Many people have the perception that data governance is all about policies and mandates, committees and paperwork, without any real "rubber on the road" impact.
I want to dispel this viewpoint by sharing a simple example of how one company implemented data governance to enforce something practical that delivered long-term benefits for customers, stakeholders and users. The form of governance in question relates to implementing better standards and approaches toward data migration projects.
Data migrations are notoriously tricky projects to pull off successfully because they're not something companies perform on a regular basis. They're also a project that has traditionally been devalued as a tech-centric endeavour and therefore outsourced or given minimal oversight. But the reality is that a poorly executed data migration can cause the transformation efforts of your business to grind to a halt (or at least a lumbering, sloth-like pace).
I won't turn this into a how do you do data migration post because there is a stack of posts about data migration on the Roundtable and also on my Data Migration Pro site. What I will say is that most data migration projects fail because of very simple mistakes that are easily avoided.
A good example was the car manufacturer that refused to appoint a data migration expert to help define its strategy because the company just "wanted to go with ETL instead." Another example was the telco that wanted to do its business analysis using analysts 10,000 miles away "to cut costs and delivery lead times." Another example was a utility that "didn't want to get bogged down with data quality," so the company elected to try to fix all the defects in its target system.
You see what I mean? Simple mistakes. Easily avoided.
But how do you avoid these mistakes? How do you stop your teams and partners making the same, fundamental mistakes every single time?
For one organisation, the answer lay in its data governance foundation. This organization reviewed the types of best practices that practitioners write about here on the Roundtable and Data Migration Pro. And it compiled those best practices into a Corporate Guide for Data Migration, and then baked them into its data governance processes.
But most companies have a mass of these policies on their virtual shelves – and that's often where they stay, neglected.
So what did the organization do to make this policy enforceable?
The company made it mandatory for any data-driven project to go through a peer review that would be checked off against existing data policies. Think of it as building control and planning permission for your home. You can't just erect a new two-story extension to your existing home (well, at least not in the UK !). You have to first seek approval from the governing body (planning permission) and then have several visits from building control (experts in construction) to ensure the building meets required standards.
We're going through house modernisation right now, and it's a pain going through the governance process. But I understand that it's in my best interest to build a structure that will be safe and habitable for my family.
That's what you need to do with your data governance controls.
Those controls need to deliver more reliable and predictable projects, using commonsense standards, that all too often fly out of the window when budgets, partners or deadlines change.
The company in my example lacked data migration expertise, so they brought me in as their "building control officer" on any new projects they implemented. My job was to help review the proposed migration strategy and highlight any red flags. Using this centralised approach, the company gradually built up its policies to cover other areas of data management so that the maturity of the whole organisation improved.
Have you had success "operationalising" data governance? Would love to hear your stories and comments below.