Help improve decisions and results with a strong data foundation
Once you decide that it’s time for your business to become data-driven, you need to take a crucial first step. It might sound silly, but data management experts recommend that you remind yourself to actually make data the top priority. While data is the main ingredient in data-driven initiatives, it sometimes becomes an afterthought for the tools and processes that depend on it.
Too many companies have learned this the hard way. If you flow less-than-stellar data into a robust CRM platform, a highly sophisticated risk model, or a powerful generative AI application, the output may be dubious at best. And when you base decisions on their less-than-stellar analysis or reporting, you’re likely to experience disappointment, distrust, and even potential business disruption.
Whatever your strategic focus is – customer acquisition and retention, revenue and profitability, supply chain management, fraud prevention and regulatory compliance – company-wide access to current, comprehensive, and meaningful data is vital. According to George L’Heureux, Jr., Senior Director of Product Management at Dun & Bradstreet, “Going forward, we need to think of data as the lingua franca of business. For companies to be effective, they need team members, every one of them, to be not only literate but fluent in data.”
As L’Heureux and other data experts explained in the 10th Annual Dun & Bradstreet B2B Data Report, a shared commitment to data quality can help your company reduce risks, work more efficiently, and grow. “Data is the language in which we do business,” he noted. “It’s how we make decisions. It’s how we talk to one another. And it’s how we’re going to be able to measure our success or our failure.”
Understand What You Have and What You Need
Your data should help provide a comprehensive view of prospective customers and your existing customers. That view should include high-quality business insights, so that your teams can take actions that help drive revenue and healthy growth. To gauge the current state of data, your teams need to be asking some hard questions.
- How easily can our team, and the other teams with which we collaborate, use our company’s data and analytics tools to make decisions?
- How effectively are our company’s data and tools reducing manual tasks for our team and the other teams with which we work?
- What data challenges prevent our team from benchmarking/measuring success on key objectives?
- How confident is our team that the data in our company’s core systems and technology is current and comprehensive?
- How challenging is it for teams to keep the data in those core systems up to date?
What about your internal data management processes? Are they adding any roadblocks? To find your answer, try taking stock of data expertise by launching a company survey, or a series of internal interviews, to help assess knowledge gaps and identify training needs.
Next, ensure that good data security habits are being encouraged and modelled. To help teams understand how to protect data integrity, avoid errors, and prevent fraud, make sure clear, regular communications about security protocols are available and distributed.
Confirm that data governance policies are being communicated and applied. Secure executive buy-in for clear guidelines that explain how to safely store and share data. Finally, start working on a roll-out plan that will help spell out the goals, timelines, and value of a data quality initiative for all teams in the company.
Choose a Data Provider
After you identify where you have vulnerabilities or gaps, the next step in becoming data-driven is to choose a B2B data vendor. Using comprehensive, trusted third-party data from an experienced data vendor can give your company more accurate, reliable, and timely business intelligence for decision-making.
As you begin discussions with a particular data company, ask yourself these questions to help assess the provider’s capabilities and strengths.
Data quality – Is the data accurate, comprehensive, and standardized? Is the data authoritative, credible, and fit for our purpose?
Data coverage – How many geographic regions are covered by the provider’s data? What is the percentage of businesses and commercial entities covered in each region? How extensive is the provider’s data for SMBs, corporates, multinationals, etc.?
Data freshness – How frequently is data refreshed? What triggers a refresh?
Innovation – Is the data company expanding its offerings? How and where is it using AI to strengthen its data solutions?
Expertise – Does the data vendor have dedicated teams for data science, economic research and analysis, etc.? What kinds of advisory/consultative services are offered?
Data security and compliance – What is this data vendor doing to reduce risks associated with data privacy, confidentiality breaches, or other security threats? How is it complying with legal and regulatory requirements?
Legitimacy, consistency, and reliability – What are the data origins and collection methods? Is the process/procedure legitimate and reasonable? How consistently is the procedure being followed? Does the data company have a compliance program in place?
Stability – How long has the data provider been in business? What sort of growth has it experienced? How is it performing financially, and what is its general reputation?
Integration – How easily can the vendor’s data integrate and adapt to any future upgrades of our systems?
Evaluating and selecting the data provider best suited to your needs are crucial to building a strong data foundation. For additional evaluation criteria and assessments of the 14 B2B data providers “that matter most,” read The Forrester Wave™: Marketing and Sales Data Providers for B2B, Q1 2024.
Secure Leadership Buy-in and Budget
While you may feel confident and ready to move forward at this point, remember that there is another important phase of the journey: Becoming a data-driven organization usually requires budget approval.
As you prepare to discuss budget with the buying group or other company executives, think about metrics. Pick four or five measurements that are valuable to your company and present them in context of your expected results. Be sure to also create advocates; convince different teams of the value of a data quality project, as there is often a domino effect to gaining agreement and collaboration.
Be ready to tell a good story, with a compelling narrative that helps those holding the purse strings really visualize the benefits. You’ll also want to provide clear, conservative figures for expenses as well as the anticipated return on investment.
Continue the Quest for Better Data Quality
The more resources, time, and effort that teams can commit together to improving data quality, the faster they can centralize and bring greater consistency to their data. As data quality, accessibility, and ease of use improve, so can collaborative, data-driven decisions across your business – decisions that can help you differentiate your company and outperform your rivals.
Want to help your business evolve even more quickly into a data-driven organization? Explore more resources from Dun & Bradstreet.
The information provided is for suggestion purposes only and is based on best practices. Dun & Bradstreet is not liable for the outcome or results of specific programs or tactics undertaken based on the information. Please contact an attorney or tax professional if you are in need of legal or tax advice.