Want To Make a Case for Better Data? Think Southwest.
The 2022 December holiday season will go down in history as one of the worst of travel nightmares, especially for travelers flying on Southwest Airlines. A massive winter storm stretching across most of the US caused its critical IT applications to fail. The airline ended up canceling more than 16,700 flights over roughly a one-day period, leaving hundreds of thousands of customers and employees stranded, losing mountains of luggage, and leaving billions of dollars in unused assets sitting idle on the runways. This operational disruption was an especially costly one — roughly $800 million in reimbursement expenses, undesired regulatory scrutiny, projected revenue losses in Q1 of $300 million to $350 million, and immeasurable damage to reputation and brand. 1, 2
In response, Southwest CEO Bob Jordan plans to accelerate the modernization of IT applications and processes that will mitigate the risk of such a disruption ever happening again3. But investing in IT tech and infrastructure is not enough. Organizations like Southwest need to adopt a data-centric approach to IT modernization, investing in data as their most important asset and structuring their IT applications around it.
A Technology-First Approach Erodes Trust in Your Data
Time and time again, I have worked with clients who are struggling to realize the value of their IT investments because of a lack of trust in their data. According to a survey conducted on behalf of Dun & Bradstreet and reported in our 9th Annual B2B Sales & Marketing Data Report, data quality issues continue to be a pervasive problem for B2B organizations. A third of organizations struggle with data accuracy and consistency across platforms.
Why is this the case? The recent trend of a technology-first approach to IT modernization is a key contributor, creating Frankenstein-like monsters of applications that are unable to talk to each other. When teams are not able to easily access critical data on customers, suppliers, and partners, the outcome is manual workarounds and data silos. Before long, senior leadership begins to question the value associated with the IT investments that were supposed to simplify and standardize the consumption of data.
Organizations like Southwest can avoid going down this path by adopting a data-centric approach to IT modernization that will ultimately save time, money, and resources.
Being Data Centric Reduces Costs and Speeds Time to Value
When we talk about being data centric, what does that really mean? I believe it means having a business culture that values data over the adoption of individual applications and services. It means that an organization’s culture encourages team members to be data-driven and to leverage tools, analytics, and metrics to support their decisions. Data is valued as an enterprise resource; silos are discouraged, and data governance is a team sport. Data on customers and suppliers is prioritized, mastered, and governed, and the organization has commonly accepted definitions and attributes utilized across all platforms, enabling them to talk to each other.
Having worked with many clients to improve their data quality, I want to highlight two simple data-centric practices that will set up an organization for success with IT modernization initiatives:
1. Assess your data quality by making sure it’s fit for purpose.
2. Leverage third-party data subject-matter expertise, where applicable, for a subjective view of your data and data quality.
What Is Good Data Quality?
We are often asked if Dun & Bradstreet publishes a definition of data quality. Although there are dimensions of data quality that we recommend, like accuracy, completeness, timeliness, and consistency, the short answer to the question is, “No, we do not endorse a definition of data quality.” The reason is clear: The definition of data quality is unique for each organization, with the ultimate measure of that being whether it meets the needs of the business. Data-centric organizations map their use cases back to the data needed to support them and put governance in place to benchmark and track data quality over time. Some use case questions to consider:
- Does our data support our go-to-market strategy?
- Are there commonly agreed upon definitions of our most critical data (customers, suppliers, and partners) that enable applications and departments (and people) to communicate with each other?
- Do we enable enterprise visibility for critical functional areas like sales, analytics, finance, risk, compliance, and marketing?
- Is our data easily accessible to those who need to use it?
Metrics are critical in the context of these uses cases — ensuring that the data needed to support them is accurate, complete, timely, and consistent.
Assess Data Health Before IT Modernization Efforts
When undertaking IT modernization initiatives, it is common practice to cleanse data before moving it into a new platform or application. But more often than not, the cleansing exercise is initiated late in the project timeline and does not allow for the time, budget, and resources needed to adequately assess and cleanse the data. Cleanup efforts require engagement and feedback from business owners and often require investigative work to identify and correct the root causes of data quality issues up- and downstream. If this is not done early and often, data issues create risk for implementation timelines and the integrity of the application itself. So don’t wait; get going on the data early.
Don’t Go This Alone — Get an Objective View of Your Data
Over the course of my career, I have supported many IT modernization initiatives, including MDM, CRM, ERP, and countless other three-letter application acronyms. But the clients I work with are often going through IT modernization initiatives for the first time. They don’t know what they don’t know; they know what they are being asked to do, but they don’t know where to start. This is where I recommend engaging with a third-party data provider to save both time and money. Not only will a third party objectively assess the health of your data, but it will also come to the table with pitfalls to avoid and best practices to adopt based on its collective experience of working with many clients just like you! Entity resolution, deduplication, and account aggregation are especially complex concepts for organizations that may not yet even agree on their definition of a customer. So reach out for help! Open collaboration, including the sharing of use cases, KPIs, milestones, and budgetary requirements, forges a partnership with shared goals and vested outcomes. In addition to data expertise, third-party providers bring an outside-in perspective and provide expertise on building business cases, organizational data maturity, data integration, design, and data to support your use cases.
Another thought to keep in mind is that having high-quality internal data isn’t always enough if the data will not enable all your use cases (for example, being asked to support a vertical go-to-market strategy based on industry without having the industry names or codes that current customers and prospects fall into). In this case, the organization has two options: Either build the data, or buy it from a third-party provider. It is possible to build, that is, to gather the industry information yourself, but there are drawbacks: It can take a long time, you run the risk of the data being subjectively biased by the individuals manually creating it, and it may be difficult and costly to maintain. But industry classifications are an off-the-shelf attribute for many third-party data providers and come with instituted data governance standards and maintenance practices. In cases like this, the business case for buying the industry data (or other segmentation, risk, and behavioral data) is the fastest, cheapest, and most objective path to enabling your use cases and setting up your IT projects for success.
Taking Flight With Your Data
As Southwest Airlines moves forward, the reparation costs and lost revenue will far exceed the investment costs associated with modernizing their IT. For any business that is going to undertake that effort, I recommend modernizing your approach by starting with, and maintaining, a focus on your data.
Here's a first step. Find out if your data has what it takes to meet your marketing objectives with Dun & Bradstreet's free, self-service Data HealthScan report. It's worth checking out.
AMY COOPER, Principal Consultant with the Dun & Bradstreet Data Advisory Services team, is a 30-year veteran in data management. In her career with Dun & Bradstreet and with Gartner, Amy has worked with some of the most complex organizations in the world supporting Master Data initiatives at the enterprise level and at the sales, marketing, analytics, supply, and finance functional levels.