Playing with Numbers
As you will see from my signature at the end of this note (provided you have enough patience to finish it), I am a business analyst in my current role (and also by my background). This was probably a lucky career choice, finely tuned to one of my personality traits. I always loved analysing things in search for interesting and surprising facts. Here is a simple exercise I did recently with a few numbers from the ‘State of Data Governance’ survey conducted by First San Francisco Partners in the US. This is what they asked their respondents, among other things:
Anna Ovchinnikova, Senior Business Analyst, Perfex Lab; firstname.lastname@example.org
Anna will be speaking alongside Andrey Pavlov at the Data Governance Conference & Master Data Management Summit 14-17 May in London. They will be speaking on the subject, “Maximising Business Outcomes of a Data Governance Programme by Bridging it with Business Performance Management“
‘What do you believe is the biggest obstacle to establishing a formal data governance strategy?’
‘Not seen as important by senior management’, answered 18.75% of the survey audience.
‘Lack of resources’ was the answer from 39.58% of them. (A direct consequence of senior management’s lack of interest, I guess.)
‘Too hard to prove the business case’ hit 20.83%. (Another acknowledgement of the same fact, probably.)
By running a total of the three numbers above, I got an interesting result: in 79.16% of participating companies, the level of support from senior management for their data governance initiative is discouragingly low.
And where the C-Suite demonstrates limited interest and involvement, the lower echelons of business users would normally follow suit.
Shall the Twain Meet?
There are of course a good few reasons why active participation in data governance can be accepted with only a moderate enthusiasm by business leadership, LOB’s and business departments.
Articulating the potential impact of governed data on business value is not an easy task, and the ROI is hard to quantify. There is ever-present resistance to change and shortage of resources for engagement, as employees in business functions are already overloaded with other tasks. (But of course, ‘too busy’ has always been just a polite substitute to ‘not a priority’.)
But there is this one other reason. It may sound a bit harsh, but lean closer to reality.
Data governance is, naturally, about data. But business has limited interest in data, if any at all.
A reckless statement probably, but it comes from my 10+ years of experience on both sides of the fence: consulting and client-side.
Two remarks are needed at this point though.
First, there is one category of business specialists that does possess an immense interest in data: my former comrades-in-arms—functional business analysts—are always in search for a fresh subset of data to feed their analytical models.
Bad news—they show absolutely no interest in governance.
Second remark relates to data quality, that has been declared the key business deliverable in most data governance business cases we have seen so far.
No doubt that business is interested in quality of data at large, as it has direct impact on the quality of managerial decisions. But in everyday life, data quality is clearly considered a subject residing in its entirety within the IT domain.
In the same way the conductor of a philharmonic orchestra is not concerned with the technical mastery of her oboe player, she just takes it for granted.
So, if my hypothesis has an element of truth in it, and business folk are not really interested in data, then we need to readjust the focus of a data governance programme to gain their buy-in.
How exactly? Let me share a story first.
Call Setup Rate Falling
The project at this mobile telecom company was clearly heading nowhere. It all started with an unlucky title themed around ‘metadata management’ and after the initial outburst of enthusiasm everything came to a halt. IT was juggling with ‘technical metadata’ and ‘business metadata’ clubs, while marketing (nominated to represent the business) showed no signs of interest.
It was at this point that we met with their Chief Technology Officer (CTO), for the first time, on a mission to gain a wider support from the C-Level. Five minutes into the discussion he interrupted us with a fairly resolute ‘I need this’.
His primary responsibility, he explained, was in maintaining the quality of their wireless network at a highest level, as it had an immediate effect on subscribers’ experience. To achieve that goal, his team had to monitor a set of around 300 metrics, based on data generated by network equipment, on a regular basis.
Keeping each metric in this set accurate and actual was a critical issue, but almost impossible to resolve, as the only governance tool in their possession was a mammoth MS Word file. As a result, quite often a miscalculated or misinterpreted metric would lead to a wrong technical decision followed by failure of a certain network node. Which, of course, did not make their customer service managers any happier and their subscriber churn rates any lower.
Three months from the first meeting with the CTO, we delivered results of this initially unplanned project track: full inventory of reports and metrics completed, business glossary filled with content, and data sources defined and linked to content. And, of course, stewards assigned and functioning, and (simple) governance processes running smoothly.
‘Good example highlighting the importance of C-Level sponsorship’, one may say.
No doubt—but not only that.
The most important lesson we learned from this experience: business involvement is almost guaranteed where there is a highly visible (almost palpable) connection between the data, the context in which the data is presented, the outcome of a data-driven decision and, finally, business performance of a certain function (or company).
This is exactly how, in my opinion, we should readjust the focus of data governance to make it more appealing to business—by replacing the vague promise of ‘better data’ with a clear path to improved business performance.
Business Glossary or Glossary for Business?
I must apologise here for the ‘data-driven decision’ cliché used in one of the sentences above. Business decisions are indeed driven by information, not data. And in most cases by a very specific type of information: metric.
Therefore, the metric (or ‘indicator’), in my opinion, is destined to be used as a key argument in our bid for business engagement in data governance.
Quality of data is just too abstract of a concept and definitely someone else’s problem. Quality of metric, in contrast, can be comfortably grasped and irrefutably related to business performance, as illustrated in the telco story above. And our pitch can get even more convincing when we switch the emphasis from a single metric to a system of metrics.
Now we are talking business.
Let us just clarify the terms first, as ‘system of metrics’ may sound a bit alien to our business colleagues. Within their borders they call it ‘performance measurement system’. Something they had a go at in the Balanced Scorecard era and probably failed. And, of course, performance measurement system is the cornerstone of business performance management. (I probably had to remind here the old mantra ‘you can’t manage what you can’t measure’, but that would be another cliché, would it not?)
But what if this whole idea of attaching ourselves to a clearly business practice of performance measurement takes us a step too far into our neighbours’ territory? Shall we not leave to Cesar what is Cesar’s?
Well, we shall not.
First of all, I cannot think of a stronger driver for a business-focused data governance initiative than contribution to business performance.
And then, we are doing it already, are we not? Collecting definitions, terms and (probably) metrics to charge our Business Glossary?
Let us just change our positioning and repurpose the Business Glossary as a Glossary for Business. Not a place to store some business content intended to guide us in our quest for better data, but as a business tool playing the three-part role of a guarantor, mediator and navigator for one of the most critical information assets owned by business.
To perform this role effectively, the Glossary will need to comply, at minimum, to the following standards: be centred around the metric (performance measure), be structured with a business user in mind and be complete.
Building such a business tool is a very challenging mission indeed. Challenging, but not impossible if approached with a good plan at hand.
Interested to know more?
Ignore Google. Ask me.
Anna brings more than 10 years of experience in business analytics to her current role as a leader of Performance Excellence Lab (Perfex Lab), an R&D team of Acctiva Limited. Her background gives her a unique understanding of the viewpoint of business information consumers and their needs. Anna has played a key role in developing Perfex Lab’s business performance measurement framework that serves as a foundational component for business-led information governance. She has also worked on a number of external client engagements in the retail, pharmaceutical and other industries, focusing on delivering meaningful and sustained business value. Anna leverages her diverse practical experience, deep understanding of modern technologies and strong academic knowledge to advocate for closer interconnection between business performance management and information governance, and she presents and writes regularly on this topic. She holds an MSc and PhD degrees from National Technical University of Ukraine.
Copyright Anna Ovchinnikova, Senior Business Analyst, Perfex Lab