5 Tips for Making Data Work for Your Business
Leveraging advanced data and analytics (D&A) capabilities remains perhaps one of the largest untapped opportunities for many organizations. While some 47% of business leaders say D&A has fundamentally changed their industries over the last four years, many still struggle to put their data to work to optimize performance and capitalize on opportunities.
The obstacles take multiple forms:
- Lack of executive buy-in. Tapping into D&A requires a substantial investment of time, money and resources and it can be hard to convince key decision-makers that the ROI is worthwhile. Digitizing offline data, analyzing unstructured data and figuring out what you’re trying to achieve as a strategy are big commitments that don’t come easily or cheaply.
- Data quality. In many cases, an organization’s data isn’t up to par for a full-on D&A strategy. It may be incomplete, inconsistent or include duplications and discrepancies. This manifests in two big roadblocks: The overwhelming chore of data clean up and the fear of getting started without doing so keeps many D&A strategies from getting off the ground.
- Integrating data into workflows. Too often the actionability of data — what you can do with it — is left off to the side, excluded from the D&A strategy. Companies focus on what they could do with their newfound insights, but these never make their way into the workflow so that these insights are actually used. The result: Pretty charts that aren’t very actionable.
In order to overcome these barriers to D&A success, companies must implement clear and relevant strategies that focus on real business cases. Too often data scientists get excited about data and its nuances, but the organization doesn’t know how to operationalize the insights and turn them into action that drives business results. Here’s how to overcome that problem, along with other tips that can help ensure you get the maximum ROI out of your D&A investment.
1. Start with the “why.” The best D&A strategy starts with identifying your business goals. What do you want to do or do better? What gaps are holding you back? Oftentimes, business units may not be able to fully understand how data can help them, or they’ll think they don’t need it until you can show some specific use cases.
For example, sales organizations often don’t think they need data because they already interact with the customer and know what they want. Yet D&A initiatives are very effective at identifying cross-sell opportunities by surfacing the buying patterns of customers with similar profiles, enabling sales reps to suggest additional products. D&A can also help to predict which customers are most likely to churn, allowing the sales and customer service teams to take action before they cancel.
2. Set realistic expectations. Companies often experience two big pitfalls in their D&A strategy: They overestimate what they can do with their data and underestimate the effort and timeline needed to make real use of it.
In the insurance industry, for example, we have so much rich data available about the end-insured, in-force policies, risks and more. The problem is it’s mostly sitting in paper documents. So, while we do have an incredible amount of data, extracting it and making it useful is incredibly hard without an automated solution purpose-built for this task. That’s why I advise companies that they must be realistic in how quickly they can digitize their data, what they can get from it and how long the process might take.
3. Use business cases to get executive buy-in. To move a D&A strategy from theory to practice, make the case with real-world examples of the kind of insights your strategy can deliver. Concrete examples of what’s possible—with the practical business applications and benefits – help decision-makers understand why a D&A strategy is even necessary, let alone worth the spend.
For example, when the pandemic caused widespread lockdown and business closures in the hospitality industry, most downstream or related businesses didn’t have a way to accurately forecast what their own impact might be. The ability to analyze your data by business sector allows you to look ahead, figure out what your exposure might be to market forces and respond with more customer support, or even a shift in your business strategy to optimize your own business performance in the face of challenging times.
4. Build policies around data quality. While you will need to invest the resources to retroactively clean up existing data, start right now with policies and procedures that focus on data quality at the point of data entry. For example, if analyzing customers by industry classification is important for your D&A strategy, it can’t be an optional field of entry. Require complete, accurate data entry from this point forward and give your sales and customer service reps the right tools they need to do so.
Also, set up your D&A strategy for long-term success by preparing for both your current and future data collection needs. Create an infrastructure that allows you easily adjust to capture additional data as needs arise. It’s much easier to do it now than to go back and try to add more on the backend. When it’s clean, accurate and usable, you can never have too much data.
Finally, don’t wait until your data is perfect: it’ll never happen, and many, many opportunities will have passed you by.
5. Build partnerships between IT/data leaders and business units. Building a D&A program without addressing the needs of the business is putting the cart before the horse. A successful D&A strategy – one where a business truly realizes the value of its D&A investment – is a full-business initiative. IT and data leaders who partner with the business to understand their pain points and opportunities, and then connect those dots to what the data and tools available can do, can maximize the impact and value of a D&A strategy.
It’s no secret that unlocking your business data with a smart, robust and actionable D&A program is the key to business growth in the modern era. But with many organizations still struggling to figure out the best strategy, those who do will quickly surge to the head of the pack. By implementing these best practices, businesses in any sector can formulate and execute on a D&A strategy that delivers clear, measurable business value and growth.
About the Author
Scott Ziemke, Director of Data Science, Vertafore
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