Today we are talking about ‘Building a Business Case for Master Data Management.’ Our customers have told us that this is not always an easy process since it requires calculating the cost of bad data to justify the pricing of potentially multiyear master data management project. And if you haven't attempted to calculate these costs, don’t worry you are not alone.
One research study recently surveyed over 500 businesses to determine the state of master data management maturity. Almost 50% of those surveyed indicated they have not even attempted to calculate the cost of bad data. And over 6% estimated that their costs are reaching well beyond $11 million.
And we have heard that implementing master data management isn’t always easy either. Experts tell us you can't just throw money or software at a master data problem. Organizations also need to budget for data governance, data stewardship and other process improvements. So today’s Webinar is intended to sort this all out and give some tips and advice about building a business case for master data management.
So let’s start off by asking how do companies even begin to quantify the cost of bad data, or to put a more positive spin on it, start calculating the potential value of master data management?
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The Cost of Bad Data
I think businesses have long had difficulty quantifying the cost of bad data other than to suffer the consequences of the problem. It’s clear that incorrect customer data leads to missed opportunities for cross-sell and up-sell of existing customers as well as inefficient methods of finding new customers and increases the chances that you are going to irritate all your customers through incorrect billing, poorly-aimed marketing and other problems.
Also with regulations such as HIPAA and Do Not Call lists in place, bad data could lead to regulatory violations, public embarrassment and even legal penalties. There is bad data, but there is also incompatible data. That’s another issue that master data management needs to address. Now the resistance is where the data certainly has meaning but is not universally understood across the organization. This confusion impedes the flow of information throughout the organization and generally raises the cost of doing business.
Master data management is about information about customers, products, suppliers, regions, hierarchies and involves business rules and other detailed aspects of the company’s business. And so what makes master data management different from other previous efforts to address bad data and resolve inconsistencies is that the way I see it, MDM does not treat information asset as static as I think other systems have in the past. MDM addresses the use of data by both business users and processes. So that way they can look at the business potential of MDM not just in terms of an IT project.
What is the wrong way to build a business case for master data management, or what flawed approaches are out there?
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Improving Data Quality
Well, I think that IT, in particular, and really the business side, have to look at what's happened in the past with information repositories and other efforts to try to improve data quality throughout an organization because this is not a new problem. People have been trying to address this for a long-long time.
And I think that one of the things that happened in the past is that some of those objectives tried, to use an expression, they tried to boil the ocean, and those attempts always fall short of expectations because you can't accomplish the whole thing in one fell swoop.
So I think that’s an important consideration right off the bat. Expectations have to be set appropriately for MDM projects by raising it up to the business level. Make it clear that the objective is to address business definitions and the accurate use of data and information. That should get the attention of the business people.