Data Management Hasn’t Failed, but Data Management Storytelling Has

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Click to learn more about author Scott Taylor.

Let’s not kill the messengers; let’s fix the messaging!

In their recently published declaration, Data Management Has Failed!, John Ladley, Tom Redman, and a host of other long-time DAMA leaders drafted a call-to-action recommending the “bold, powerful moves” needed to secure business leader support for Data Management. They suggest we should:

1. Remove technology from the conversation.
2. Focus on outcomes, not minutiae.
3. Earn true senior-level engagement.

These are indeed worthy actions, but perhaps the real crux of the problem lurks deep in Ladley and Redman’s observation that, “As a community, we have failed to educate our leaders on the need for high-quality data . . . and craft messages that people will listen to.”

Yes, there is too much tech talk making Data Management messaging very hard to listen to. There are multiple reasons why Data Management programs may fail, yet an overwhelming majority suffer from an inability to demonstrate and then communicate business alignment. “Trouble is,” opined Jason Krantz, CEO of Strategy Titan, in a recent LinkedIn post, “In aggregate, we are not terribly good marketers or communicators of the value we bring to the table.” To fix this, we need to become better storytellers.

The current Data Management sales pitch simply isn’t convincing. “It’s unacceptable that the DAMA crowd hasn’t made any substantive progress in selling the benefits of Data Management to execs,” notes David Langer, VP of Analytics at Schedulicity. To solve this selling problem, we need to work on what I refer to (with a knowing wink to big data) as The 3Vs of Data Management storytelling — vocabulary, voice, and vision. Because as we sit here today:

  • Our vocabulary is confusing
  • Our voice is discordant
  • Our vision is blurred

Our Vocabulary is Confusing

The “need for high-quality data” has been the dominant rallying cry from data practitioners for decades. Redman references his Sloan Management Review piece stating, “Our ultimate goal has been to improve data and information quality by orders of magnitude.” Although it was published in 1995, it reads like it was written yesterday. That’s kind of the problem. These messages and lessons have been the same forever. 

Business leadership is just not inspired by the concept of “high-quality data.” If Data Quality was a successful way to pitch for senior-level engagement, it would have worked by now. It hasn’t. It never will. Quality is an emotional, subjective, intangible word that evokes soft-focus imagery of hand-crafted products and a Ricardo Montalbán-like voiceover cooing about “fine Corinthian leather.” Similar concepts, such as data hygiene, cleansing, and freshness, are rarely strategic and hardly holistic. Most data hygiene exercises are ad-hoc campaign-based projects isolated to a siloed use case. Although Data Quality metrics are important, and extremely valid within data departments, senior business leaders do not care about Data Quality. They care about results.

Vocabulary Tip: The words we use are important. To be convincing, we must go well beyond the legacy lexicon of the enterprise Data Management space. In executive discussions, replace inexact terms, such as “quality, cleansing, freshness, and hygiene” with definitive words like “structure, standards, coverage, and interoperability.”  You will notice a difference immediately.

Our Voice is Discordant

Data Management, as a practice area, has always been plagued by the lack of a consistent narrative. Blame it on the marketers, if you like, but the data community just loves to wallow in self-absorbed existential pondering. As debates rage among us about whether Data Governance is bigger than Data Management or vice versa — or if we should start calling it all “data enablement” — the rest of the enterprise moves on. When we bicker on these types of topics, the businesspeople say to themselves, “You see, even they don’t agree” and slowly back out of the meeting, leaving us fighting and unfunded.

It doesn’t help that Data Management efforts aren’t considered exciting, innovative, or “cool.” Meanwhile, business intelligence, in all its iterations (artificial intelligence, machine learning, etc.), enjoys a disproportionate amount of exposure, limelight, and support. The elevation of these practices to near-heroic stature continues to overemphasize business intelligence over Data Management.

Hot trends give the cold shoulder to Data Management. Where is the active voice of Data Management in Data Storytelling, Data Literacy and Data Visualization? I don’t hear it. Data Science, in all its sexiest-profession glamour, glosses over the core value of Data Management. We seem numb to claims that data scientists spend 50-80 percent of their time munging and wrangling data. Those cute terms mask a real issue. Much of that munging and wrangling can be avoided with access to better-managed data — data free of duplicates with well-governed, expertly-stewarded structure for hierarchies, taxonomies, and geographies. Do your data scientists even know where to find you?

We need to speak up. How many of you sit silently when a BI thought-leader boasts, “Without analytics, data is just a cost center” or “Data has no value unless it is turned into analytics.” That is your work they are talking about! A baker would never say, “Flour is worthless unless I make it into bread” because they have respect for the ingredients. There is no doubt that business intelligence provides incredible capabilities, but without proper Data Management, those efforts are futile. Challenge the analytics community to end this type of zero-sum portrayal of data vs. analytics value. It doesn’t help either group gain executive support.

Voice Tip: Get your Data Management elevator pitch ready. BI fails without proper DM. Devoid of Data Management, data storytellers have no story to tell — the plot may be based on analytics, but the characters come from Data Management. As Redman suggests, become a data provocateur. Reach out to those other constituencies, and let them know you are there to help — and that without your work, their work will suffer. Harmonize your voice in the key of business topics that stakeholders care about.

Our Vision is blurred

While I applaud the spirit of Ladley and Redman et al., I do not agree with their advice to “convince leadership that improving Data Management is more important than at least one item already on their ‘top five.’” Data Management will never make it on any corporate top-five priority list. Nor should it.

But here is why that is actually an opportunity. Better data is a mandatory requirement for most, if not all, of those top-five priorities. Study the key business initiatives of your organization. Do those objectives have anything to do with increasing market penetration? Operational efficiency? Mitigating risk? Strengthening security? Authenticating identity? Mergers and acquisitions? Data Management plays a mission-critical role in all of those.

Recognize that Data Management is actually macro-trend agnostic. Fintech, Martech, migration to the cloud, IoT, and the 4th industrial revolution all need a strong data foundation that only professional Data Management can provide. Data Management is a horizontal discipline that enables an enterprise to scale. The value of every digitally transformative customer-facing initiative, every as-a-service offering, every foray into e-commerce, and every enterprise software implementation is inextricably linked to the successful output of Data Management efforts.

Vision Tip: The vision of your Data Management program must enable the strategic intentions of your enterprise. Scour your company’s “top five,” and find each mention of relationships (customer, vendor, supplier, client, partner, prospect, patient, consumer, citizen) and brands (product, service, offering, location, banner, property, asset) as well as any form of analytics (BI, AI, ML, DL), and you will uncover the need for a steady flow of highly structured, standardized, secure, trusted content about those entities. If you can’t find any, I’ll help you.

Add Some Sizzle to Your Steak

Most Data Management leaders who I have known and loved are truly passionate about the value of data. They understand to their core that data can grow, improve, and protect their businesses. Many have challenges, however, articulating that value in a business-accessible manner — especially when competing for funding with better storytelling peers from sales and marketing. I, too, am a firm and fervent believer in the power and importance of proper Data Management and have spent my career successfully convincing senior business leaders to invest in it. To win over business stakeholders, Data Management leadership must craft a compelling narrative that builds urgency, reinvigorates enthusiasm, and evangelizes WHY their programs enable the strategic intentions of their enterprise. If the business leaders whose support and engagement you seek do not understand and accept the WHY, they will not care about the HOW. When communicating to executive leadership, skip the technical details, the feature functionality, and the reference architecture and focus on:

  • Establishing an accessible vocabulary
  • Harmonizing to a common voice
  • Illuminating the business vision

When you tell your Data Management story with that perspective, it can end happily ever after.

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