• Christophe Barriolade

How to add Master Data Management to your organization's list of 2014 resolutions

Many organizations recognize that master data management is a must have. As our customers point out, accurate and consistent master data for products, customers, financial accounts, organizational hierarchies and locations streamlines processes within the organization and reduces reconciliation costs. This need for accurate and consistent identifiers, attributes and hierarchies is the impetus for implementing the processes and systems used to govern your organizations shared data, or master data management.

However, in most companies the business and IT teams focus on operational projects and MDM often appears to be off their critical path. While these teams will gladly leverage an existing MDM program, the perception is that MDM is an independent program with its own executive sponsor somewhere at the top of the organization. That's why it shouldn't surprise us that a lack of an executive sponsor is one of the key reasons why MDM programs struggle.

Convincing executives to sponsor your standalone MDM program is not the purpose of this post. This post is about finding alternative approaches to implement MDM. In our thirteen years as a MDM software provider, we've seen hundreds of projects, many of started without a discrete executive sponsor. In this post I share a few approaches that worked for many of our customers and a few ideas for finally getting MDM on your organization's list of resolutions.

Securing your ERP migration with MDM

One of the biggest IT projects out there is the ERP migration. Whether they're ERP upgrades, platform swaps, or multi-ERP unifications; data migration is a key challenge. Data migration includes consolidating, cleansing and migrating lots of master data sets-supplier lists , product hierarchies or location data-between the old and new ERP systems.

While important, data migration is often framed as a one-off, useful as long as data needs to be ported over from the old ERP. Framed as such, the responsible teams often take a quick and dirty approach. They'll use tools at hand, literally emailing excel spreadsheets to each other when reconciling supplier codes or product hierarchies. Rarely the ERP team will invest in a data management platform just for the project to assist data migration.

While these approaches are expedient they can have a detrimental effect on the quality of the master data (which in turn can sink your ERP migration). Without workflow they'll be substantial process variability across the migration tasks as each team approaches the process slightly differently. The lack of automated tracking makes it challenging to understand how far along teams are or how much of the data has been migrated. And if there's no oversight, you're entirely dependent on the conscientiousness of your teams. While these missing capabilities are not an issue in small scale application upgrades with ERP migrations, these informal, ad-hoc processes breed plenty of downstream reconciliation and user-acceptance problems.

Several of our customers have used MDM to facilitate a structured data migration process. With built-in workflows and business user friendly interfaces found in MDM software, the teams can quickly establish processes to review and approve master data and mappings, make decisions on duplicates and inconsistencies. Workflow also adds oversight, traceability, and auditing to the data migration process helping the migration team identify problem spots and track status.

In addition, a centralized MDM hub can be especially useful for organizations that plan on staging their rollouts. In these types of rollouts, companies continue to run their old and new ERPs in parallel while they migrate each business unit or region to the new system. What this means is that the data migration project is not a one-time project but instead a continuous process to synchronize master data between the old and new platforms throughout the rollout.

In both cases, when the ERP migration is complete the organization has both a new ERP and a fully functioning MDM platform that contains all the policies and procedures needed to manage your master data.

From those customers stories that have inspired this blog post, I remember a quote from the CIO of a Fortune 500 company replying to the question "What is the ROI of your MDM program?". His answer what simply "Nobody is asking the question, as our worldwide ERP roll-out is on time."

Ensuring accuracy in business intelligence with MDM

My second example is on the analytical side: Business intelligence, or BI. Many organizations are deploying BI platforms to improve their understanding of the business. BI tools help managers spot opportunities for improvement by providing easy-to-use reporting and analytics that assesses an organization's performance over time.

In order for time-series analysis tools to be meaningful the dimensions and attributes the organization uses to classify transactional data need to be applied in a consistent fashion across business contexts or reporting periods. Inconsistency is often found across time periods. For example, an organization might have previously defined the North American organization as Canada and the US, if the North American organization ‘grows' to include Mexico in the next reporting period, adjustments must be made to make the data comparable.

A key strength of Master Data Management software is its ability to manage past, present and future versions of an organization's dimensions, attributes and hierarchies and their evolutions. Understanding the evolution of dimensions, attributes and hierarchies (such as our organizational hierarchy example for "North America") helps the business intelligence analysts understand how to keep the versions consistent so that the periods can be compared. For projects involving Big Data, the need for a solid MDM platform is even bigger. While much of the recent focus has been on big data management technologies, bear in mind that those small underlying sets dimensions, hierarchies and attributes are what makes big data meaningful, analyzable and therefore actionable.

A business intelligence program is a great opportunity to consider MDM. MDM will provide, not only, the accurate, trusted source of dimensions required to perform consistent reporting, but also the means to manage those dimensions and their versions over time.

MDM for EPM and Finance transformation programs

My last example is how MDM can support finance transformation programs and in particular the deployment of Enterprise Performance Management platforms.

Finance and accounting departments rely on multiple enterprise performance management applications for consolidation, planning, forecasting and budgeting. In order to produce accurate financial reports, those applications need to consume consistent reference data, such as charts of accounts, cost centers or legal entities.

As most of those data are managed in operational systems — GLs, ERPs, etc — project teams need to reconcile financial hierarchies before loading it into EPM applications. My experience shows that hierarchies and dimensions are usually managed in spreadsheets or custom tables which lead to errors and inconsistencies. One small error in your chart of account hierarchy can have dramatic consequences in your financial report. In other cases, companies use specific tools such as Oracle DRM. Those solutions reveal themselves to be expensive and usually limited to a small number of power users. As a consequence, finance and accounting user loose access and control on their core financial hierarchies.

This is another opportunity to use MDM technology. Rather than trying to maintain accounts and entities in spreadsheet, with many problems of synchronization and quality, an MDM provides a single store for all financial hierarchies. It also provides sophisticated hierarchy management capabilities that helps finance teams manage not just standard and alternate hierarchies, but also, keep track of past versions and work in future "as-if" versions.

MDM elevates data quality for your ERP, BI or EPM project

As I've explained in the three examples aboves, MDM software brings capabilities that improves chances for success in ERP migration and deployments of BI or EPM. That said in order for your master data management software to advance your project the technology you select should:

Be easy-to-adopt

With an ERP, BI and EPM rollout on the line, your teams don't have the time to invest in learning an entirely new technology-this is one reason why spreadsheets are so common. Our goal is to make MDM just as easy to adopt for all users (both technical and business) to compress the time-to-productivity as much as possible.

Be easy-to-use

In application rollouts you're already resource constrained. The MDM technology you choose needs to act as a force multiplier, improving team productivity. MDM software that is configuration-centric (rather than development-focused) means your teams have to spend time on technical tasks (hand-coding, testing and deploying screens, data models or workflows). Instead the teams invests their time on business oriented tasks such as understanding and reconciling your organization's dimensions, attributes and hierarchies.

Include distributed workflow

In most organizations there are multiple individuals that responsible or accountable for enterprise dimensions, attributes and hierarchies. Over and above the traditional email and excel route, workflow adds oversight, transparency and performance measurement-you can always report on who did, what and when. With email you know you sent an email, with workflow you can track everything from task statuses, acceptances, time-to-completion, defect rates and add simple things such as re-routing to handle cases where people are out of the office.

By using an MDM software during one of those enterprise projects (ERP migration, BI or EPM deployment), you will not only secure those initiatives but also build a solid foundation for an enterprise MDM platform. Many of our customers have started this way, and evolved to a more global architecture where the MDM become the point of entry and governance of their master data, integrated with both operational and analytical applications.

These are just a few of the many opportunities that we see to add MDM into your organization's agenda. What do you think? What other "two for one" opportunities do you see in your company?

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