How to Prioritise Enterprise Data Governance Strategy

How to prioritise Data Governance Strategy

This is a guide for those that are being asked to engage in governing their data for the first time. If you have been asked to do this, with no real idea why or where you ought to begin, this article is for you. We will cover the questions you need to answer in order to prioritise your Data Governance Strategy.

Data Governance Mandated by Management

I meet with a lot of people (usually in the IT department) that have been tasked with governing the Enterprise data because their CEO read about it on an in-flight magazine, or because a consultant whispered something in the CEO’s ear about the benefits of being “data driven”. Filled with the excitement of what Deloitte have called the “4th Industrial Revolution” these CEO’s kick the initiative straight over the fence to their already over-burdened IT teams.

When we get to meet these teams, they’re understandably interested in the tools we have to offer.  Often there is a hope that a software product might deliver the ‘Silver Bullet’ to govern the sprawling mass of data at their disposal on its own. Unfortunately, as good as the current Data Governance software is, it won’t solve your problems unless you’ve got a good plan in place to clean up and manage the data yourself.

In order to succeed we need to:

  1. Narrow the Data Governance project scope to something achievable, and;
  2. Focus on Data Domains that will deliver “quick wins”

The best way to do this is to understand the strategic priorities of the organisation. First look for areas where Data is preventing the organisation from succeeding in these strategic objectives. Second, look for areas where better Data Management practices could reduce the time to achieve the objective or increase the return on the investment in this strategy.

Align Data Governance against Core Data Pain Points or Strategic Corporate Aims

Unless you have a well thought out plan, with the right ambitions and objectives aligned to the prevailing business strategy you’ll end up “boiling the ocean” and governing data for the sake of it. This is a very quick way to have a failed project and to suck all the enthusiasm out of the initiative. The answer to this is to try to align the goals of your organisation to the benefits of Data Governance, in order that you can solve problems that will matter and deliver a return on investment.

If you’re completely stuck for the type of use-case to look for, or you need inspiration and ideas on where to start, this article is for you.

Align Against Key Business Processes

Look into the business processes currently operating in your organisation. Focus your attention on those processes that are adversely impacted by poor data. Where is data the underlying bottleneck that’s preventing growth or causing costs to climb? Those core business processes that drive revenue are often the easiest to focus on, as investments in new tools for revenue generating processes are easiest to unlock.

Depending on the type of organisation you work for, the key business processes you might want to align against will change.

Business Process Examples that Benefit from Data Governance

  • A Manufacturing company might focus on data challenges they see in their manufacturing and production processes
  • Insurance firms have been hit by changes to their IFRS accounting standards recently – so they will be focused on improvements to the finance and reporting processes in the business to enable compliance with IFRS 17
  • An Education institution might want to re-think how it’s attracting new students, and how it’s reporting the successes of its Alumni. It might need to look at the Admissions Process in order to target the right student demographic
  • Customer Success and Satisfaction objectives are found across almost every organisation – look at Customer Lifecycle and Customer Relationship Management processes as these can almost always be improved with better data, or by building a Single Customer View
  • Retail and/or Manufacturing organisations might be working with “just-in-time” supply chain processes, which can be improved with better Data Management.
  • Financial services organisations are heavily regulated, with Anti-Money Laundering (AML) and Know-Your-Customer (KYC) processes heavily scrutinised to ensure these services are only used by legitimate customers and businesses
  • A Telecommunications company might want to use the vast data it has on customers to improve customer segmentation – improving its marketing processes through better customer and prospect data

Regardless of the industry you work in, Data Governance projects are often easiest to implement when aligned against a core business process for the organisation. The best place to start is on business processes to either increase revenue or reduce costs. 

If there is an initiative to re-engineer any of the core business processes this is a particularly good time to engage Data Governance – as you may be able to include your own requirements inside another corporate project and get signoff and budget approval simultaneously.

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Align Against Specific Corporate Data Pain Points

Sometimes the focus of Data Governance needs to go beyond one single business process. If you can identify cross-functional data pain points, then focus your first efforts against these issues. The way you set up your Data Governance team will differ, but that should be set against the business objectives and not based on the team you have available anyway.

How do you use this to prioritise data governance strategy? Start by digging around the business and asking questions of the teams doing their day jobs. Ask where their data-related pain might be.

Some common data questions to ask are below:

  • Do you have difficulty finding and understanding the data at your disposal?
    • Can they easily pull together meaningful reports?
    • Do their current reports give all the information they need to make good business decisions?
  • Do you have poor data quality?
    • Are users frustrated by the lack of suitable quality data to make decisions from?
    • Can they trust that their data is valid and in the right format?
    • Do you have any mechanism to check the underlying data quality at your disposal?
  • Are your reports aligned across business teams?
    • Are your teams arguing over the data they present to management?
  • Lack of automation.
    • How many business processes are manual in nature?
    • How well set up are you for systems change management?
  • Lack of end to end traceability for where your data comes from, and where it goes to
    • Have you been asked by management to explain how a report metric was calculated?
    • Are you concerned that you’re making decisions based on reports but don’t know how the numbers got there?
  • The need for Data Impact Assessments
    • Have you wanted to make a change to a source system, but been too afraid of breaking another system or report downstream?
    • Do you have a lot of technical debt and/or obsolete source systems but you’re unsure if you can switch these off without consequence?
  • Low productivity in Data Science teams
    • Do your Data Scientists waste time searching for what data is available, understanding where it comes from etc?
  • Compliance on acceptable use of data (i.e. data privacy) and management of data requests.
    • Will your organisation collect data from citizens of the EU? If so, you might have a GDPR obligation
    • Has your jurisdiction enacted its own Data Privacy legislation and you’re not sure how to deal with it?
  • Data trapped in silos
    • Are different business units comfortable sharing data across the organisation?
    • Is there any collaboration on data held by different teams?
    • Are you suffering because some departments have outdated records?
  • Poor customer engagement due to incomplete or inaccurate customer contact details (phone numbers, addresses, emails etc)
    • Do you have a call centre or marketing team that are wasting time chasing uncontactable leads?
    • Are you getting missed deliveries or struggling to find your customers?

Final thoughts on how to Prioritise your Data Governance Strategy

Hopefully this list will help narrow down the areas in the business where Data Governance or a Data Quality programme can make the most immediate impact. You might still have quite a long list of issues that you may want to fix, which is absolutely fine.

Remember that Data Governance is a marathon and not a sprint, the purpose here is for us to identify areas that will get an immediate benefit from better Data Governance and Management. If you go through the above lists and all of the issues are plaguing your business, you’ll need to prioritise the issues that have the biggest immediate impact.

Data Governance Strategy Assistance

If you need help working out how to prioritise Data Governance strategy in your organisation, we can help. Our experts will get you moving in the right direction. Just drop us a note in the form below as we’ll be in touch in no time.

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