This is the first article in an ongoing series on Data Governance sponsored by SAP.
The most important thing about data governance is to “start from where you are”. Most companies are just getting started on their data governance journeys. It can be hard to admit that your company is at data governance maturity level 0 or 1. But the most critical step is the first one – getting started.
We live in interesting times. Poor information security practices led to the release of a huge number of secret diplomatic cables to WikiLeaks. The Federal Aviation Administration admitted that registration information for as many as one-third of all private aircraft is out-of-date and inaccurate, forcing the FAA to cancel and re-register all civil aircraft.
And the private sector isn’t immune. TUI Travel, Europe’s largest tour operator, accepted the resignation of its CFO after restating its 2009 results to the tune of $185 million, blaming problems in integrating computer systems following a 2007 merger.
Sound familiar? Hopefully, your company doesn’t have any data governance “skeletons in the closet” like these. But if you hunt around a bit, you’ll undoubtedly find people in your business who’ll tell you about:
- decisions that were made based on reports with wrong or missing information,
- the real costs of duplicate data in your customer master database,
- cash flow being impacted because invoices were being sent to the wrong addresses,
- supplier master issues causing millions in avoidable costs in lost volume discounts
- the penalties for not complying with industry and government regulations on customer data and privacy,
- failure to comply with tax laws because of inaccurate billing information,
- information-heavy projects that run over time, or require length rework after go-live,
- decommissioning systems is nearly impossible because clear retention and destruction policies have not been defined,
- manual correction and alignment of content and documents takes time away from resources because these items aren’t singularly governed,
- IT staff spending a lot of time re-integrating data and dealing with data fire-drills because data service level agreements and fit-for-use levels have not been established and tracked.
If you talk to business owners across functional areas like R&D, Marketing & Sales, Finance, Operations, Human Resources, and Customer Service, you’ll fill up a small notebook with the stories about what not having a data governance organization in place is costing your company.
What exactly is “master data”?
Good question. Master data is the lifeblood of your company. It’s information that’s critical to the enterprise, including entities such as customers, products, employees, suppliers, and locations. It’s shared (or it should be) across applications, systems and databases, and across multiple business processes, functional areas, organizations, geographies and channels. It’s generally not anything that happens at a particular time, but instead a person, place or thing that changes slowly over time. Master data is not transactional, but it’s used by and linked to transactions.
And what is “data governance”?
Master data needs to be governed as you would any other critical asset in the enterprise – with diligence, formal processes and metrics. I’ve often said that if companies treated their cash and their inventory the way they treat their customer and product data, a lot of people in corporate America would be going to jail.
Jill Dyché, in Ten Mistakes to Avoid when Launching Your Data Governance Program, defined data governance as “the decision rights and policymaking for corporate data”.
Whenever you see the word “decision rights” and “policymaking” next to the words “corporate data”, you know that you’re dealing with an area that is more political than technological. But technology can be an enabler.
One of my favorite quotes is by Dean Kamen, the inventor and entrepreneur:
The technology is the easy part. Understanding what drives people – individuals, societies, what makes cultures clash – all of those questions are way, way harder to answer than how to solve any particular technical problem.
Simplifying today’s enterprise architectures
Today, most companies larger than $500 million – $1 billion in revenue:
- have grown through merger & acquisition activity,
- have a mixture of front office and back office suites and “best of breed” applications
- have some acquisitions and applications that are integrated and some that aren’t
- have created shadow IT organizations in individual Lines of Business in an effort to speed up results
- have created more complex processes for dealing with data issues, causing individual groups to creatively work around the processes
- have more diverse groups of workers with diverse experience (and preferences) for enabling software tools, like Excel
As a result, most companies suffer from significant data silos and data fragmentation – what I call the “Islands of Data” problem.
These data silos increase costs, hurt business and IT agility, and result in bad decisions being made throughout the enterprise (because of low quality, inaccurate, inconsistent data).
Master Data Management can solve the “Islands of Data” problem
Master Data Management (MDM) technology brings master data together in an MDM hub. In addition to the MDM hub itself, you’ll usually need:
- Data Integration (usually using Service-Oriented Architecture)
- Data Profiling and Data Quality
- Business Process and Business Rules Management
- Third Party Data Enrichment
- Technology to facilitate Data Governance
The MDM Hub centralizes master data, providing the much desired “Single Source of Truth”, streamlining business processes (which reduces costs and increases productivity and agility), and increasing revenue (through ability to support more targeted marketing and cross sell / up sell initiatives) and improving compliance.
But committing to MDM technology isn’t enough, unfortunately. Nor is it the first thing you need to figure out. In order to make the entire exercise work, we also need data governance.
So Why Do It? Why Govern Master Data?
The alternative – not governing it – is information chaos and anarchy. “A disaster of biblical proportions. Human sacrifice, dogs and cats living together… mass hysteria!” (from one of my favorite movies, Ghostbusters).
Seriously, why would we bring together master data from all over the enterprise, cleanse it, build golden records of customers, products, suppliers, etc. and not govern the decision-making process, result, and resulting analytics? That would be a value destruction exercise worthy of the Guinness Book of World Records.
Data governance is a critical success factor for master data management. MDM isn’t a “lights out operation”. Don’t try to do master data management without a data governance organization in place or under construction. You’ll wind up looking like this guy!