Why the C-suite Should Invest in the Competitive Advantage of Quality Data
While data professionals do a lot of the work, that doesn’t negate the need for the C-suite to be involved.
While the world has become dependent on data, it’s not always a priority for the C-suite – but it should be. If executives commit to data literacy and data quality, they will be well-positioned to accomplish or exceed company goals.
The world runs on data. Even though most leaders would concur, it is often seen as someone else’s responsibility. An HFS Research poll conducted in April 2021 found that 90% of the C-suite feel data is vital to success, but only 5% have all the data they require. Knowing what they need and having it – as well as knowing who is responsible for getting it– aren’t the same thing for most executives.
Though it’s true that data professionals – your IT teams, data scientists and data stewards – do a lot of the work, that doesn’t negate the need for the C-suite to be involved. Let me explain why.
All Roads Lead to Data
Let’s start with the fact that an utterly unmanageable amount of data is generated daily. It is estimated that 463 exabytes of data will be created each day globally in just three years. For some perspective, one exabyte is the same as one billion gigabytes (equivalent to the amount of branded trade show flash drives I have collected over the years). Given this and the speed by which decisions need to be made, it’s no surprise that folks feel like they’re barely staying afloat when it comes to managing their data, let alone harnessing its power. This can mean they’re either moving too quickly or they lack the time to acquire the tools and knowledge needed to find and use the quality data that’s actually helpful to their business.
I firmly believe that every business issue can be traced back to a data issue. Got a problem with your inventory? That’s a data problem. Problems with working capital? You can link that to data, too. Each of these difficulties is frequently linked to erroneous customer or product data, which often indicates issues with how you collect, process and govern data.
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The Foundation of Business Success
The quality of your data is critical if you’re trying to leverage new tech and initiatives – and today, who isn’t looking for that extra leg up on the competition? Data sharing, sustainability programs, advanced AI and machine learning, and a slew of other activities all begin by having and accessing trusted, understood data.
Similarly, not having clean, quality data can hamper many daily processes, resulting in lost money and time. And no C-suite executive can afford that.
But here’s the thing – quality data is necessary, but not all your data will be quality to you. It’s unrealistic to expect all that data to be relevant or valuable to you; there’s simply too much of it. You can’t possibly have the same standard for all your data – there’s just too much of it, and not all of it is going to be helpful.
One piece of advice I always give: start with prioritization. Think about your intended business outcomes and company objectives – things like how many deals you want to close or the number of customers you want to land in a certain vertical. What major metrics do you use to assess the health and success of your company? Think of this as the starting point of your data quality strategy: what data do I need to support this business goal? Find the data that supports those.
Starting with prioritization will help you get a handle on what’s important and what you can put aside. Once you’ve prioritized your business-critical data, this will help you figure out where to drill into to make sure that data is trusted, understood and available for you to make decisions with it.
The Strategic Advantage of Quality Data
There are the standard things we know that can drive advantage – things like creating more personalized experiences for customers, better marketing and sales targeting, product improvements and faster enhancements. However, one thing often overlooked is the role of data in mergers, acquisitions and divestitures (M&D) to create an advantage.
This activity represents one of the major tools in the CEO toolkit for increasing your company’s enterprise value. And challenges with data integration are the primary reason MA&D transactions aren’t finished on time – and why the acquiring company doesn’t always see the full advantages of acquisition. Different firms may – and frequently do – gather, store and govern data in different ways; they may have varying procedures and standards; they may not scrutinize the data’s quality as closely, and they may be employing different solutions.
Duplicate records can be incredibly harmful both to your reputation and your bottom line, whether it’s wasted costs and poor customer experience by marketing to the same person multiple times, lack of confidence in personalization efforts, negative customer service interactions, and inaccurate reporting. And let’s not forget the missed sales opportunities – with a merger or acquisition, you want to upsell or cross-sell relevant products to this new, larger group of customers. But if the naming isn’t consistent, how do you know if there’s overlap in customers? And how about the product codes? This quickly becomes very, very messy.
Although it may be difficult to believe, data integration can and does significantly slow down large MA&D transactions. That’s why data should be treated like any other asset. If you’re the CEO of a company that’s buying another, you should consider the quality of the data you’re getting and how it’ll be integrated and used much earlier in the acquisition process – you could begin by doing some table-top exercises during the due-diligence period. We find ourselves with duplicate data records. How do we prepare for this?
Whether it’s source mapping, data deduplication or load validation concerns, the more complicated the purchasing and selling companies are, the more complex the data migration will be. It’s also important to consider the legal constraints of M&A data transfer — these issues can be significant, and any data errors can have far-reaching ramifications.
That’s why the chief financial officer (CFO) should be a key participant in the data quality process. More than any other leader, the CFO is aware of the financial ramifications of data. His information is crucial because if you think cleansing data is costly, wait until you discover how much poor data may cost you. I once had a CFO who shall remain nameless tell a project team (who was coming back for the third extension of the project), “when are you going to tell me how you’re going to address this core issue of data quality?” Needless to say, that was a bit of an awkward conversation to be having at that stage in a project.
Data isn’t just about discovering what’s hidden; it’s also about seeing opportunities that could help you realize the deal’s benefits sooner. Data shows where there are synergies between the acquiring and selling companies, such as customer cross-sell and upsell. These days, data is a strategic asset class that must be evaluated accurately on its own merits.
Data Quality for the C-suite
The world has become dependent on data. It’s not always a priority for the C-suite – but it has to be. Executives will be well-positioned to accomplish or exceed company goals, whether they are financial and operational performance or enhanced customer experience if they commit to data literacy across the organization and focus on data quality that delivers meaningful business outcomes. Data is truly everyone’s business nowadays.
How are you ensuring data quality? Is your C-suite taking a more active role in data management? Tell us on Facebook, Twitter, and LinkedIn.
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