The first time I met a bona fide Data Czar I thought of Pepperidge Farm. Actually, a lot of topics evoke Pepperidge Farm for me. Though I’m not a big fan of those Goldfish, don’t get me started on their Chessmen cookies. They’re like shortbread, but with extra butter, and you can’t eat just one… but I digress.

The reason I thought about Pepperidge Farm when I met the Data Czar was because Pepperidge Farm has a title called, “General Manager of Snacks.” Now that’s a job title! And it was probably invented by the person who wanted that job and needed something on his business card that reflected the reality of the position. I wonder if the General Manager of Snacks at Pepperidge Farm taste-tests Chessmen? And if so, does he have one of those spit-buckets like they do at wineries for people who’ve had enough? Really, if you’ve ever had a Chessman, you’d realize how unnecessary a spit-bucket was.

Anyway, this Data Czar was actually doing an important job for his company. I asked him to describe his role in a sentence or two, and he said, “My role is to make sure that data is really managed as an asset – just like you’ve been talking about!” Here was someone who was walking the walk.

We had lunch and talked about his day-to-day activities. The Data Czar had successfully convinced his CIO to establish the position, and he reported directly to her. The CIO had been clear about her expectations: in order to keep his job, the Data Czar’s team needed to be self-funding. Consequently, measurement was a big deal for him, and he was rigorous about it. The Data Czar’s team was constantly prioritizing new initiatives based on their potential economies of scale, measuring improvements in data quality and usage, and doing before-and-after scenarios of business initiatives that had been information-enabled. He had a variety of positions reporting to him, including data modelers, data and metadata administrators, data stewards and project managers for individual departmental efforts. He had just instituted a Data Quality Center of Excellence that was slated to be its own self-funding unit. The Data Czar knew most of the company’s line of business executives well, and a few of them were on speed-dial.

But the Data Czar was by no means completely sure of what he was doing at all times. His company, a well-known retailer, was big on packaged applications, and new systems (aka: new data sources) were being introduced regularly. He still had trouble making sure his group was kept apprised of projects in IT’s pipeline. And he had his share of politics, too. Not surprisingly, when I asked him about his top three challenges, he gave me five:

1. Data hoarding. Even though the Data Czar had the full support of the CIO and the executive staff, he couldn’t convince certain departments to share their data. “Managing data as an asset” had entered the corporate lexicon. Nevertheless, marketing and finance were stonewalling his organization, and business initiatives had suffered as a result.
   
   
2. “Executive ADD.” The Data Czar was a victim of his own competence. Although the CIO had given him support and funding, he was often called in to advise on troubled projects, many of which had bigger problems than just data. The Data Czar had been careful to repeat the question, “What is the goal of this project, and how can data help?” However, several executives continued to rely on him for his business knowledge and problem-solving skills. While flattered by this, he knew his organization risked losing focus.
   
   
3. Dirty data. No, it never goes away. With the onslaught of new packaged software came untested, poorly defined, often-proprietary, loose-ruled data. New data was coming in faster than the Data Czar could assign someone to steward it, which brings us to the next challenge.
   
   

   -----
   Related content from the BeyeNETWORK
   
   Read this white paper to learn the role of data governance programs in supporting compliance efforts with a focus on the types of contributions these efforts make, especially in the areas of managing compliance costs.

   
   Click Here
   -----

4. A shortage of skilled personnel. The Data Czar was short on data stewards. He’d originally assigned a steward for each of the company’s subject areas, but the data was so complex that he discovered he needed specialists to understand the inbound and outbound data from specific systems, such as the company’s ERP system. He could find ERP experts, but they weren’t necessarily “data people.” And even when he managed to wring a new staff requisition from the CIO, the Data Czar knew that the business and company-specific knowledge would still need to evolve.
   
   
5. Ticked-off developers. When the CIO announced the Data Czar position, there was a sigh of relief among the scores of application developers who’d been managing their own data with a mixture of brute force, book learning and long hours. Finally, someone would take over the data administration and integration work, centralizing these processes and making them available as a service to the applications and projects that needed the data. But not so fast! See Number 4, above. The company’s IT and HR people were much better finding application developers than they were data experts. The shortage of skilled resources combined with the escalating workload meant that some IT developers still needed to “do their own data.”

The Data Czar was circumspect about these issues. After all, the CIO had only given him one metric – pay for your department – and he’d recently met that goal. But he wanted to be seen as less of an overhead guy and didn’t want to be associated with “infrastructure.” I asked him if he wanted to be a hero.

“No,” he replied, “just a solutions provider.”

And so began my little project, “Coaching the Data Czar.” Working with him for a couple hours each morning, we built a simple strategy that we hoped would transform his reputation in the company and cement the data management function and its value proposition. We came up with three immediate tactics that would trigger the initial change.

1. The Data Road Show. The Data Czar had been measuring the improvements and economies of scale delivered by data quality refinement and data integration activities. It was time to broaden the audience for this message and toot the proverbial horn. We scheduled “Lunch and Learn” sessions for different departments to come to hear how their data had improved. Each session had to include an in-depth description of the business benefits delivered by integrated data. Ideally, this discussion would be led by a business user, not the Data Czar.
   
   
2. Deploy Additional Metadata. In discussing information availability, quality and accessibility with some of the company’s business users, it was clear that they still weren’t sure how to get the data they needed and where to find it. Many of them still relied on human relationships in order to get the reports they needed. We decided to develop a metadata taxonomy, do a gap analysis to see what metadata was still necessary, and put that work in the Data Czar’s development pipeline.
   
   
3. Introduce Master Data Management (MDM) through Customer Data Integration (CDI). Although the company’s data was robust and increasingly integrated, there was still no overarching master data management strategy. The impact of this on the business was traceable. In particular, there were 43 different sources for customer data, and no one had really engaged the business units on what the ideal rules should be for customer data. The Data Czar had been researching MDM, but wasn’t sure where to start. We decided to start with a CDI project to bring the management of customer master data into the limelight. We calculated that the CDI project could pay for itself in seven months.

The Data Czar had done a lot of the hard work, but there was still work to do. Of the three overarching tactics we identified, we decided to begin with the road show, which would be comprised of two parts, each an hour long. We called the first hour “Rearview Mirror” and it would focus on what the Data Czar and his team had done to date, and how they’d succeeded. The Data Czar enlisted a businessperson to present the successes on his team’s behalf. The second hour was called “Looking Ahead,” and it described what was still left to be done. We would tee up the metadata and CDI projects during this hour.

I must say, the road shows went swimmingly well, and not just because we served lunch between Rearview Mirror and Looking Ahead. People really wanted to see how their business initiatives had been affected by data and what the Data Czar and his team had actually been doing. It was cathartic for the Data Czar, too, since he’d felt that his successes had been confined to the CIO’s office, and he was able to sing loud and strong in front of a wider audience.

I was happy, too. For one thing, I’d taken an already-successful client and propelled them forward. The client had taken my suggestions and acted on them. One of those suggestions was to serve Chessmen cookies for dessert during the road show meetings. It was just one of those really good days.

Recent articles by Jill Dyché

• When Data Can’t Be Trusted, Master Data Management Becomes “Plan B”
• From Popcorn to Meat and Potatoes: Data Governance Evolves
• Confessions of a Data Governance Sponsor
• Data Governance in 3-D