Training Up the Organization Chart Is Job One

(US and Canada) For several years, I’ve advised my clients — and anyone who would listen — that “training up the organization chart” is the most important job of whoever holds the Top Data Job (TDJ). I find that once stated, most data people readily agree. But the topic doesn’t appear on job descriptions and receives far too little attention. This article aims to begin to address this situation.

Why Training Senior Leaders Is So Urgent

No one denies that data has become increasingly important.  But the pace of “all things data” seems agonizingly slow.  While many factors contribute, one big one is that, by and large, senior leaders have stayed on the sidelines. This is a killer because data programs need leaders to help connect data and business priorities, provide political cover, and drive change. Without them, data programs struggle to gain traction. Even after a solid success or two, they find scaling up difficult. Well-conceived and executed data and analytics programs can be transformative, but sooner or later — usually sooner — expectations exceed delivery. The short tenure of most Chief Data Officers bears testament to this dynamic.

I have enormous sympathy for senior leaders. They have a lot on their plates and, absent very good reasons, the time they can devote to data is scant. Furthermore, the data space is a confusing mess. There is data quality, data governance, data-driven decisions, data privacy, data science, data ethics, data monetization, and on and on. They cannot open their email or a magazine without a deluge on digital transformation, security, blockchain, and artificial intelligence. Confounding this, where are the big successes, outside the FAANGs, anyway? And if artificial intelligence is so great, where was it during COVID-19? Finally, many reason “I dealt with these issues as I worked my way up. What’s different now?”

Untangle the hairball

During the first year of COVID, I spent an hour most weeks with the head of a mid-sized media company, exploring what a data-driven XYZ would look like. Maybe 40 hours, all told. He talked about the issues the company and he personally faced, specifically due to COVID and longer-term. I introduced various scenarios involving quality, data science, artificial intelligence, common language, and so forth. Over time, we took particular care to untangle the “data hairball” in terms he appreciated. We talked about practicalities — what he personally needed to worry about, who would be the first hire, where that person would report, what they should do first, what support both he and others would need to provide, and the like. Finally, we talked extensively about what he could “sell,” the constraints he faced, and the political capital he had and was willing to spend, as he introduced data to his leadership team and the larger company.    I rate this leader as “fully trained.”  His actions have since proved it.

 Create opportunities on the confluence of what you need and what senior leaders can do. You are unlikely to get an hour a week from the head of the company, so you will have to create other opportunities. Two areas may provide them. First, most senior leaders I’ve met (admittedly a small and possibly biased sample) genuinely want to help, and the others want to be perceived as such. At some level, they know all too well how difficult it is to introduce new ideas into any organization, and they know innovation is important.  

What CDOs need most, particularly early in their tenures, are connections. One CDO, tasked with starting their company’s data program, decided to focus first on quality — after all, everything in the data space depends on high quality. To address quality properly, she needed to build an extensive network of embedded data managers to touch every work team. Building such a network would have taken months. So instead, she asked the management committee for help.  In posing her request, she provided a primer on a few fundamentals of quality.  

There is much to learn from this example. First, this CDO aligned her task to something senior managers are uniquely good at — connecting her to the right people in different departments. She needed help, and they provided it. Second, senior leaders, like most people, learn by doing. Thus, the background this CDO provided was not some abstract discussion on the details of data quality; it was tied directly to the task she asked them to take on. Finally, it created the opportunity for her to report some months down the road on the embeds' effectiveness and provide the next bit of training. 

So, how are we doing?

The second training opportunity arises because many senior leaders are interested in “How do we compare to others in our industry?” After all, no one wants to look bad or to be caught flat-footed by a more innovative competitor (conversely, some want to be among the leaders).  

Look for opportunities to provide answers to these questions, providing training as necessary context. Senior leaders trust other senior leaders and outsiders more than insiders in this regard. Bring them in — judiciously, of course! Benchmark surveys, in which you compare your company against others, also provide a great opportunity. I’m most familiar with data quality benchmarks. Most companies think they are far better than their peers, and finding out otherwise is a real eye-opener!

In closing

Senior data professionals must devote considerable effort to training more senior leaders. The goal, of course, is to enroll them in the effort. Unfortunately, there is no “script” for training senior leaders, and I doubt one will exist for quite some time. After all, the topic is broad and confusing; companies are in different situations, and leaders have different styles and interests.

The good news is that you can find opportunities if you know where to look. Furthermore, a short list of “what senior leaders need to know” and approaches to help them buy in are clarifying themselves. I’ll dig more deeply into these topics in future columns.

About the Author

Thomas C. Redman, Ph.D., “the Data Doc,” is President of Data Quality Solutions. He helps start-ups and multinationals,  senior executives, Chief Data Officers, and leaders buried deep in their organizations chart their courses to data-driven futures, emphasizing quality and analytics. Redman holds a doctorate in statistics.