Blogs

Examining The Corporate MDM Dashboard: What, Why, How and When

Jul 25, 2019 6:01:16 AM / by Abhishek Kamboj

Master Data Management (MDM) is no longer a “fast follower” initiative but is now a generally accepted part of any information management program.  Many enterprises have well established MDM programs and many more are at the beginning stages of implementation.  In order to be successful with MDM you need continuous insights into that master data itself and how it is being used otherwise it is impossible to truly manage the master data.  An MDM dashboard is an effective tool for obtaining these insights.

What is an MDM Dashboard?

 It is difficult to improve a process without having a means to measure that process.  In addition, it is difficult to gauge continuous improvement without being able to track performance on a regular basis.  Dashboards are a common tool that is used to communicate key measures and their trends to stakeholders on a regular basis.

An MDM dashboard provides key measures about the master data such as:

  •  Metrics and trends of how the master data is changing.
  •  Metrics and trends of quality issues, issue resolution and issue backlogs.
  •  Insights into the composition of the master data.
  •  Metrics and trends of how the master data is being used by consumers across the enterprise and their experience such as meeting or failing service level agreements.

Additionally, the MDM dashboard must highlight significant changes and provide insights into key improvement areas and risk areas as these are what need to be actioned.  For example, perhaps a sudden increase in high severity quality issues coming from a particular source system.

The stakeholders for the MDM dashboard will be broad given master data is an enterprise asset.  Stakeholders will consist of a mix of business and IT resources from a variety of areas.

Stakeholder

Use of Dashboard

A representative from each consumer of the master data (e.g., call-center applications, e-commerce applications, data warehouses and so on)
  • They will want insights on how many transactions they executed against the MDM hub, failure rates and SLA attainment and how it compares to past periods.
  • They will want to understand trends in quality for the data they are using, or plan to use, because data quality directly impacts business outcomes.
  • They will want to understand the composition (or profile) of the data they are using.
A representative from each provider of the master data (i.e., source systems that feed the MDM hub)
  • They will want trends in quality issues for the specific data they have provided to the MDM Hub so they get insights into their own data quality and can prioritize addressing quality issues at source.
  • They will want to reconcile change metrics in their system with change metrics in the MDM hub.
Executives responsible for managing the MDM program
  • They will want insights on MDM hub operations and performance to evaluate whether the system is meeting defined SLAs for the many consumers across the enterprise.
  • They will want to understand trends in data quality and data usage to not only optimize the MDM hub, but also to justify the MDM program.
Data Governance Council members responsible for setting and measuring policies including data quality initiatives
  • They will want insights into all aspects of master data and its use, including quality trends, change trends, consumer activity etc.  However what is most important is in highlighting any significant changes from period to period so that the council can take action where required to identify and prevent potential issues before they escalate.

The frequency for producing and delivering an MDM dashboard that targets these stakeholders varies from client to client but a common time frame is monthly.  However, this does not negate the need for frequent, detailed reports delivered to other stakeholders. Daily and weekly reports, for example, are essential to the team members that are responsible for implementing the MDM program.

What are the contents of the ideal MDM Dashboard?

The business cares most about significant changes in metrics and it is those that must be highlighted.  The goal of any dashboard should not be to look at everything available but rather to look at the information that is most important and most revealing - to gain insights into what is happening within the business unit with the end goal of making better decisions and identifying and anticipating issues before they can have a negative impact on the business.  An MDM dashboard can help to identify how effective the MDM and governance programs are in meeting the needs of the organization.

Breaking down the metrics

Every metric is nice to have but not every metric is key at the strategic level.  For example, metrics which show that MDM helped increase the accuracy of customer data by 10% aren't likely to impress the management, but metrics which show that customer retention or cross-selling rates increased as a result of MDM will.

To make the link between goals and strategy, organizations should focus on specific metrics instead of trying to measure everything that can possibly be measured.  Therefore, organizations should look at the top five to 10 items that are important to measure on a regular basis.

Standard key metrics to be captured in the dashboard include:

Key Metric

Contents

Master Data Composition A static view of the master data - very much important because data is brought together from multiple sources and this gives you insight into what your “combined view” looks like.
  • Number of master data records (eg, number of Customers, Accounts, …)
  • Number of key elements and ratios (eg, Number of Addresses and average number of Addresses per Customer, number of Customers with no Addresses, number of Customers with many Addresses and so on).
Master Data Change Provide understanding on how the master data has changed over the time.
  • Number of de-duplicated and split master data records.
  • Number of New records, Updated records for the month.  Additionally a comparison on change trends from last periods with significant variances highlighted.
  • Change for key elements of interest.  For example, New / Updated Email Addresses if there is a campaign to obtain as many email addresses as possible for direct marketing purposes.  Again, with comparisons to prior periods.
Master Data Quality Provide master data quality trends.  Quality concerns differ from one client to another but common concerns for customer master data include anonymous values in names, invalid addresses, customers that don’t fit a n expected profile (such as too many addresses) and default birth data (such as 1900-01-01).
  • Number of quality issues discovered in the reporting period (by severity and type of issue).
  • Number of quality issues resolved in the reporting period.
  • State of the quality issue backlog to be addressed.
  • Sources contributing to the quality issues.
  • Trends compared to previous periods.
Master Data Usage Provide an understanding on how the master data is being consumed.  Managed master data only has value when it is consumed and so it is important to understand who is using it and how it’s being used.
  • Top consumers of the data including SLA attainment and error rates.
  • Trends using past reporting periods with significant variances highlighted.  If a consumer’s activity spikes for one month it may indicate an issue on their side or new requirements on using the data.

MDM hub performance details that can be used for capacity planning and performance tuning.

  • Number of transactions broken down by transaction type.
  • Success versus failure rates.
  • Processing Rate (transactions per second).
  • Min, Max, Average response times and message sizes.

Semantically speaking, organizations can define their metrics in more business-oriented terms that are meaningful to stakeholders. For example, strategic metrics related to the operational effectiveness (e.g. cost measures), customer intimacy (e.g. customer retention rates), and so on. The bottom line is key metrics drive the success of the organization.

Example Uses

The following are examples of how an MDM dashboard can be used to support and optimize business initiatives.

Example 1: Reduced mailing costs in marketing campaigns

The marketing team of a retail company uses the customer and address data from its MDM hub for its direct mail campaigns. Investigations revealed there is approximately $4 in processing costs for each returned mail item plus an undetermined amount of lost revenue since the mailed item did not reach its destination and fulfill its purpose.

An MDM dashboard would provide fundamental metrics and trends on address data including:

  • Number of customers and addresses
  • Number of new and updated addresses in this period
  • Number of addresses in standard form

The dashboard would provide advanced metrics and trends including:

  • Number of addresses with quality issues broken down by severity
  • Number of addresses that are aging and have become unreliable due to data decay

The marketing team can use this information to understand trends and be more strategic in how they approach their campaigns from a cost perspective.

Example 2: Addressing quality initiatives at the source.

Many source systems don’t have quality controls and trending information on master data such as customers and products that resides in their databases.  Analyzing the master data within an MDM Hub provides a “one-stop-shop” for finding and tracking quality issues that trace back to particular source systems.  It is always best to address quality issues at source and an MDM dashboard would provide management the metrics they need to understand how quality of the data and the backlog of issues in their source systems are trending.  Likewise, it gives the MDM team insights into how source systems are contributing to the MDM effort.

Example 3: Capacity Planning

As MDM gains momentum in the enterprise, it takes on more and more consumers.  Examples of consumers are CRM systems, e-Commerce, Web Applications, source systems and data warehouses.  As with any mission critical system, it is important to ensure the MDM Hub is providing all of these consumers with high quality service. This includes (but is not limited to) providing maximum availability and the ability to fulfill transaction requests within defined service level agreements (SLAs).

It is critical then to understand transaction metrics for each consumer including:

  • Number of transactions executed
  • Types of transactions executed
  • Failure rates
  • SLA attainment rates

These metrics, along with high level trending information, can be used to plan for future capacity needs to ensure the technical resources are there to satisfy the demands placed on the MDM hub.

It also gives your data stewardship team the means to identify anomalies and items in need of investigation – for example, if a consumer’s transaction workload drastically increases one month or suddenly begins to experience an unusual number of failures.

Conclusion

If you want to manage it then you must first measure it.

This is no less true just because your organization has implemented MDM - how can you expect your teams to manage your master data if they have no way to measure it?  An MDM dashboard is a tool that provides the measurements to various audiences so that you can optimize your MDM program and get more business value from it.

InfoTrellis has incorporated over 12 years of experience both in MDM product development and MDM implementation in a unique MDM dashboard solution “MDM Veriscope” that provides  you with the metrics you need to manage your MDM program.

Please click here for a recent announcement (April 2013) on the release of MDM Veriscope 3.0.

Topics: Blog, Data Quality, MDM, Master Data Management, MDM Implementation, master data governance, data governance, master data analytics, MDM Dashboard, reporting

Abhishek Kamboj

Written by Abhishek Kamboj

Subscribe to Email Updates

Lists by Topic

see all

Posts by Topic

See all

Recent Posts