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(originally published by Booz & Company)


Who Should Own Big Data?

The matrix approach does have its challenges. Although it solves the problem of how to balance the concerns of both the business and IT, the matrix approach requires a high degree of organizational focus and a commitment to developing new data capabilities at the highest levels in the organization. These include IT capabilities such as the design, development, and support of centralized data hubs, and the ability to identify and integrate external sources of data. Business-side capabilities include the ability to set clear priorities for what data will be gathered and how it will be analyzed and used, and a strong governance mechanism for determining who sets those priorities under various circumstances.

As advantageous as the matrix model can be, it often comes with a higher price tag. Justifying the incremental cost and added organizational complexity is relatively straightforward for companies in industries such as healthcare and financial services, which have historically depended on information as a competitive asset. Manufacturing companies, on the other hand, may find a matrix organization more difficult to justify initially. However, many are already making greater use of data in such areas as supply chain management, and they too will find benefits in the matrix model.

No matter the industry, the matrix data organization demands a senior leader who understands the business and has a clear line of sight into C-suite priorities. He or she must have considerable authority to make key decisions about investment priorities regarding both IT and business resources, a high degree of respect among both business and IT stakeholders, and the ability to balance short-term business needs with longer-term goals for building out the necessary data capabilities.

Defining the Path

Arriving at the proper cross-functional, collaborative model for taking the most advantage of all the data at one’s disposal isn’t easy (see “More Than One Right Model). Companies will be starting off at different points along the path, with different organizational structures and levels of maturity, and varying sets of capabilities. We offer the following questions as a way for companies to consider the current state of their data efforts and to help them set the right path to follow to achieve full maturity.

  • How fundamental is data to your company’s industry and business model? Companies that use data primarily as an afterthought to evaluate performance and accounting may not feel a pressing need to develop their data capabilities or redefine organizational structures, compared with those in industries where having strong analytics is a requirement for survival.
  • Where and how dominant is the current “center of data analytics mass” at your company? Companies whose data operations are already tightly controlled by either IT or a specific business unit or function may find it especially difficult to move to a matrix model, given organizational politics and the level of resources one group will likely have already invested.
  • How willing is the company to invest in additional data capabilities? Companies that are not satisfied with their current analytics processes and organization must look closely at where the gaps are, and what it will take to fill them—whether by building new internal capabilities and structures, through new partnerships, or via some combination of the two.
  • Do you have a plan? A truly balanced matrix model requires a considerable degree of thought in working out the details of organization and governance. The planning stage is critical, and it must include every group with a stake in how best to collect and use data.

How each company answers these questions will help determine its current condition with respect to data, its commitment to boosting the necessary capabilities, and the proper path to a truly differentiating data organization (see “What’s Your Level of Data Maturity?).

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