Quick Guide | 10 min read
The Business Case for Modern Master Data Management
High quality data is a critical requirement when operating a business. In theory, there should be no good reason why business leaders would raise objections to projects that provide access to high quality data that delivers business insight.
In today’s highly competitive and digitally-driven business environment, high quality data is a prerequisite to seizing growth opportunities and driving operational efficiencies.
This is borne out by the 82% of business leaders who strongly believe that data helps create a strategic advantage in strengthening their level of customer trust as well as their bottom lines
Yet many companies remain reluctant to commit to Master Data Management (MDM) initiatives, despite the fact that they recognise they have a problem when it comes to reliable, actionable data. In fact, according to a recent article by KPMG, 56% of CEOs have concerns regarding the integrity of their data. So why the hesitancy when it comes to MDM?
One major cause is that there are a significant number of technical and business leaders who will have embarked on MDM projects before, only to have been met by failure and frustration. Gartner estimates that close to 85% of big data projects fail – a frighteningly high proportion – and anyone who has been burnt by the big data promise may be understandably reluctant to tread that path again.
So how do Chief Data Officers, Heads of Data, Data Architects and Data Scientists go about building a compelling business case for MDM which not only addresses the desired outcomes and current challenges of the business, but which will also stand up to scrutiny when it’s time assess whether the project was a roaring success or an abject failure?
Read our guide to creating a strong business case for MDM below.
1. Focus on business outcomes
The ultimate goal of any MDM project will most likely fall into one of three areas – enabling growth opportunities, driving operational efficiencies and/or managing risk. There are many different ways in which trusted and reliable data management can support these overarching goals, and your business case should be very clear about how your project will deliver on them.
Best practice is to focus on one key area of the business initially. MDM projects tend to have one of three main areas of focus – customers, suppliers & products, or internal. For example, if your commercial leaders are concerned about customer loyalty and retention, your customer-centric goal might be to achieve a single view of the customer and quantify the monetary value to the business if you were able to deliver hyper-targeted marketing campaigns that directly addressed customer buying behaviours and preferences.
If, on the other hand, you’re a manufacturing business with multiple suppliers, locations and product lines, you might want to know which of your products is most profitable and which of your suppliers is the most cost-effective. This would form the basis of a supplier-centric MDM project.
Whatever the issue you’re trying to fix, make sure that it clearly aligns to a goal that is important and has value to the business. Remember that your project will likely be competing with many others from across the company for attention and funding. A quantifiable, measurable and realistic business outcome will greatly increase the likelihood of securing both the funding and executive sponsorship you need to get your project off the ground.
In summary, the effectiveness of a Master Data Management (MDM) project hinges on its alignment with critical business outcomes like growth, operational efficiency, and risk management. Success demands a focused approach, targeting specific areas like customers, suppliers, or internal processes, and should be directly linked to tangible business goals. A well-defined, quantifiable project that addresses a key business need increases the likelihood of obtaining necessary funding and executive support, ensuring the MDM initiative's relevance and impact within the organization.
2. Secure executive sponsorship from the outset
If you’ve successfully identified the business outcomes, the next logical step is to identify and gain consensus from an executive sponsor with a vested interest in ensuring that those outcomes are achieved. The need for an executive sponsor for MDM projects is not new, and the lack of one has long been cited as a primary reason for the failure of these types of project.
In traditional MDM projects this was because it would quite probably touch every system and process in some way, and change not only how data is managed but also processes and practices that affect many people and departments. Conventional MDM projects have the potential to become very disruptive and political, another reason why being the lone champion is a risky business.
Modern MDM goes a long way to negating this issue because there is far less emphasis on human intervention and upfront preparation – and therefore less disruption to the business. The most advanced platforms can start to deliver ROI almost straightaway, making it far easier to keep executive sponsors engaged and committed to the project. While you will most definitely need an executive sponsor who can evangelise and communicate project progress to a broader audience, their job (and yours) will be made a lot easier by having regular wins to show for it.
In summary, securing executive sponsorship is crucial for the success of Master Data Management (MDM) projects. The role of the executive sponsor is pivotal, especially given the history of MDM projects failing due to a lack of high-level support. Their engagement is vital due to the cross-functional impact of MDM, which traditionally touches upon multiple systems, processes, and departments, potentially causing disruption and political challenges.
Modern MDM projects, however, benefit from reduced human intervention and faster ROI, aiding in maintaining executive interest and commitment. An effective executive sponsor not only advocates for the project but also communicates its progress and achievements, leveraging regular successes to sustain momentum and support within the organization.
3. Focus on small, quick wins
A traditional MDM implementation is generally considered successful if you can get a single domain operational within six months. Six months! This is because in traditional implementations you need to model the data, identify and develop the right business rules and then build a complex ETL (Extract, Transform and Load) pipeline to bring it all together. In effect, you needed to build your data model upfront, and hope that the data fits into it.
Yet data is a living, breathing, and forever morphing business asset. Which means that within every organisation there’s a significant amount of data which just doesn’t follow the rules and fit neatly into the categories we’d like. And this is never going to change. If you wait to fix the quality of your data before you embark on an MDM project, you’re in for a long wait.
Modern MDM does away with upfront modelling, effectively letting the data – even when it is of poor quality - find its own path using the principle of eventual connectivity. This allows you to onboard new data environments in a scalable way. As you bring data in, your MDM solution should be capable of doing the manual, repeatable work for you by providing tools that can identify common issues, like spelling errors, and automatically fix them as they are ingested into the platform. Using this approach allows you to identify common data problem patterns more effectively and fix them as you go. This won’t work for all parts of the business or all types of data such as Personally Identifiable Information (PII) and credit card information, and your solution should be sophisticated enough to understand these constraints and apply the right business rules at the right time for each data point.
This way, the technology can pick up 80% of the challenges and help discover the underlying issues with the final 20%. Using this approach means that you can grow from five data sources to 25 or even 250 data sources that were never meant to work together, but can now. What does this mean for your business case? In conjunction with your MDM partner, you should be able to break the project down into manageable use cases that not only accelerate the implementation, but also the ROI. The most effective project managers know that it is far more efficient to focus on small, gradual wins, instead of a grandiose "one and done" approach.
Anyone with experience of MDM projects will probably be prepared for a long wait before the value is realised. Your job, and that of your technology partner, is to demonstrate that it doesn’t have to be that way, and that the ROI of the project is both achievable and measurable.
In summary, focusing on small, quick wins is essential for the success of modern Master Data Management (MDM) projects. Traditional MDM approaches, characterized by lengthy implementations and upfront data modeling, often delay tangible results. Modern MDM practices, however, embrace the concept of eventual connectivity, allowing for the onboarding of diverse data sources without rigid initial structuring. This approach acknowledges the dynamic and sometimes unruly nature of data, offering tools to automatically address common data issues and adapt to various data types, including sensitive information.
By breaking down the project into manageable use cases, modern MDM allows for a scalable expansion from a few to hundreds of data sources, emphasizing the importance of incremental progress over a single, comprehensive solution. This strategy not only accelerates implementation and the realization of ROI but also challenges the traditional expectation of long wait times for MDM project benefits. Effective project management in this context involves demonstrating the attainability and measurability of ROI through a series of progressive, achievable milestones.
4. Demonstrate the cost of doing nothing
A solid MDM business case will clearly outline the ROI of the project in commercial terms – either through opportunities to generate more revenue and/or profit, or by saving the business money. How easily you can quantify these amounts will depend on how complex the undertaking is and how well you work with line of business, finance and your executive sponsor.
While it isn’t always possible to come up with a definitive amount saved or gained, you can research best practice examples and refer to successful business cases outside of your own organisation. This will also allow you to show how other organisations are using MDM to support their initiatives, and potentially how your competitors or other industries are gaining an advantage. The cost of not being able to gain insights into how your customers buy or the points at which churn occurs cannot be measured purely in terms of immediate revenue loss. Over time, as your competition gains these insights and puts them to good use, the impact on your organisation will amplify if you choose to stand still.
In summary, a key element of a solid Master Data Management (MDM) business case is demonstrating the cost of inaction. This involves not only highlighting the potential ROI of the MDM project in terms of revenue generation, profit increase, or cost savings, but also considering the broader impact of not implementing the project. While exact savings or gains may be challenging to quantify, drawing on best practices and examples from other organizations can provide valuable insights. It's important to recognize that the inability to gain customer insights or identify churn points extends beyond immediate revenue loss.
Over time, as competitors leverage these insights, the negative impact on an organization that does not adopt MDM can significantly intensify, underscoring the cost of doing nothing.
5. Be clear about the ROI
The ultimate metric for any project is ROI and no business case would be complete without it. In its simplest form, an ROI calculation weighs the expected quantifiable benefits of an MDM project against its costs and will project this over a period of years. Your organisation will have its own language and prerequisites for ROI so it will be important to frame your calculations in the terms that business and financial leaders understand and expect, and include all relevant data and documentation. Another benefit of this approach is that by couching it in business terms and using the organisation’s preferred method of measuring value, it becomes more than just “the MDM project” as it is inextricably tied to a set of agreed metrics and outcomes that key stakeholders have all bought into.
Some MDM platforms will be easier to create an ROI case for than others. For example, by choosing a cloud-native MDM platform, one that was built to integrate easily into environments like Microsoft Azure, you can demonstrate how you’re future-proofing the organisation’s investment by introducing predictable, transparent pricing, accelerating implementation and reducing manual processes. The most advanced platforms can lower operational costs by 25%, minimise manual work by a factor of 12 to 1 and are 80 percent faster to implement than their traditional counterparts – all of which will help to boost your ROI.
In summary, articulating a clear Return on Investment (ROI) is crucial for any Master Data Management (MDM) project business case. The ROI calculation should compare the expected quantifiable benefits to the costs of the MDM project over several years, using metrics and language familiar to business and financial leaders. This approach aligns the project with the organization's value measurement methods, making it more than just an MDM initiative, but a strategic business endeavor with agreed-upon outcomes.
The ease of creating an ROI case can vary based on the chosen MDM platform. Opting for a cloud-native platform, especially one that integrates seamlessly with environments like Microsoft Azure, can showcase future-proofing of the investment. Such platforms often offer predictable pricing, faster implementation, and reduced manual processes. Advanced platforms can potentially lower operational costs by 25%, reduce manual work significantly, and implement 80% faster than traditional systems, all contributing to a stronger ROI for the project.
There has never been a better time to embark on an MDM project, as pioneering new approaches like zero-modelling and eventual connectivity are breaking down the barriers to success and enabling a multitude of use cases like improving data quality, building a single view, creating a data fabric and unifying data silos. All of which are essential for your data-driven projects.
Whatever your overarching business goals, they will almost certainly rely on having data that is accurate, insightful and ready to be used by multiple departments. The key to building a successful business case is demonstrating how modern MDM can enable these initiatives, and those of the future, in a scalable and outcome-driven way.
Here are the key take-aways from this guide:
1. Focus on Business Outcomes:
- MDM projects should target growth, operational efficiency, or risk management.
- Best practice involves focusing on specific areas: customers, suppliers, products, or internal processes.
- Clear, quantifiable goals aligned with business values are essential.
2. Secure Executive Sponsorship:
- Executive sponsorship is critical for MDM success.
- Modern MDM minimizes disruption, aiding in maintaining executive commitment.
- Sponsors should actively advocate and communicate project progress.
3. Focus on Small, Quick Wins:
- Modern MDM avoids upfront modeling, adapting to data's dynamic nature.
- This approach allows for scalable integration of diverse data sources.
- Emphasizes incremental progress and measurable ROI.
Demonstrate the Cost of Doing Nothing:
- Highlighting potential ROI and the broader impact of not implementing MDM is vital.
- Use examples from other organizations to underscore potential benefits and losses.
- Recognize the long-term impact of failing to gain customer insights or identify churn.
Be Clear About the ROI:
- Essential to present a clear ROI calculation.
- Align the project with the organization's value measurement methods.
- Cloud-native platforms can offer predictable pricing and faster implementation, enhancing ROI.
- Modern MDM approaches like zero-modeling and eventual connectivity simplify implementation.
- Success depends on demonstrating how MDM can enable scalable, outcome-driven initiatives that support data-driven projects and future goals.