Making your own weather: your data management microclimate

Emerging master data management (MDM) and customer data integration (CDI) initiatives, along with the steady-state CRM efforts and growing business intelligence (BI) portfolios, are breathing new life into data management.

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This article originally appeared on the BeyeNETWORK.

I live in a microclimate. While most southern California neighborhoods bask in the balmy heat of climate Zones 9 and 10 – for you non-gardeners out there, that’s hot – my house sits in one of those small hillside canyons where the sun stays high and the nightly fog lingers into the morning. On a good day, I live in Zone 8. 

What this means is that I can grow clematis that friends living a mile away can only see in the pages of Sunset Magazine. Columbine pokes through, and in certain springs, the wisteria will actually pour down through the trellis planks like raindrops.  

Of course, I’m usually traveling the week this happens, but I’ve got pictures. 

We worked with a large high-tech company this past year that had a microclimate. The company’s executives paid lip service to big ideas, but were nevertheless change averse. The culture rewarded “doing your own thing” under the guise of innovation. Employees were acknowledged for building new applications which quickly became silos. Hunkering down and writing code was the order of the day, and skunkworks projects were the rule. Enterprise-level initiatives were not.  

Among this risk-averse culture, a small department of IT change agents not only grew, but thrived. I began working with a director who had secured grudging support for a new department. He was going to start the company’s formal data management organization. 

After an initial week together defining a charter, and another solidifying job roles, I was convinced that this director and his group would soon hit the compost heap. First of all, their collective energy level was palpably different than the rest of the employees stationed on their floor. But this team, headed by a man I’ll call Curtis, persevered. They built a mission statement, defined rules of engagement for the business, and began socializing the concept of managing data as a corporate asset. We built a data management strategy document that outlined relationships between business and IT initiatives with data, and detailed the tactics we needed to set up in order to manage data as an asset.  

When we decided to formally launch the enterprise data management (EDM) organization, we invited 23 managers and executives to the kickoff meeting. 25 people showed up to the meeting. (And to answer your question: No, there was no free food.) 

The people in Curtis’ group had an average tenure of three years at the company. Some were veterans, some were newbies. Some had come from the business side, some from IT. None of them had ever done exactly what their new jobs would require; but all of them had a passion for putting process around data as an asset in its own right, separate from platforms and projects. They looked forward to what they would learn and to using what they already knew. And, most importantly, they’d been around enough to be able to intuit EDM’s value to the company before they agreed to join the group. 

Change management wasn’t going to be an option for Curtis’ team. They needed to combine “missionary work” around communicating the value of a discrete data management function with delivering the quick wins that the company’s management held so dear. This combination of top-down education and expectations management with bottom-up delivery was a challenge. We didn’t need to tell Curtis something we tell almost every client: Don’t spend too much time on organizational charters, mission statements and laminated visions. Curtis was already there. 

What we did tell him helped craft the messaging for the launch meeting and manage expectations. Here are the basic tenets we laid out before we launched EDM: 

  • Have the answers, but expect more questions. After a couple meetings with some data stakeholders, one of the company’s entrenched cultural habits reared its head. People responded to questions with more questions. Turns out this is a common phenomenon in companies that don’t enforce individual KPIs and enforce ownership. During one meeting, Curtis asked a group of marketing product managers how they calculated return on marketing investment (ROMI). The product managers proceeded to milk Curtis for a formal definition of ROMI, rather than admitting that they had no reliable way of gauging which campaigns were successful. This team was practiced in the art of avoiding accountability. If campaigns weren’t successful, it was the advertising agency/printer/mailing house’s fault, not theirs. 

  • Paint pictures that align with people’s realities. In a meeting with application developers, we got a group of overworked practitioners to brainstorm about what they would work on if they didn’t have to focus on integrating data. Ideas from performance optimization to capacity planning to agile programming techniques popped up immediately. People were jazzed by the idea that if something routine and complex was removed from their workload, they could apply new learnings and concepts to their jobs. Bingo! 

  • Focus on providing a service. One of the most effective means of launching a data management team is to identify the group as a “service to the enterprise.” This has funding implications – ideally the group will be self-funded for a period of time during which they build up their value – but it’s also a captivating message for technology mangers who are focused anew on service-oriented architecture concepts where processes can be automated in a centralized and sustainable way. Making the cultural and technological linkages can help in communicating the value to busy IT people who might ultimately embrace the concept, and eventually pay for it. 

  • Seek agreement before commitment. Data management is evolution, not revolution. Most companies I know have been practicing at least a few components of data management for the past decade and beyond. The value of a centralized and customized data strategy and accompanying architecture has been realized in many companies. What’s important in building a data management team is to gain people’s trust, manage expectations about delivery and align around the philosophy that data is an asset that should be managed and measured. Only a brave and misinformed few will argue with the latter point. And the tactics can follow soon after. 

  • Dispel myths up front. Appeasing people’s fears usually means assuring them that they will continue to own their own domains. “We’re not going to own the CRM data, we’re just going to ensure that it reflects business rules,” Curtis told one project manager, “so that your team doesn’t have to.” The project manager sat back in her seat. If you have the authority to take headcount cuts off the table, allay fears about the loss of budget money, and promise new learnings that will enhance people’s work experiences and enrich their resumes, data management is more likely to get a fair shot. 

Data management is hard, rigorous and structured. It involves job changes, new hiring, scrapping and revamping entrenched methodologies, and the introduction of new conventions. It mandates handoff points and a teamwork culture that might be new to the company. It is, eventually anyway, a set of practices and methods employed at the corporate level. It reports to the CIO or a line-of-business executive willing to stick her neck out for the greater good. It’s hard, but it’s worth it. Data management, when done right, not only pays for itself over time, but drives new revenues through improved data quality, tighter integration, greater reuse and innovative, fact-based discoveries. 

Depending on your company, your management’s priorities, incumbent power centers (sales-driven versus operations-driven, for instance), it might not be a great idea to create your own weather. But maybe, just maybe, if the conditions are right, something new will grow and thrive, and the entire environment will be better for it.

Jill Dyché

Jill is a partner co-founder of Baseline Consulting, a technology and management consulting firm specializing in data integration and business analytics. Jill is the author of three acclaimed business books, the latest of which is Customer Data Integration: Reaching a Single Version of the Truth, co-authored with Evan Levy. Her blog, Inside the Biz, focuses on the business value of IT.

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