Master Data Management - [MDM] Solutions

More to MDM than Customer / Client solutions

2011-09-01T21:24:00.000+01:00

It is amazing that my lastMDM Blog was nearly a year ago.. If Ihave any excuse, it is that I have been very busy implementing MDM solutions inthe Netherlands and in Belgium andtime just flies by when you are having fun!

What has interested merecently, is the increasing number of MDM solutions that are not “Customer /Client” based solutions. At the momentat the Entity Group I am working on Mastering TechnicalDocumentation and Learning Objects.

These new solutions are along way from the “Customer / Client” traditional view of MDM. However, the value benefits of mastering thistype of data are just as compelling.

What is becoming more andmore clear to me is that the duplication of any data type across a corporateenterprise introduces additional quality control issues and extra costs.

In the end, as the namesuggests, an MDM solution must deliver consolidated and clean data that can bemaintained as a master and reused across an enterprise.

Know a good customer profile when you see it?

2010-10-01T23:08:00.004+01:00

A visit to the London Retail Fraud 2010 conference this week proved to be very thought provoking, not least the workshop on

data sharing and the clear dependency the whole idea of shared information has on Master Data Management.

Having considered in previous posts the difficulties of creating an accurate single view of client data across a large company enterprise, I find the thought of creating an accurate client view across the whole FS&I industry a difficult one to reconcile.

From a client point of view I would worry about the integrity of the data, and the potential for mistaken identity to affect legitimate claims.

From a shareholder's perspective, I wonder if the investment made by FS&I companies in schemes like Cue, can be justified on grounds of value and the return on investment.

In my mind, most FS&I companies would get a better return by focusing on their own internal governance and an investment in the latest MDM and data analytics technologies.

It must be better to know your own customers, and understand what a good customer profile looks like for your own business model at the front end than to rely on others to identify your bad eggs at the claims stage?

Acquisitions, Mergers and Asset Stripping may cause the death of CRM?

2010-03-17T12:54:00.000Z

The Financial Services and Insurance sector remains in a continued state of flux. Over the last 20 years acquisitions and mergers, in particular the emergence of Bank Assurers has made the job of creating a single customer view across an FS&I enterprise almost impossible to attain, at least for any length of time!.

In 2010, we now face a different set of problems, with the prospect of the newly nationalised corporations being split up and asset stripped by a cash strapped government. The predicted sell off is likely to happen at a pace if the Conservatives form the next administration!

Counter this by the opportunities for sound companies to increase market share by acquiring smaller companies that can no longer satisfy the stricter financial solvency rules.   Witness the mergers occurring in the building society sector earlier this month

The traditional methods of creating the single customer view, involves merging systems and creating centralised CRM based solutions using on the same unlikely data quality standards highlighted in my last post.   It is not surprising then, that because of this continual churning, most of these “projects” either fail or are never-ending.

It is unlikely that the ebbs and flows of market capitalism will ever stop or slow down, so FS&I companies will have to find an alternative to the traditional CRM IT solutions to deal with the continuing expansion and contractions of a typical enterprise.

I did note this month, that one of the leading MDM products designed to solve this long standing problem [Initiate Systems] is, itself, in the process of being acquired by a larger company, IBM no less. Is this a sign that, even the CRM king that is IBM, have decided a new approach is now needed?

Does data quality matter in an MDM solution?

2009-12-29T11:39:00.001Z

Data Quality is often considered the panacea of a successful MDM implementation. However, in my experience, any attempt to achieve good data quality across a complex enterprise is almost certainly doomed to failure. Good MDM solutions therefore, have to work with inconsistent and poor data quality.

If there was a single industry data quality standard that applied to the finance and insurance industry, what would it look like and how difficult would it be for the average

FS&I company to conform to the standard?

This is a probably the minimal requirement for such a standard:

1. a set of mandatory attributes should be captured for each individual sufficient to uniquely identify them. [e.g. title, name, sex, date of birth];

2. the relationship each individual has with the company should be captured using standard terminology. [e.g. share holder, product owner];

3. the role each individual has with a company product should be captured using standard terminology. [e.g. life assured, beneficiary];

4. any change to individual circumstances that affects any of the standard attributes of relationship with company or products should be captured immediately. [e.g. change of name, change of address];

5. any change to the status of the relationship between company or product and the individual should be captured immediately. [e.g. at product maturity role changes from Life Assured to Maturity Paid].

In reality:

1. the only absolute method of uniquely identifying an individual is probably to use their encoded DNA or finger prints. However, this is impractical to implement on a large scale, and even these scientific methods are challenged by some within the legal profession;

2. even if the industry could agree a single terminology there would also need to be an agreed set of codes and abbreviations to facilitate IT storage requirements;

3. there is no obligation on 3^rd parties to pass on changes to individual circumstances to interested parties, even if the interested parties were known, and the disclosure did not contravene data protection rules;

There is an additional set of attribute that should probably be captured in support of the products where the individuals holds a significant role..

1. a standard set of attributed for each individual / role combination [e.g. for a Life Assured role – health status [smoker / non smoker], proof of data of birth etc]

2. any change to a 3^rd party relationship with the individual that affects the mandatory attributes or the relationship between company / product and the individual should be captured immediately.

I don’t think anyone would seriously suggest such a standard could be attained within a commercial organisation. Yet time and time again, data quality is put forward as a fundamental first step to a successful MDM implementation.

In my view the facts are:

1. each business has different needs in the area of data capture and the cost associated with the capture of non product specific data is not sustainable. Any MDM solution therefore has to cater for different data sets for different product / role combinations;

2. customer data can easily get out of date when the product life cycle does not necessitate regular customer contact. For some products, contact may be at the start and end of the product term. In some cases there may only be contact at product inception – term assurance for example where the customer dies during the product term. Any MDM solution therefore, has to cope with out-of-date data sets;

3. change of customer circumstances over time is a certainty and can vary from very predictable events like marriage, to unpredictable events like change to financial arrangement. Any sensible MDM solution therefore, can’t rely on the maintenance of up‑to‑date concurrent data.

If we take these facts into consideration, the obvious conclusion has to be that any attempt to maintain a consolidated master view of customer data can not be based on the concept of data quality standards applied enterprise wide across an organisation.

A successful, MDM implementation should build on and complement the product based data sets. To achieve this, more complex methods of creating and maintaining a consolidated view of Master Data need to be employed that do not rely upon data quality standards.