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A Story Of Installed Base Upgrades, Lost Business, MDM, Analytics And Politics

Lost business. The phrase strikes a chill into any CEO or line-of-business ("LOB") executive.

Lost business is also a special data management challenge.

So, let's see how a story about the "business of lost business" plays out between LOB execs and IT.  There is a data management angle on this story, and e
ventually we might even find some leverage for master data management (MDM) and analytics, but first we need to understand the all-important business drivers behind the scenes.

In our example, based on real events, imagine a technology services business employing close to a 1,000 people, and with accelerating product life-cycles. In only a half decade, the field refresh period for installed systems has fallen from seven years to five. This change means system sales reps must be on their toes for the upgrade sale, and ensuring the upgrade is even harder when smaller systems are sold through channels where warranty registration isn't complete.

What kinds of lost business events are there? First you have to understand that "lost business" as defined by Field Service means a "lost service contract" -- not a "lost system sale", although of course the two are closely linked. And in the distinction between services sales and systems sales we see the collision between three huge organizations: engineering, systems sales and services sales, each with different metrics and P&Ls! And to make matters more interesting, the engineering bill-of-materials ("BOM") has never been shared with customer services!

From the self-interested (and perfectly legitimate) perspective of Field Service, the semi-formal definition of "Lost Business", besides "Home Team Upgrade" (and thus "Warranty Transfer"), includes "Service Contract Lost to Third Party Maintenance Competitor", "Cancelled Contract, System Still In Place", "System De-Commissioned And Not Replaced"(possibly hiding a competitive upgrade), "Contract Service Level Changed", and the unhelpful "Unknown", an all-too-popular event designation. All these terms have specific legal definitions and data event attributes for capture.

The Field Service metrics stemming from reporting on lost business, together with all other Field Service metrics, enable a complete installed base model for customer services. Or at least the "installed base as defined by Field Service", which as noted above is not the same thing as installed base for all systems sales!

The installed base model supports strategic business analysis for the services executive team. The model is fed from operational systems, especially the Field Service contract management, Field Service services management and corporate billing systems. At the time, the models were entirely managed in spreadsheets.

With this business-oriented story in place, now we're ready to look at data management technology and projects. And we can see that we are in a very interesting business space, where master data management ("MDM") meets business models and politics! Or if you prefer a more polite term, "governance".

How do MDM and organizational governance issues come together around the issue of systems upgrades?

The Field Services organization enjoys huge revenues from older systems. In fact, on new systems sales, services revenues have been falling at the rate of 14% per year for any given system capacity -- a fact revealed in the installed base model.  (Although the falling service revenue yield is a challenge for Field Service, the phenomenon is a competition-driven engineering achievement and strict competitive necessity for new systems sales.). This decline in service revenue yield rates means on one hand that customers can see huge services savings when they migrate to newer systems, and a migration to a newer system is great insofar as it helps the sales organization make its numbers. But the Field Service organization on the other hand is not highly motivated to give up the older systems, for exactly the same reasons: the oldest systems are the most profitable and account for the largest revenue streams. In fairness, facing the inevitable, it should be noted that customer services leadership is looking hard for new sources of revenue.

But there's a data management problem!

Even if the Field Service organization can be persuaded to provide systems sales prospecting opportunities to systems sales people, sensibly on the oldest system at greatest risk to competitive upgrade, they can't!

Because the engineering-defined systems BOM has never been incorporated into Field Services systems!

Field Services systems have their own taxonomy of systems which makes sense from a field engineer's perspective. And in those systems and with that taxonomy, there's no way to directly select for "all customers with 7 year old systems" and get any human being names, with addresses, organization name, email addresses and phone numbers. Even if you wanted to!

And with sales rep and field engineer turnover, the "organizational memory" concerning where customer systems are is much less than 100%. In fact that's one reason why we like information technology, to solve problems such as organizational memory of customers! The better to serve customers!

Meanwhile, danger lurks.

During the same time that company leadership is "discussing" the pros and cons of upgrading older systems (there's a well-documented reluctance on the part of any organization to cannibalize itself), and lacking the technical capability to extract relevant sales opportunities, competitors have stealthily and systematically acquired comprehensive information on the installed base, including on most of the larger systems and a larger portion than the home team of the smaller systems sold through channels.

The methods used by competitors were simple and legal and involved market research and simple list purchases! And of course competitors have no compunctions about unleashing their quota-hungry sales reps on our customers. Remember, these are customers with older systems and high expense structures and thus prime upgrade targets. (Separate in-house survey research revealed that a disturbingly high percentage of "Unknown Reason" lost business events were in fact competitive upgrades.)

Eventually there's a happy story to tell about sales access to customer services information. With a mashup of engineering BOM data and the customer services system, together with billing data, sales gets a periodic feed with all the needed information. And a front-line home-team rep can even enter a high-level system designation and have the system pull all the locations and contact information for systems meeting those criteria. Prospecting nirvana!

Our story is based on real events at a technology vendor. And there's a strong analytics and MDM angle to the story. But the context is organizational politics and data governance. And only when the governance issues were addressed -- and senior execs stepped up because data management and access was critical to P&L results -- only then was the opportunity realized.

Do you have a master data management opportunity? Can you trace that opportunity back to a serious business case? Where a senior exec with P&L responsibility and insight would be willing to support a business case? MDM is hard enough. And good analysis is sometimes easier imagined than executed.

Make sure you've got the support you need and the payoff can be wonderful. You have a technical achievement that is then a programmatic part of your organization, and you'll be contributing to your organization's success every day!

Data Quality Sidebar

There was a big data quality issue which was a sub-project to the above sales prospecting success story.

Sales is difficult if you don't know the names -- correctly spelled names -- of human beings which are your primary targets.

In the case under discussion, customer contact names were stored in multiple locations, often with different spellings and different address, email and phone contact information. A major sub-project was undertaken to identify, capture, normalize, de-duplicate and clean the entire population of names. The resulting high-quality list was then joined to the BOM to produce a high-quality internal sales prospecting resource, made available to field sales. And then the full lresource was the basis for more wins when we mashed internal names up with external targeted lists!

Biggest Technical Challenges: (1) Undocumented customer name resources; (2) Scaleability issues in terms of massive files and databases and processing time.

Moral of story: Digital wins require business savvy as well as technical chops! There were difficult technical challenges through this project; but the business and policy challenges were equally important. Get everyone onside, show how working together makes sense. And make sure you can execute on the technical issues.