Balancing Business with Data Governance

Often, the organizational impact of a data governance implementation is underestimated. This can result in a high-risk project and friction between departments. Especially for the business, the implementation of data governance can be challenging, even though it determines much of its success.

Data governance will bring change, and people have a natural tendency to resist change. Embedding data governance in your organization comes with new processes, practices, roles, policies, standards and metrics that will impact each department differently. Especially within a large organization, there will be new dependencies and possibly even power struggles between departments. Essentially, data governance reveals a deeper need for change management. Meanwhile, your Marketing and Sales departments may wonder when this “navel-gazing” is finally done and when they can enter the markets with quality data to improve the customer experience and online revenues.

So, how do you align the customer-facing business with the enabling organization?

Cultivating a Culture of Data

The biggest challenge of a data governance process is convincing people to work differently. There must be a real benefit to switching, but for some departments – those who have to do more work – this is not so clear-cut. It helps to get management support and to have a corporate vision. One that explains why the organization is implementing data governance and how everyone should do their part. But the best approach is to set a separate horizon for each department.

Start with mapping separate data processes. How are things working? What are the pain points? Often, sending Excel spreadsheets back and forth is still the standard, particularly in multinationals or companies that have gone through mergers and acquisitions. Determine where you can make the biggest impact with data governance and decide which steps need to happen before you can reap the benefits.

Let the Business Set Priorities

For some departments, there will be a mountain of work that has to be done. Generally, this concerns product data, which can exist of hundreds of thousands or even millions of data records. Who would want to start improving data quality for these numbers? This is where you need a business approach to make smart decisions. A good practice is segmenting your product data by the way you will use it in the market, for example:

  • A: Popular products that are always in demand and that customers expect.
  • B: Products that offer you a good margin, or popular products with seasonal demand.
  • C: Products that make up the long tail and that are not commonly sold.

For each segment, you can also apply different levels of product quality. For example, segment A should be as complete as possible and segment C only has to be presentable enough. To do this efficiently, it helps to use data quality dashboards that visually show the quality status, the product margin and the tasks required to raise the bar. This way, you can put the focus there where the business needs it.

Benefits Versus Efforts

For departments that are closer to the market, such as Marketing, Sales, Fulfillment, Distribution and Support, the need for quality data is unmistakable. At this side of the organization, data governance is happily welcomed because higher data quality makes their work easier and better. The heavy lifting, on the other hand, is typically done by enabling departments like Sourcing, R&D, Supply Chain, Product Management and Inventory Management. Even with the work chopped up in sizable chunks and done according to the priorities set by the business, there may still be irritation between departments.

This may sound like: What is taking them so long? Don’t they know we need to sell these products next month? From the Sales department. To: Why do they want these products? We only sell five per year at best! From Product Management. The big issue often in these cases is a lack of awareness and communication. The challenge is to identify and communicate specific data needs for the business, and to make it clear what these needs mean for the supporting departments. The best way for this exchange is by setting up a multidisciplinary data team.

Setting the Common Goal

The crux of finding a balance between data governance and the business is realizing that each department has a different relationship with data. The only way forward is to put people from the different departments together to determine common goals to work on together. This calls for the understanding of the expectations and needs of each department and a business focus on the customer. Above all, it should be clear for everyone that it’s always business first. Without happy customers, the organization risks losing its relevance quickly.

Working in a multidisciplinary team also brings clarity to the challenges for the customer-facing departments. Marketers have the challenge of managing a growing number of digital channels and marketing tools, such as content marketing and automation, affiliate marketing, e-commerce, social media marketing and email marketing. A lot is happening, and data is a big part of it. The Sales department needs to prove its worth more than ever and score in every customer contact as a growing part of the customer interaction is online. And Customer Support is facing a growing customer expectation: customers want to be helped immediately 24/7. To meet these expectations, there needs to be up to date high-quality product information, manuals, guides, how-tos and FAQs that are searchable, tagged, readable online and available for download. These challenges are business challenges that call upon the whole organization.

This is the fifth blog of our article series on Data Governance. Click here for the next article.

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