MDM Multi-Domain Planning And Challenges, by Mark Allen
Our latest article is by Mark Allen, the co-author of a Master Data Management in Practice – Achieving True Customer MDM. Read more 
Africom’s PROTEA Program
Our 300th article. After this year’s Gartner MDM Summit conference (May 4-6 in Los Angeles), Hub Designs sent a small team to a new client in South Africa called Africom. Read more
Gartner Projects MDM Software Revenue to Grow 14%
Bank Systems & Technology magazine had a good article by Penny Crosman today.
Gartner Research is predicting 14% growth over 2009 levels for master data management (MDM) software license revenues, to $1.5 billion.
Business drivers for adoption range from delivering revenue, service, agility and risk management improvement, cost reduction and integration simplification. John Radcliffe, a research vice president at Gartner, said ”Today, most organizations juggle multiple sets of business and data applications across corporate, regional and local systems. At the same time, customers are demanding faster and more complex responses from organizations, leading to an inconsistency that hinders the organization’s ability to measure and move within the market. With MDM, CIOs can create a unified view of existing data, leading to greater enterprise agility, simplified integration and, ultimately, improved profitability.”
Some interesting predictions were included in the Bank Systems & Technology article:
- From 2009 through 2014, MDM software markets will grow at a compound annual growth rate of 18%, from $1.3 billion to $2.9 billion.
- Gartner foresees a larger, more unified MDM software market reaching nearly $3 billion by 2014.
- By 2015, 10 percent of packaged MDM implementations will be delivered as software as a service in the public cloud (MDM today is typically implemented on-premises)
- Through 2015, 66 percent of organizations that initiate an MDM program will struggle to demonstrate the business value of MDM.
This is not because MDM can’t show sufficient business value. The Bank Systems & Technology article goes on to say “If IT departments initiate an MDM initiative, they often struggle to get the business on board and to demonstrate the business value of MDM, particularly if there are no business-process-oriented metrics and financial quantifications to define and measure success, Gartner analysts say.” (emphasis added)
At Hub Designs, like many other MDM practitioners, we’ve been saying for quite a while that the business needs to own the MDM initiative. This isn’t always a popular stance, particularly when the people bringing you into a particular client company are the IT people. But it’s the truth – if the business doesn’t own it, the business won’t feel ownership.
The article goes on to say “MDM needs to align with the business vision and strategy, and will require executive business sponsorship, strong involvement of business stakeholders and change management.”
“It’s not just an IT project. The business needs to take responsibility and be accountable for master data governance and stewardship,” says Radcliffe.
“Unless organizations take a holistic, business-driven approach to MDM, addressing governance and metrics requirements in particular, they risk having their MDM programs fail,” he says. “Internal politics won’t be brought under control without a governance framework, and without a metrics structure, there will be no way of objectively defining what success looks like and measuring whether or not it has been achieved.”
We couldn’t agree more. In our “Ten Best Practices” series this October, we specifically discussed that topic in Master Data Management Best Practice #10 – Use a Balanced, Holistic Approach, saying “This may be the most important best practice of all: use a balanced, holistic approach – addressing people, process, technology and information. Start with the people, politics and culture, and then move on to the data governance and stewardship processes, then the technology.”
The MDM initiatives that companies are taking on right now aren’t “too big to fail”, but they are too important to fail.
As a long-time MDM evangelist, who is used to describing MDM and data governance in such a way that people get excited about the change it can make for their companies, I think we need the types of economic and technological changes described in Penny Crosman’s article. Too many companies are lurching into the 21st century with the baggage of a late 90′s technology infrastructure holding them back. Faster, better decision-making, increased revenue and reduced costs, easier compliance and risk management, improved business and IT agility – these are things that aren’t going to come easily but they are worth it, and MDM and data governance are a big part of the answer for a lot of companies.
So hats off to Penny Crosman and her article in Bank Systems & Technology, and to John Radcliffe and Andrew White at Gartner Research for all the good work that they do.
Informatica MDM Tweet Jam
This is a transcript (lightly edited for brevity) of today’s Informatica MDM Tweet Jam. We hope you enjoyed the actual Tweet Jam and this transcript. If there were questions you didn’t get a chance to ask, please feel free to ask them via our web site’s Contact Us page.
Dan Power: Informatica MDM Tweet Jam like playing “stump Dan” – see if you can perplex, mystify and amaze me!
Dan Power: Actually, just kidding – want to have a good dialogue with everyone – would love to have a good MDM discussion.
Informatica Corp.: Right now! Join the #MDM TweetJam with @dan_power. 9am PT.
Dan Power: OK, the Tweet Jam is officially open!
Jakki Geiger: Dan, what are the most common concerns you hear about MDM?
Dan Power: IT people still seem concerned about how to involve the business and sell it to senior management.
Jakki Geiger: what advice do you give them?
Dan Power: IT seems to know that MDM is needed but sometimes can’t seem to get the business on board, and it can be hard to pitch to the C-Suite.
Dan Power: We advise building a compelling business case – getting outside help if needed – and recruiting internal business champions.
Jakki Geiger: What strategies to get the business on board have you seen work?
Dan Power: I wrote an article about that in a recent Information Management magazine and a blog article on Hub Designs Blog that accompanied it.
Jakki Geiger: We’ve seen IT successfully tie MDM to key strategic imperatives like improving cross-sell and up-sell=getting sales on board.
Ravi Shankar: One thing we have done to help IT is to quantify how much DQ issues can cut costs or increase revenue.
Dan Power: Getting the business on board means STARTING in the business – find out their pain points and recruit them to drive from Day 1.
Jakki Geiger: Others include onboarding channel partners onboard faster, which appeals to sales and channel operations.
Jakki Geiger: A huge driver has been regulatory compliance = appealing to those who gather data across the enterprise and create reports.
Ravi Shankar: I like what Charles Bloodworth of J&J said at Informatica World 2010 – “MDM is not just a project; it’s a discipline – a way of doing bus for us”.
Dan Power: Good points Jakki & Ravi – those are the pain points I’m talking about: increasing revenue / onboarding channel partners faster.
Jakki Geiger: One area I think is really going to take off is improving business processes = improve data to improve the process.
Jakki Geiger: One exec got buy in from exec team with “we need to manage our product supply chain and info supply chain equally efficiently”.
Ravi Shankar: Agreed – bus needs to be involved in MDM. Charles of J&J said bus involvement drove their MDM and data governance success.
Dan Power: That’s right – becomes a way of life – new discipline for the business – to have a golden copy of the data that they can trust.
Jakki Geiger: I agree with u. IT needs to understand what the business pains and strategic imperatives are, then evaluate “can MDM help?”
Dan Power: Product management and supply chain are just as fertile for most companies as customer data – so MDM is just getting started.
Dan Power: I’ve been talking to a lot of companies lately that have already done customer MDM and are now looking at doing product MDM.
Ravi Shankar: Product MDM: I see lot of demand for this from manufacturing companies. Just came from S. Korea – product MDM is hot.
Dan Power: Or even supplier MDM – in order to get global strategic sourcing initiatives off the ground, which can save millions of $.
Ravi Shankar: Customer MDM to product MDM – we’ve seen that with our own early customers – They leveraged the same Informatica platform.
Julie Hunt: How do you see MDM implementations evolving to take advantage of newer tech such as ‘cloud’?
Julie Hunt: And what advantages does the cloud offer to MDM solutions?
Dan Power: Good question, Julie – definitely see a movement towards the cloud – people don’t want to create tomorrow’s “legacy systems”.
Dan Power: So they increasingly are asking their vendors about cloud deployment options, even if they don’t rush to take advantage of them.
Dan Power: They want to know they’re available
Dan Power: To Julie’s Q about cloud, I think eventually we’ll see cloud deployments at lower cost than on-premise (particularly hardware).
Ravi Shankar: Let me outline 2 use cases we’ve seen @ InformaticaCorp.
Ravi Shankar: Use case 1: During peak times like holiday seasons, retailers can burst into cloud for additional capacity.
Ravi Shankar: Use case 2: Mktg mgrs can use self service tools to upload attendee list from event w/o having to bother IT.
Dan Power: The promise of cloud for me, is more flexibility as my business grows and if we have seasonal peaks and valleys of demand.
ocdqblog (Jim Harris): What do you say to companies that expected that from their data warehouse? How is MDM different from conformed dims?
Ravi Shankar: ocdqblog – welcome. Looking forward to a lively MDM discussion.
Dan Power: Good question, Jim. Most companies had unrealistic expectations from data warehouses, which ended up being expensive, read-only,
Dan Power: and updated infrequently. MDM gives them the capability to modify the data, publish to a DW, and manage complex hierarchies.
Dan Power: So to finish answering your question Jim, I think MDM offers more flexibility than the typical DW.
Dan Power: That’s why BI on top of MDM (or more likely, BI on top of a DW that draws data from an MDM) is so popular.
Ravi Shankar: MDM for DW – 90% of Informatica MDM customers use it for analytical use (in addition to operational).
ocdqblog (Jim Harris): Thanks Dan – Follow-up is do you see MDM as compliment or replacement for DW?
Dan Power: Definitely a compliment – fills void in the middle between trx systems and the DW – does things that neither can do to data.
Jakki Geiger: are you seeing this trend? Evolving beyond single customer view= visibility into 360 customer view w/products and channels, etc.
Dan Power: Yes, Jakki – people want more than a single view – they want multiple views on top of the single view.
Ravi Shankar: Siperian customers – We’re having a lively chat on MDM and data governance. Join in!
Ravi Shankar: Dan, what do you tell DW admins that DW provides their single view for enterprise?
Dan Power: I tell DW admins that most people in the enterprise aren’t completely happy with DW – that’s why there’s pain leading to MDM.
Jakki Geiger: Since the driver of MDM is the business, how are we getting master data into the hands of the business?
Dan Power: Good Q, Jakki – getting MDM data back into hands of the business should be built into the project – and the software platform.
Ravi Shankar: Compliance is driven out of DW – you need MDM for accurate compliance reports – Do you agree?
Dan Power: Yes, Ravi – Garbage in, Garbage out – you need quality data from the MDM system to feed into the data warehouse.
Julie Hunt: So we must advocate value of data governance as well as value of MDM with business, senior management?
Dan Power: I tell people to think of their initiative as a data governance project that happens to involve #MDM technology.
Dan Power: Not an #MDM technology project that requires data governance.
Dan Power: And to start the data governance piece about 6 months before the technology piece, if possible.
Julie Hunt: The importance of data quality = another layer to be advocated to the business and to management – show them the impact on outcomes.
Jakki Geiger: MDM is like a Ferrari. If you don’t use DQ with MDM, it’s like putting regular gas in Ferrari=sub optimal performance.
Dan Power: I’ve seen people try to do MDM without data quality – and it’s a disaster, like trying to run a submarine on dry land!
Dan Power: The fact is that #MDM and data quality are linked, just as #MDM and data governance are linked.
Ravi Shankar: Should data quality be integrated within #MDM?
Dan Power: Good question, Ravi – I’ve seen it both ways – a data quality engine integrated with the MDM platform or separate, both can work as long as the data quality tool is robust and the integration is solid, shouldn’t matter.
Dan Power: Most MDM platform vendors are not equally good at developing data quality tools – Informatica is one of the few that is.
Julie Hunt: How much does corporate culture impact success/failure of projects for #MDM, data governance etc.?
Dan Power: Great Q – corporate culture is a huge impact on success because data governance drives MDM and requires a lot of change mgt. So spend a lot of time on org. change in the data governance side of the #MDM initiative in order to be successful.
Ravi Shankar: Heard a customer say – “Don’t overdo data governance – do just what’s necessary” Do you agree?
Dan Power: I’d agree not to go overboard on data governance – balanced approach that’s right for your co. just enough to get the job done. Too much data governance can be worse than not enough – can be bureaucratic – the “data governance police”.
Ravi Shankar: Data governance applies to all data, but I hear that in MDM context a lot. Do you hear “master data governance” for MDM?
Jakki Geiger: Some argue shouldn’t call it data governance because the -ve connotation of “governance” thoughts?
Dan Power: I actually like that phrase – master data governance – makes it more clear and precise what we’re talking about
Dan Power: Because otherwise, data governance organization can get drawn into all kinds of weird things not related to master data
Dan Power: We need to recognized that data governance is (a) political, (b) controversial, (c) going to have an enforcement side.
Ravi Shankar: Now, do orgs do data governance first before implementing MDM or after they select an MDM product?
Dan Power: So in some ways, I actually like the term “data government” better – makes it more explicit what we’re talking about.
Dan Power: And it reminds people that we’re talking about governing the enterprise’s core master data – just like we govern other key assets.
Jakki Geiger: I think the challenge is that we’re still in the process of understanding that data is a strategic asset.
Dan Power: It’s ideal if they can start data governance before even selecting a product – so that the data governance org. can help w/ the selection process.
Ravi Shankar: Dan wrote an excellent whitepaper – “When Data Governance Turns Bureaucratic” – you can download it from http://bit.ly/ck2Gw8.
Dan Power: Truly competitive 21st century companies not only understand that data is a strategic asset, it’s how they run their business.
Dan Power: Forward looking businesses like Google, Amazon, Century 21, eBay, etc. realize that the data IS their business!
Jakki Geiger: “Data as strategic asset” is a fairly new concept. Visionaries recognize need 4 scale and intelligence=harnessing & analyzing data.
Dan Power: That was a fun white paper to write – looking forward to doing another one with the great folks at Informatica again soon!
Jakki Geiger: What I liked about Dan’s WP was the discussion around stopping the problem of data quality at the source.
Seth Grimes: Is data governance also (d) useful on balance and (e) capable of delivering ROI?
Dan Power: Yes, of course – or people wouldn’t be doing it. You can’t bring together massive amounts of data in an MDM hub and not have some type of governance framework in place. And if there was no ROI, it wouldn’t be happening.
Dan Power: I’m pretty familiar with Oracle’s data governance program, and for a huge company, it’s not real expensive.
Ravi Shankar: Welcome to #INFATJ – good data governance question.
Ravi Shankar: Successful Informatica MDM customers like J&J, Merrill, and numerous others have had strong global data governance orgs.
Ravi Shankar: Data is a key asset that many firms make a lot of money out of it – Bloomberg for e.g.
Ray Wang: RT @Ravi_Shankar_: Data is a key asset that many firms make a lot of money out of it – Bloomberg for e.g.
Dan Power: Good example with Bloomberg – welcome Ray!
Ravi Shankar: @rwang0 thx for the RT
Jakki Geiger: Can you create a career out of MDM? Many of our customers have extended MDM to address more and more issues in their orgs.
Dan Power: Good Q, Jakki – u can create a career out of it, I have for the last 6 years, but you’ve got to really have this in your blood
Ravi Shankar: Within Informatica customers, we’ve seen careers of several people take off b/c of successful #MDM data governance.
Julie Hunt: Thanks for great tweet jam!
Jakki Geiger: Thank you for participating! Looking forward to next time. Good luck to you all!
Dan Power: Thanks for joining us today – hope you enjoyed it! Check out the Hub Designs Blog at http://blog.hubdesigns.com.
Ravi Shankar: Thx for your insightful discussion and advice on #MDM data governance. Hope you all enjoyed it. Until next time!
Dan Power: This is Dan Power, signing off – have a great day everyone!
Organizational Readiness for MDM
The Hub Designs Blog welcomes a great guest post by Rob DuMoulin, an information architect with more than 26 years of IT experience, specializing in master data management, database administration and design, and business intelligence. Rob wrote a popular 5-part series called Data Profiling for All the Right Reasons, and his first article was Calendar and MDM. He brings a fresh perspective from the front lines of MDM.
Is my organization ready for Master Data Management (MDM)?
Assuming you’re confident that you can answer the question “What is MDM?” and can successfully debate “what MDM is not” with an unseasoned Data Architect, the title question is next in your readiness assessment progression.
While the question itself seems simplistic, the answer requires examination of many aspects of business operations as well as data management and IT maturity.
MDM projects focused on creating “IT solutions” to “IT problems” fail to provide true end-to-end life-cycle management, which is the key to maximizing business value. Below are questions to consider when evaluating your business readiness for MDM success. Consider the Core Subject Item to be the business object that you are considering mastering, such as Product, Customer, Raw Materials, Party, etc.
- MDM success relies on understanding the current and desired state of business operations. Identifying and involving business champions and business sponsors is the only credible method of defining information and process gaps which lead to a true business case. Are your business sponsors fully engaged?
- Is there a Data Governance strategy in place already that can be used to manage business information or do we need to define this from scratch?
- Is the business case defined and does it directly tie to the project success criteria?
- What is the Core Subject Item of your MDM? Have you validated that business owners, Finance, Customers, Marketing, Legal, and IT all have the same perspectives, including the same granularity and the same definitions? If not, how will you resolve the differences?
- What are the target volumetrics for the Core Subject Item based on current and anticipated business needs?
- Is there a single Taxonomy for your Core Subject Item where all objects map to one and only one leaf node?
- Have you created an as-is information model?
- Have you created a to-be information model that business and IT sponsors agree on?
- Would you be able to define a conceptual data model to describe the various high-level information types targeted for the MDM system?
- In the case of product MDM, can business users define the difference between a version and a revision, if there is one? How do they manage each?
- Is there unstructured data you need to include?
- How are object related to each other? Are some products cross-sellable, up-sellable, substitutions, or versions of others? Do some contacts household with others?
- What rules and restrictions do you have to enforce in the MDM system?
- What additional information must be collected to allow other downstream information consumers to apply their business rules and restrictions?
- What is the current lifecycle process used by the business to manage its Core Subject Items? What is the proposed new process to do lifecycle management?
- What are the technical constraints your organization will be facing?
These are just a few of the points to consider when evaluating how well your business is prepared to undertake a successful MDM project. While you do not necessarily need to answer all of them before you start your project, consider making them a milestone before full budget is allocated because it makes planning much more accurate.
Lastly, keep in mind that knowledge and experience go a long way. Those who have gone through these projects before can attest to importance of laying down a solid foundation to build upon.
Speaking at SAP Virtual Trade Show
Hub Designs is an associate member of SAP’s alliance program, and on September 23rd, Dan Power from Hub Designs will be speaking at an SAP virtual trade show being put on by SearchSAP.com and TechTarget.
This free virtual seminar is focused on best practices for maximizing SAP performance. The day long virtual event features expert presentations, live panels and expert networking opportunities to help you make the most of your SAP environment, and will cover the hottest topics in SAP right now – including business intelligence, virtualization, master data management and mobile technologies. You’ll learn tips that you can put into practice immediately and you’ll get unbiased advice for long-term strategy development. At this unique online event, go beyond the hype and get insight into the latest technologies and best practices you can use to improve operational efficiency in SAP environments.
Dan Power’s session will be at 1:30 pm EDT, and will cover topics such as:
- Definitions of master data management, data governance and data quality
- The five essential elements of MDM
- Why companies are doing MDM and what this means to you
- Getting started on an MDM roadmap
- Is your organization ready?
- Creating the MDM business case
- MDM software selection
- Some important best practices
For more information, please visit http://searchsap.techtarget.com/feature/Getting-the-most-out-of-your-SAP-environment, and to register, please click here.
Our MDM Strategy Offerings
Recently, I put together an overview of Hub Designs’ MDM strategy offerings for a potential client. Here’s a recap.
Education
- Based on our popular “Best Practices in MDM and Data Governance” speaking engagements, presented at Oracle OpenWorld and the Oracle Applications Users Group COLLABORATE conference.
- Our workshops get business & IT professionals up to speed quickly
- You get access to the best MDM experts, and can bring your business people into the process early
Roadmap
- Based on Hub Designs’ MDM framework
- Defines where you are now, where you want to be, and over what time period
- Looks at master data management, data integration, data quality, and data governance over time
Readiness Assessment
- Looks at issues relating to politics & culture
- Performs skills assessment on people who may need training
- Examines process issues, outlining where business processes need improvement or redesign
- Investigates technology issues, detailing where essential components are not present or not able to support your upcoming MDM initiative
- Performs data profiling to discover data quality issues
Business Case
- Captures business requirements
- Identifies stakeholders and select metrics
- Baselines current performance
- Negotiates expected benefits
- Converts to financial results
- Develops total cost of ownership
- Calculates hard-dollar ROI
Software Selection
- Develops selection criteria
- Creates a weighted vendor scoring model
- Includes functionality, technology, viability, costs, services and vision
- Develops demo scripts for vendors to follow and sample data sets to give them
- Manages proof of concept (POC) process
- Assists in evaluating POC performance and scoring vendors
These engagements range in length from one to twelve months, with teams varying from two to ten people, depending on the size of the company, the number of domains of master data involved, and the complexity of the politics and legacy systems in the enterprise.
If you’re interested in discussing an MDM strategy engagement like this, please contact Hub Designs at http://www.hubdesigns.com/contact_us.html. Or if you have comments on the above approaches, please let us know by commenting here.
Philosophy of MDM
My philosophy of MDM is simple: all things being equal, enter and manage master data in its own repository or hub, and pay the same attention to the organization and business processes for creating, distributing, updating and retiring master data that you do for other types of data within the enterprise.
You’d be amazed how often that simple statement confounds people though. They want to enter master data in their ERP or CRM system, and then synchronize it over to the MDM hub. Or they’d like to somehow do without an organization to manage their master data for the enterprise. Or they’re willing to concede the need for a data governance group, but don’t think that group will need any formal processes or technology to help orchestrate their work or facilitate it and improve their productivity.
Even though the link between data quality tools and master data management is well established, I sometimes still see people try to do MDM projects without using data quality technology. And even though synchronizing the high quality master data available in the hub should be a high priority, people (typically for cost reasons) still try to skimp on integration technology and try to get by with only the most basic ETL tools.
One of the most popular articles we’ve had here on the Hub Designs Blog was the Five Essential Elements of MDM, in which I laid out what I thought were the most important related areas of technology. In it, I included the MDM hub itself, of course, and also data quality, data integration, middleware, third party content and data governance (which of course, is not really technology, but needs to be included because it too is so often forgotten).
So getting back to the focus of this article, my philosophy of MDM is to have all of the essential elements, to have a sound vision and strategy for MDM, a strong business case based on metrics, to create a governance framework and organization to carry it out, to design governance processes, and then (last but not least) to implement technology to facilitate the governance needed to support the enterprise’s master data requirements.
So often today, we see organizations taking a technology-driven approach, or leaving out important parts of the above approach. Have you thought your MDM initiative all the way through?
Recent eLearning Curve Webinar
Hub Designs recently hosted a 30 minute webinar on “Best Practices in MDM and Data Governance with Dan Power”, in concert with our friends at eLearning Curve and Information Management magazine.
To download the replay of the webinar (with audio), please go to http://bit.ly/hub-designs-webinar. To download just the slides, please go to http://bit.ly/mdm-best-practices and click “Download”.
For the “When Data Governance Turns Bureaucratic” white paper mentioned in the presentation, go to http://bit.ly/data-governance. Scroll to and click the link at the end of that article.
Thanks for attending the webinar (or the replay). We hope you found it valuable!
Hidden Costs of Duplicate Customer Data
A client asked me last week about what rate of duplicate data was “normal” in customer master data.
My initial answer was that, among companies that don’t have any formal master data management, data governance or data quality initiatives in place, duplication rates of 10%-30% (or more) are not uncommon.
When I was at D&B, we used to routinely see that level of duplication in client’s customer files.
In a study in the healthcare field, Children’s Medical Center Dallas engaged an outside firm to help clean up their duplicate data:
“Solving both the current and future problems around duplicate records helped Children’s improve the quality of patient care and increase physician acceptance of the new EHR. The duplicate record rate was initially reduced from 22.0% to 0.2% and five years later it remains an exceptionally low 0.14%. The 5 FTEs initially tasked with resolving duplicate records have been reduced to less than 1 FTE.”
“For the Children’s Medical Center, the results were heartening, not only from a care delivery standpoint but also because of the significant cost-savings that can be realized. A study conducted on Children’s data showed that on average, a duplicate medical record costs the organization more than $96.”
So it is possible to get the duplication rate down to really low levels through careful analysis and the application of the right tools, as part of an ongoing data governance program. Even the hospital above (and hospitals are usually not mentioned as practitioners of best practices) was able to maintain a duplication rate of only 0.14% after 5 years.
And there are very real costs to not de-duplicating your customer data. Depending on the functional area (marketing, sales, finance, customer service, etc.) and the business activities you undertake, high levels of duplicate customer data can:
- annoy customers or undermine their confidence in your company,
- increase mailing costs,
- cause hundreds of hours of manual reconciliation of data,
- increase resistance to implementation of new systems,
- result in multiple sales people, sales teams or collectors calling on the same customer,
- etc.
The best studies I’ve seen of the cost of duplicate data have been in the healthcare industry. One study I saw said:
“According to Just Associates, the direct cost of leaving duplicates in an Master Patient Index database is anywhere from $20 per duplicate to several hundred dollars. The lower cost reflects the organization’s labor and supply costs to identify and fix the record while the higher expense reflects the costs of repeated diagnostic tests done on a patient whose previous medical records could not be located.
The American Health Information Management Association (AHIMA) estimates that it costs between $10 and $20 per pair of duplicates to reconcile the records. If the records aren’t reconciled, however, the costs are even higher.”
Here are three more case studies backing up the range I quoted of 10%-30%:
- Once the analysis was complete, Sentara discovered they had a significant duplication rate, over 18%. They had attempted to address the duplication rate in the past through a remediation process, but due to either technology issues or because the cost of merging and cleaning up the duplicates across their many different systems was too high, they had not yet successfully reduced their duplication rate. Source: Initiate Systems success story
- Emerson Process Management faced a tremendous challenge four years ago in getting its CRM data in order: There were potentially 400 different master records for each customer, based on different locations or different functions associated with the client. “You have to begin to think about a customer as an organization you do business with that has a set of addresses tied to it,” says Nancy Rybeck, the data warehouse architect at Emerson who took charge of the cleanup. Working with Group 1, Rybeck analyzed the customer records for similarities and connections using everything from postal standards to D&B data, and managed to eliminate the 75 percent site-duplication rate the company suffered in its data. “That’s going to ripple through everything,” she says. Source: DestinationCRM.com
- Problem: Number of duplicate records: 20.9% of Utah Statewide Immunization Information System records. Impact of Problem: Difficult to find patients in system—key barrier to provider participation, risk of over-immunization—unable to find reliable patient record, cost of unnecessary immunizations, risk of adverse effects on patients. Source: health.utah.gov.
And here’s a good quote from a white paper titled “Data Quality and the Bottom Line” by The Data Warehousing Institute:
“Peter Harvey, CEO of Intellidyn, a marketing analytics firm, says that when his firm audits recently ‘cleaned’ customer files from clients, it finds that 5 percent of the file contains duplicate records. The duplication rate for untouched customer files can be 20 percent or more.”
Every organization will need its own metrics, but left unchecked, the duplication problem is a hidden cost that drags at your company, slowing down your processes and making your analyses less reliable.
If your sales analysis reports can’t be sure that there’s one and only one record for each of your largest customers, then the sales figures for those customers are probably not right. So the entire report becomes suspect at that point.
I’d like to end with a great quote on data quality by Ken Orr from the Cutter Consortium in “The Good, The Bad, and The Data Quality”:
“Ultimately, poor data quality is like dirt on the windshield. You may be able to drive for a long time with slowly degrading vision, but at some point, you either have to stop and clear the windshield or risk everything.”
Please let us know what you think by commenting here. We’re interested in hearing your thoughts on data quality and the issue of customer data duplication.
Webinar with Initiate Systems
“Master Data Management: The Sliding Scale Between Build and Buy”
Replay of the webinar with Dan Power and Marty Moseley
Please join industry experts Dan Power, Founder and President, Hub Solutions, and Marty Moseley, CTO, Initiate Systems, for this webinar where we’ll outline the best practices that have evolved to support organizations in making the critical “build vs. buy” decision.
Master data management (MDM) transforms data integration and business processes. Many organizations are exploring an MDM solution and will eventually have to answer the build vs. buy question. The combination of build and buy for MDM depends on the individual organization’s circumstances, goals and objectives. As MDM has evolved, so have the best practices for considering how much should be built and how much should be bought.
Some key considerations include:
- What are your current data volumes? How will they change in the near and distant future?
- Are customer relationships one-dimensional? Are you concerned with multiple domains of data and managing the corresponding hierarchies?
- Will you implement Web services? How will they be used?
- Do you augment your internal data with information from external vendors?
- What are the time, budget and resource limitations?
- Is MDM intended to eventually provide an enterprise data platform?
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Solid Strategies for Surviving a Slowdown (Part 2)
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Editor’s Note: This is Part 2 of a two-part series written by Jim Walker from Initiate Systems. You can find Part 1 here.
Here are the rest of the six proven business strategies fueled by real-time, accurate and complete customer data in a master data management (MDM) system:
Use customer service to retain customers and cut costs: Acquiring customers is expensive, and losing them is even more costly. Better customer service will improve customer satisfaction and retention and reduce your costs. Empowering your touch points with a complete and accurate view of each of your customers and their relationships provides a clear picture to both your customer and your representatives. Automated collection and presentation of complete customer information to service professionals reduces search times and has a positive effect on call waiting times, increasing productivity and reducing costs. It allows you to never ask a customer to repeat themselves. Accurate composite customer data enables web self-service applications with a single view of multiple accounts to empower your visitors to help themselves.
Be bold, change the playing field; buy a competitor: A downturn will have an indelible effect on many industries as valuations decrease and otherwise impossible consolidations becomes plausible. Historically, the most successful mergers are made in downturns. According to Harvard Business Review, “downturn mergers generate about 15% more value, as measured by total shareholder return, than boom-time mergers.” However, capital is sparse and careful due diligence of a potential target is imperative, as their problems will become yours if the merger is completed. Merger analysis should include careful consideration of customers and any potential risks. This knowledge will help you make sense of a bold move during a tenuous time.
Regulations never go away: An economic downturn does not delay compliance with government regulations. In fact as a slide continues, governments look to increase regulation to prevent future issues. Compliance in a recession is imperative so that you avoid costly fines that may have a devastating effect on your financial picture.
Obtaining and delivering accurate, comprehensive customer data is at the foundation of all six of these strategies. Your level of success will depend on the quality of the data that feeds each of these business improvements. An accurate data foundation allows you to deliver on fixing short-term pains, while setting up long-term gains. A new breed of data management technology has evolved to meet these challenges.
Master data management enables delivery of these valuable strategies and objectives. It provides complete, accurate customer views and valuable hierarchy management to your customer data. Reliability and effectiveness of this data is determined by its accuracy and ability to reflect real world conditions in any situation where that data is used.
Jim Walker is a Senior Manager, Field Marketing for Initiate Systems, a leading provider of master data management (MDM) solutions. Jim specializes in researching and writing on the effects of MDM on the enterprise. He has held numerous marketing positions at enterprise software companies, focusing on data management and security. He has also designed and implemented large scale enterprise systems as a technology consultant. Jim holds a MBA in e-commerce from Carnegie Mellon University and a BS in Computer Engineering form the University of Illinois at Chicago. He can be reached at jwalker@initiate.com.
Click here for Part 1 of this series.
Solid Strategies for Surviving a Slowdown (Part 1)
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Editor’s Note: This is Part 1 of a two-part series written by Jim Walker from Initiate Systems. You can find Part 2 here.
As uncertainty accelerates, some companies not only survive, they prepare themselves to thrive during the subsequent recovery. Even in the best economic conditions, organizations look to do more with less, and in a downturn, they are forced to manage things even more tightly. Added market pressures force tough decisions. Less money results in contraction and consolidation of vital resources. Many companies turn to their most valuable asset, their customer data, to forecast and define their future.
A downturn opens rare opportunities to outmaneuver rivals by reducing costs and increasing efficiencies. Reliable and accurate customer data can provide valuable insight into changing market dynamics. Organizations that analyze their data to identify and avoid fraudulent and high-risk accounts can also reduce operating costs. Many use customer data to build and strengthen relationships and identify revenue opportunities. High quality, reliable customer data allows them to spot opportunities across lines of business or properly align a sales force with an up-to-date and accurate customer hierarchy. They can find pricing discount opportunities for customers or identify commissions over-payments.
The potential gain is substantial; however, the effectiveness of these initiatives is only as good as the underlying data that drives the results. Here are six proven business strategies that are fueled by real-time, accurate and complete customer data that master data management (MDM) can provide your organization.
Incent customers through improved pricing: Purchasing behavior changes dramatically in a recession. Consumers increasingly opt for lower-priced alternatives to their usual purchases. Customer upgrades and extensions not only improve your top line, they also increase customer retention and can be completed with much less cost. Knowing your customer will present pricing discounts or up-sale opportunities. However, complex business relationships, such a subsidiary and parent structure, keep you from obtaining a clear picture. Overlaying a trusted hierarchical structure on your customer data will provide an accurate view of rolled-up sales and introduce appropriate pricing discounts to garner new business in difficult times.
Never double pay a commission: Geographies or strategic sales territories sometimes overlap for sales executives. Managing this overlap for hundreds of sales resources across complex business relationships is difficult at best, and the potential overpayment of commissions is high. Identifying and removing the overlap requires you to have a clear picture of the customer and their organizational hierarchy. For instance, if two sales resources are selling into two subsidiaries of the same company, you may have missed an opportunity to roll up the sales and pay a single commission. Identifying and eliminating redundant commissions reduces operating costs.
Spend the right time on the right customers: Organizations are concerned for their own well-being as well as their customers’ and prospects’. Identifying and mitigating customer risk requires complete insight into accurate customer information, license positions and relationships. Overlaying a trusted hierarchical structure on customer data will allow you to roll up risk calculations so that you can analyze and identify a master account and apply appropriate risk strategies. This will help you understand your best customers and make strategic plans to maximize revenues associated to them. It will help you spend the right amount of time with the right customers.
Jim Walker is a Senior Manager, Field Marketing for Initiate Systems, a leading provider of master data management (MDM) solutions. Jim specializes in researching and writing on the effects of MDM on the enterprise. He has held numerous marketing positions at enterprise software companies, focusing on data management and security. He has also designed and implemented large scale enterprise systems as a technology consultant. Jim holds a MBA in e-commerce from Carnegie Mellon University and a BS in Computer Engineering form the University of Illinois at Chicago. He can be reached at jwalker@initiate.com.
Click here for Part 2 of this series.
2009 Predictions
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In November, I attended Gartner’s second MDM Summit conference in Chicago.
One of the topics people were talking about at that conference was how well the Master Data Management market would fare in an economic downturn.
Certainly, companies that were just “testing the waters” on MDM may cancel or slow down their initiatives, and anyone making the front pages or the nightly news (and not in a good way) is probably going to see some disruption to their Master Data Management efforts.
But I’ve been pleasantly surprised by how much interest and activity we’ve seen, particularly since 2009 started.
Friends in the MDM space report getting a slew of new opportunities recently, especially in the healthcare and pharmaceutical industries. Industries like that are doing relatively well, and even in affected industries like retail, some companies are “swimming against the tide” and investing into the downturn, looking to take market share and revenue from their competition who are cutting investments and going into hibernation mode.
Barney Beal on SearchDataManagement.com described the picture at BJ’s Wholesale Club:
[John Polizzi, senior vice president and CIO] “Our plan was not an investment in a master data management (MDM) system, or an ERP implementation, or a point of sale (POS), but rather all of them — and more. BJ’s is embarking on a five-year transformation of its IT infrastructure and systems.”
Philip Lay, managing director of TCG Advisors, who spoke at the Gartner conference, said “now is the time to buck conventional wisdom and ‘think like a contrarian’ when it comes to MDM.” Lay advised the attendees “the key to making a successful business case for MDM is to tie MDM to specific, broken business processes” and quantify that impact.
I wrote an article for DM Review on “Easing into Master Data Management” which describes how to get started by building a data governance program first, with existing resources and applications, and tackling data quality and data integration as predecessor steps to MDM.
Certainly, one of the classic drivers for MDM has always been reducing costs – and that’s even more important in a recession (look for a guest post on this topic in a few days from Ravi Shankar at Siperian).
But even more important is to grow the “top line” – to increase revenue and pull customers away from your competitors, through better information, better customer service, better products, better pricing, you name it.
In 2009, I predict the MDM market will be affected somewhat by the recession, but it will still be one of the fastest-growing software segments, as Gartner has been predicting too.
But let’s tap into YOUR collective intelligence – what do you think? Please comment here or on the MDM Community.
Top Posts for 2008
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I thought I’d recap our “Top 10 blog posts for 2008″ for anyone who might have missed some of them.
- Ten Best Practices for Master Data Management – by far our most popular post (with thanks to MDMSource.com for featuring it)
- Our MDM Partnership Strategy — discusses our vendor-neutral strategy for partnering with the MDM hub vendors
- Different Styles of MDM Hub — outlines differences between Registry, Transaction and Hybrid style hubs
- MDM Business Case Creation & ROI Analysis — links to a “one-pager” on our Business Case Creation & ROI Analysis service
- How Master Data Management is Similar to ERP – talks about the similarities in organizational disciplines and processes between ERP and MDM
- Metadata and Master Data Management — discusses what metadata is and different approaches to managing it in the context of MDM
- Critical Data Quality Questions – outlines four “hard questions” relating to data quality and MDM and suggests ways to answer them
- Building a Data Governance Organization – five points to keep in mind as you build your data governance organization
- Five Essential Elements of MDM — technology (hub, integration, data quality, external content) and organization/process (data governance) required to succeed with MDM
- Importance of Integration to MDM — piece urging MDM project champions to think about the role and importance of data integration
These have all been read 100-800 times in 2008. If you’re interested in my articles in DM Review and speaking engagements, they’re outlined on the Publications page of our web site. If you use Twitter, you can follow me here.
Thank you all for reading this blog!
Day 1 of Gartner MDM Summit
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First, I want to encourage everyone who reads this blog to join the free MDM Community at http://mdmcommunity.ning.com.
I’m in Chicago attending Gartner’s second Master Data Management Summit.
I didn’t make it to last year’s event in Hollywood, Florida, but I’m attending this one to investigate exhibiting at next year’s event, and to keep my finger on how the MDM market is doing in the current economic climate.
The first keynote session, by John Radcliffe and Andrew White, was on “Where is MDM Going Over the Next Five Years”. Their lead-in was that MDM is more relevant than ever in today’s econonic meltdown.
Projects will need to offer incremental value, without being too tactical. Developing a data stewardship culture doesn’t hit the capital expense budget. They recommended people focus on the “hard benefits”, efficiencies and compliance requirements, while preparing for the (eventual) upturn. And they strongly suggested developing the metrics to quantify and communicate the value of your MDM program.
They presented the “MDM Hype Report Card”, saying that the hype cycle is at or near its peak. The links between MDM, business process management, service-oriented architecture and business intelligence remain unclear to many users. And external service providers (in their opinion) are finally starting to add some value to MDM programs. And they predicted that by 2012, 70% of SOA projects will fail to yield expected results unless they include Master Data Management.
Andrew and John covered Gartner’s “Seven Building Blocks”: vision, strategy, metrics, governance, organization, process and technology, and recommended a business-driven, holistic approach to MDM, which I’ve been recommending for a couple of years now.
I also really enjoyed “Building the Business Case for MDM” by Michael Smith. It was an engaging but thorough review of Gartner’s recommended steps for creating a thorough business case for your MDM initiative.
After covering the process for developing an effective business case, Michael Smith discussed how metrics can be used to quantify the benefits, and how to use the business case to manage the initiative through the entire lifecycle.
The main argument for taking the time to create a detailed business case is the fact that without one, IT projects in general seem to have only a 50% success rate, but when the time to create a robust business case is invested, the success rate goes up to as high as 75%. If your total project budget is high enough, that higher success rate can translate into some serious savings.
I attended the IBM session highlighting Nationwide’s “Transformation to a Customer-Centric Organization”, and I really enjoyed the remarks by Tara Paider, their Lead Architect for Customer Information Management.
The attendees and exhibitors I spoke to in the Solution Showcase all commented on the power of Gartner’s brand and that the 1st day of the conference was well-attended and full of good content.
I’m a big fan of Aaron Zornes at The MDM Institute and the MDM Summit conference he puts on twice a year in the U.S. with SourceMedia. I’ve attended all six events they’ve done together in the last three years, and have spoken at five of them.
But I see the appeal of the Gartner MDM event as well. At this stage in the development of Master Data Management, competition is a good thing – between software vendors, services firms, and conferences. It makes us all better to have another entry in the market to measure ourselves against and to strive to outdo.
If you’re attending as well, I’d love to hear your comments here.
Building the Business Case (Part 4) – Gaining Alignment
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In the previous installments of this series, we covered three key drivers for building your business case: Risk Management, Cost Reduction, and Revenue Growth.
Now, we’ll review the importance of and the process for gaining organizational alignment with your strategy.
When you’re building support for your business case, it’s critical to gain alignment at all levels of the organization throughout the whole process. Making the case for an information management strategy cannot rest with only one executive. And it can’t be the brainchild of IT only, or lack executive sponsorship altogether.
You need as many areas aligned as possible. More than likely, a comprehensive information management strategy needs to consider all of the data streams across the enterprise (at some point), and will therefore be fairly time and resource intensive.
If you take a three-pronged approach to gaining alignment, then you’re well on your way to obtaining approval to implement your strategy:
(1) Get front-line employees and customers to identify the problems with the data. You should have been gathering their feedback and facts as you built your case. So when you can readily articulate that customers are frustrated with your company, or that your employees are performing workarounds, rework, or aren’t as effective as they could be, then you’ve got your “first-level buy in”.
(2) You need their individual management teams to agree that these issues exist. They need to agree that they’d be more effective in achieving their goals if they had a solution to their information problems. And most importantly, if you can get them to agree that an information management strategy should be a priority and they support the contents of the business case (which shouldn’t be too difficult if you had their support during the development of the business case), then these folks become your best allies.
(3) Have those management teams bring this message forward to their leadership. When the leaders hear, directly from their own people, that they should understand and support the business case, then your business case has achieved a level of credibility you wouldn’t have gained on your own. And your role then becomes one of subject matter expert, business case developer, and valued business partner.
I do recommend getting several executives aligned to the strategy. Because of the size of the undertaking, you’ll need several leaders to prioritize and support the effort. Providing headcount, funding and the time to deliver on the plan will be crucial from these leaders.
Once again, the more compelling your business case (whether it’s to comply with regulations, reduce costs or improve revenues), the more chance you’ll have in gaining attention and alignment.
Which brings us to the final point: set up your program so that small wins are achieved throughout.
Whether you need to set up prototypes, pilots, or small projects while you are driving the entire strategy over time (probably several years), you need to prove results. Otherwise, no matter how great your plan, the organization will lose interest along the way.
So, if you set expectations appropriately, have a good measurement plan in place, and keep communicating constantly with all levels of the organization, then you’ve got a great chance of succeeding!
Building the Business Case (Part 3) – Revenue Growth
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Business Growth is really the heart of your business case. If you can identify how an Information Management strategy will enable your company’s growth, then your chances of success go way up!
This topic may be a little more difficult to document, but most executives will not argue with you if you can validate your premises.
Start by looking at existing strategic initiatives, then meet with the business areas responsible for those results and see if issues with the current corporate data could prevent them from achieving their goals.
Let’s look at the types of growth enablers you might consider:
• Mergers & Acquisitions
• Customer Service / Experience
• Customer Targeting
• Customer Coverage
• Forecasting / Planning / Modeling / Reporting
• Product / Service Offering
• Channel Strategies
• International Strategies
Questions you might ask your internal partners are: “Could you be more effective at getting your marketing materials to the right person?” “Could you improve targeting or forecasting through improved reporting, modeling or planning efforts?” “Could you improve the customer coverage model if we could more effectively identify and target customers?” “Are we failing the customer because processes are operating with bad data?” “Are there channel conflicts due to multiple or uncontrolled data sources?” “If you had better business intelligence, would you have a better chance of bringing the right product or service to market?”
If you get “yes” answers, then determine the benefits and the order of magnitude if you had a solution. Types of solutions could be through solving problems with data quality, hierarchy management, data integration, and resolving data source conflicts (through a Single Source of Truth), etc.
By helping business leaders frame their problems in terms of how an Information Management strategy could help them, then you’ve got the beginnings of a strong business case.
Your next step is to define the business requirements in more detail, and have your internal business partner(s) help you quantify the impact of solving their problems.
Stay tuned for Part 4, where Maureen Butler covers how to get organizational alignment for your business plan.
MDM and Data Governance – the Value of Planning
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Building a “Single Version of the Truth” can be more expensive than you expect, and documenting and measuring its ROI requires careful thought.
Good planning is more necessary than ever in an uncertain economic climate. The result of inadequate planning can be misdirected spending, chewing up valuable time and resources and then, six or twelve months later, having to go back and “right the ship”. And the second time around, the efforts are often overstaffed (to “make up for lost time”), while the organization as a whole might still be marching down the wrong path.
Master data management and data governance initiatives can have a disruptive effect on the organization, and the budget is often millions of dollars. Now the stakes are even higher, because in times of economic uncertainty, the pressure is on to “do more with less” and to take shortcut approaches for achieving corporate data objectives.
One such shortcut is to turn the MDM initiative into a “technology-only” project, perpetuating a “silo” approach to data and selectively purchasing the latest data quality or hub tools. This approach should be used with caution, because at the end of the day, data is still data, and without process and stewardship, even the latest technologies will probably fail to meet the intended objectives.
Because of the organizational effects (new processes, roles and responsibilities) in MDM and the budget requirements, our advice is to take the time for a readiness assessment, understand where on the maturity curve you are, see if your business drivers make a sufficient case, think through cultural issues, etc.
The results of an assessment may surprise you. Even with a strong business case and senior management buy-in, don’t underestimate the amount of preparation and time that a well conceived planning process for MDM and data governance will take.
Building the Business Case (Part 2) – Cost Reduction
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When it comes to building the case for an Information Management strategy, cost reductions alone may generate enough benefits to justify your business case, or they could further enhance your economic arguments.
Here are some examples of where you may uncover potential cost reductions:
1) IT costs, such as managing redundant systems/databases, data duplication and/or reconciliation, consulting fees, and software maintenance fees
2) Delivery costs due to inaccurate data, such as product returns, shipping fines, direct marketing waste, returned employee mailings, and Day Sales Outstanding (DSO) costs from invoicing delays
3) Productivity costs due to inefficient processes creating workarounds, redundancy, or rework. Also consider costs associated with audits, time to search for customer records, and time wasted matching customer files
Start by interviewing internal business partners to determine where they have issues. If your partners identify problems and participate in the business case development, they’ll have a vested interest in supporting it. Here are some business areas to consider:
- Finance / Credit / Accounting
- Sales / Contracts
- Corporate Development / Mergers & Acquisitions
- Marketing
- E-Commerce
- Customer Service / Call Center
- Operations / Production
- Human Resources
- Product / Vendor Management
- Merchandising
- IT
Ways to identify and measure costs include:
- Quantify shipping fines, returns, or other operational expenses
- Quantify mail return rate, response rate, and delivery hit rate (did the mailing actually make it to the intended person?) Check with Direct Marketing, HR, Finance/Accounting/Credit, Mailroom, or any other outbound mail services for these costs.
- Identify rework or workaround activities such as returned mail, product, and invoice corrections, product information corrections, report reconciliation, multiple databases, merge/purge and data matching errors, etc. Some partners, both leadership and end users, may accept this as ‘business as usual’, so be careful not to appear threatening or overly challenging.
- Conduct process mapping or other continuous improvement activities to identify & quantify problem areas. Always keep a broad perspective and analyze both up and down-stream processes.
- Conduct time studies on processes or transactions that appear inefficient such as customer service, warehouse, manufacturing, vendor management, payroll, reporting, data management, selling, marketing, planning, forecasting, customer maintenance, mergers and acquisition, etc.
- Conduct satisfaction surveys to measure customers’ experience with duplicate mailings, wrong customer information, delayed shipments due to bad data, credit problems, customer look-up time, etc.
- Work with UPS, USPS, FedEx and other carriers to determine how to improve shipping/postal rates
Cost improvement opportunities will exist all around the business; the trick is determining where you will get the “big wins”. It’s good to have a Finance partner participate throughout this process, so your assumptions and calculations are ‘blessed’.
To find out how to identify business growth opportunities and align business leaders, stay tuned for the next two articles in this series by Maureen Butler.
Building the Business Case (Part 1) – Risk Management
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When you’re building the business case for an Information Management strategy such as MDM, CDI, Data Governance, or Data Quality, start by articulating the business problems or opportunities. By building a compelling case and getting executive sponsorship, you’ll have a stronger chance of gaining organizational priority, funding and resources.
This 4-part series will review typical business challenges and provide pointers on how to make a compelling case for an Information Management strategy.
Part I: Risk Management
If your company’s leadership team is strongly focused on business risks, then focusing the business case on Risk Management is a good start. The following are some typical risk management issues:
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Regulatory Compliance such as financial reporting, Sarbanes-Oxley, environmental
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Legal Compliance such as contracts, pricing, compensation, privacy, human resources
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Other concerns, including diversity programs, quality programs, business system performance, etc.
Your business case should identify specific risks that are of concern to the executive team:
- Reporting discrepancies, inaccuracies, gaps, timeliness, lack of reporting, etc.
- Lawsuits / litigation
- Audit risks and/or audit findings
- Loss of certifications
- System performance, data archiving/retrieval
- Company reputation
Whenever possible, quantify existing or potential costs if risks are not mitigated or eliminated:
- External and internal audit costs
- Fines / penalties / legal costs
- Reporting inaccuracies
- Lack of standards, controls, policies, processes, procedures
- Workarounds, rework and other quantifiable process inefficiencies
Determine which business partners could be your allies. The more you engage, the stronger your business case and the easier it is to get leadership support. Examples include:
- Legal
- Internal Audit
- Finance
- Sales / Contracts
- Human Resources
- IT
- Quality
Risk Management is a great place to start, but if your organization doesn’t have compelling risk-related issues for some reason, or if you need to enhance your business case further, stay tuned for the next 3 articles in this series by Maureen Butler to find out more.
MDM Business Case Creation & ROI Analysis
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We published another one-page document today on our Business Case Creation & ROI Analysis service offering. Please let us know what you think …
