4 Ways to Get Buy-in for Better Data Management

In today’s digital business world, data is at the center of operations and decision making. In fact, recent data shows that 80 percent of organizations believe data is essential to forming their business strategy. The challenge we see at Experian is that while data is widely used, it is not trusted.

Less than half of businesses trust their data to help them make key decisions, according to the 2017 Global Data Management Benchmark Report from Experian Data Quality. That means that organizations rely on educated guesses or gut reactions to determine the direction of their business. This is to say nothing about what bad data does to operational efficiency or the customer experience.

And those educated guesses are coming with good reason. Global businesses believe, on average, 27 percent of their data is inaccurate in some way. However, our study also revealed that C-level executives have a higher degree of distrust in their data than those in other roles. On average, they believe 33 percent of their data is inaccurate, which can undermine their ability to make strategic decisions.

To increase the level of trust around data, businesses need to invest in their data management programs. Stakeholders need to feel that the people, processes, and technology are yielding data that can be fit-for-purpose and will give them the accurate insights they need.

If senior management believes the level of data accuracy is so low, one would think it would be willing to make an investment. But that is often not the case. Although leaders conceptually understand the value of good data, there is often very little metrics-based evidence to show the true benefit of making long-term investments in data management. Therefore, they often see bad data as a cost of doing business rather than an indication their data management is in need of significant improvement.

To get buy-in for data management improvements, stakeholders need to demonstrate the benefits of making changes and define how they will impact the business, not just the level of data accuracy. Here are four ways to help you get that leadership buy-in.

1. Generate quantifiable metrics. A successful business case for data quality should have quantifiable metrics. These should directly relate to the business and be separate from emotional feelings about data. There are several key areas to consider. The first is time. You can typically link data quality issues to wasted time for your customers or your employees. Then, think about the manual impact and resources it takes to correct data that is not accurate, not to mention the drain on staff. Next is cost. There is typically a cost associated with bad data that directly relates to the bottom line. It could be from an inability to communicate or a bad customer experience. All of those will have a cost that impacts the bottom line. Finally, think about efficiency. How is bad data making your business processes inefficient or, quite frankly, unachievable?

2. Represent the needs of the business. We typically see that the individuals involved in building a business case are in IT-related roles. While there is nothing wrong with that, the business case they make often under-represents the full needs of the business; their case inevitably needs to be sharpened by business stakeholders. To get it right from the outset, leverage stakeholders from all areas of the business and make the project a cross-departmental effort. The more expertise involved, and the bigger the benefit that can be demonstrated, the more likely the project will secure funding.

3. Tell a story. When talking about data, we often get bogged down in details about the level of accuracy or metrics around the completeness of the data. While those can be interesting to a more technical audience, they are often not relatable and compelling to someone within the business that is approving a business case. When framing the tangible impacts of your data quality business case, consider your audience and tailor the story to meet their needs. Consider showing metrics around why data impacts the finance department’s ability to collect invoices, or your marketing team’s ability to reach their most valuable customers. Tie your program to broader objectives like operational performance, financial performance, regulatory compliance, and the customer experience.

4. Set specific time frames, and keep them short. We often see clients that take significantly long periods of time between having a proposal for a data improvement and actually implementing the change. To get buy-in, you want to set a timeline for success that has clear metrics and deliverables. While you want to be realistic in your time frame, you also want to keep it as short as possible. Management will not want to wait nine months or a year to see change. They will want to see it quickly. Push yourselves and the vendors you work with to get tooling implemented quickly and delivering value.

Today, most of us like to think of our businesses as innovative and data-driven. But most companies lack the level of data management sophistication required to have trusted information that can make a positive impact. We need to make long-term investments in our data to see a business impact, but that takes buy-in from the highest levels. To get that buy-in, we need to stop thinking about our data in terms of accuracy and completeness, but rather think about its impact on the organization and its objectives.

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As general manager of Experian Data Quality North America, Thomas Schutz serves as the company's top executive for all strategic business decisions in the United States and Canada. Schutz is focused on helping organizations proactively manage the quality of their data through world-class validation, matching, enrichment, and profiling capabilities to better enable intelligent customer interactions and decision making.