted an excellent article, “Getting big impact from big data,” and addressed a proverbial elephant in the room: while most executives believe big data analytics is a critical tool for success, fewer companies have been able to successfully use analytics to drive major business decisions.

So what is preventing organizations from unlocking the value of their data? According to McKinsey a major barrier has been internal organizational cultures that are not familiar with analytical practices and therefore unwilling to take ownership of a new system with unproven results. This keeps organizations from being able to operate data driven initiatives at scale. So while software solutions can help, there is also a significant cultural challenge that needs to be overcome for organizations to realize the full value of big data.

At APT, we believe that a successful analytics function balances two elements: the need for democratized, self-serve solutions to answer more common analytical questions, and the power of a centralized capability focused on strategic, high-impact initiatives. Both approaches to analytics are critical to nurturing a data-driven culture, but equally important is the need for a common language to share both self-serve and strategic initiatives internally. This language includes using common analytical methodologies and common software across the organization, reinforced with regular training on analysis and communicating results (see Exhibit 1).

Exhibit 1 – The Data Culture Balancing Act

 

data culture blog graphic

 

Accomplishing this balance allows data to be used more frequently across the organization, and shifts internal discussions from debating about methodology to leveraging actionable insights. For example, many of our clients have established a testing “Center of Excellence” within their finance department—a streamlined group of analysts who focus on leading analysis of major strategic initiatives across the organization. The team receives requests from a variety of functional areas (marketing, merchandising, operations, digital, etc.) and meets regularly to manage and prioritize major analysis requests. Additionally, analysts within each individual functional area have access to relevant data sets and analysis tools that help them analyze smaller, day-to-day analytical questions. Regardless of the analysis scope, every team uses the same software and a standard structure for communicating results. This structure has allowed APT’s clients to efficiently analyze hundreds of initiatives per year and rapidly innovate to improve both their sales and cost effectiveness.

Institutionalizing a robust data-driven decision making process is no easy task. The need for simplified self-serve tools for basic analysis, as well as a centralized group accountable for larger initiatives, is difficult for any company to balance, especially while ensuring everyone is speaking the same analytics language. That said, we have seen that the organizations which achieve this model can drive a cultural change towards data-driven decisions and rapidly increase confidence and accuracy behind each business action.

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