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Customer Science in Motor Retail: Keynote 2. How to Harvest Actionable Insights from Dealer Management Systems

Actionable Insights are those views of data that cause managers to ask new questions about how processes work and take action.  They differ from key performance measures and daily operating control (DOC) reports that focus on delivering a picture of progress against a strategic objective, operating budget or forecast.  What actionable insights can dealers expect to source from their Dealer Management Systems – and how do they source them?

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Most motor retailers employ a Dealer Management System (DMS) to manage and administer all facets of their business operations.  The typical components of a Dealer Management System include Financials, Showroom and Customer Relationship Management (CRM), Parts, Service, Workshop Management, Point-of-Sale, Franchise Data, Vehicle Stock, Purchasing and Pricing Administration.

Many of the Dealer Management Systems that exist in the motor retail sector are proprietary systems and some of the technology employed dates back to the pre-noughties when the world had never heard of cloud computing and mobile phones were the size of a small brick.

The reason why the industry has been so slow to adopt change in IT has a lot to do with the complexity of the dealer information environment and the close synergies of the many operational areas that exist in a dealership.  As part of a tightly knit supply chain, dealers also need their systems to talk to the systems operated by the motor manufacturers.  These integrations are also complex, hard to create and adapt. Dealers ideally want to have a single information environment so to meet their need. This means software vendors have to invest hugely in attaining the ‘critical mass’ of capabilities the industry demands before they can hope to compete with incumbents.  This creates a natural barrier to new software vendor entrants hoping to enter the market.

The consequence of this market stagnation in viable competitive DMS options for major dealer groups means many are required to operate computer systems that are poor at sharing their data and exposing the actionable insights that dealer execs need.

In a market where competition is growing daily, dealers know they need to be much better at understanding the relationship with their customers, better at producing personalized offers that are event-driven, fine-grained and relevant, and better at finding more reasons to speak to customers that are ever more distant and only happy to engage with suppliers when it suits them.

 

Data Discovery from Dealer Management Systems

The quality and completeness of operational analytical tools found in Dealer Management Systems varies hugely.  Many of the younger software products include highly impressive reporting tools that are ideal for understanding the performance of pipelines and processes.  Where most dealer systems tend to fall down is their ability to source ‘holistic’ views of customer profiling, interaction and life-time value.

The essence of customer science is to gain a single page view of the customer that uncovers all aspects of the relationship including:

  • Profile: Affluence, location, family status, employment, habits etc.
  • Persona: What makes them ‘individual’
  • Communication: Communications history, activities and preferences
  • Driver behavior: How the customer drives their vehicle and the impact on vehicle depreciation and maintenance schedules
  • Buying behavior: What do they buy, how do they buy, likes and dislikes; what sort of relationship do they want to have with their suppliers?
  • Products: What vehicles do they have, like, have had previously?  What other products and services have they used, would they like?
  • Life-time value: What is the potential value of business derived from this individual

Uncovering these insights is valuable – useful - but it’s only when these many attributes can be connected that the eureka moments occur and marketers and their customer service colleagues uncover the gold dust that makes their campaigns more effective and raises the bar on their customer experience.

As a general rule, Dealer Management Systems are designed to support the many key processes that exist within a motor dealership.  By analyzing generic capabilities of motor dealerships we now know there are approximately 136 major processes that occur within a motor dealership.  These are supplemented by close to 200 common reports and approximately 150 primary referencing tables.  You get the picture – it’s complicated.

When software applications are built for a purpose the data models that underpin them take on that form.  In the case of Dealer Management Systems that means that most data models are poorly designed and include the same tables time and again in different parts of the data structure for different reasons.  For example, the field ‘Country’ will appear in customer and supplier addresses.  It will also appear in delivery locations and other records.  But will there be a single table for ‘Countries’?  Probably not.

So what?

The implication of this confused data structure is that execs that want to see customer views by activity, service used, spend (etc.) won’t be able to easily source these views because the data will be held in many separate silos and in the wrong structures too.  It also means that dealers, when they look at the data, they won’t necessarily know if they’re examining a list of vehicles from the CRM system, or a similar list of vehicles from their Vehicle Stock Book.

 

Advances in ‘Actionable Insights’ Data Harvesting

The good news is that cloud computing has introduced smarter ways of harvesting and creating new views of data that remove the hit and miss complexity of constantly trying to mash views on a spreadsheet.  How it basically works is this:

  1. Flat files reports (the type you produce on a spreadsheet with no pivot tables) are produced for each master process area.  These are designed to contain the magic fields that identify customers, vehicles, sales people, dealerships and other key identifiers.
  2. These flat files are uploaded to a ‘sorting’ engine that normalizes the data, uncovers errors and brings the various flat files together in the form of a relational database ‘in the cloud’.  This new data structure is sometimes called a ‘data mart’ – not to be confused with a ‘data warehouse’ which is a much more rigid, pre-planned data architecture for preprocessing views of data. 
  3. Once the data is onboarded, data connections are automatically generated between the various magic fields (i.e. primary key identifiers of the subject records) and it’s now possible to start performing queries on the data to create the actionable insights execs want to see.

The above summary ignores the fact that there’s a lot of data NOT on Dealer Management Systems that can enrich customer profiling systems and add fresh perspectives to analysis such as customer experience data, website clicks and interactions, finance company data, service plan data, SMS messaging inbound/outbound activity, mapping resources and consumer profiling data resources from third party vendors.

Federated operational insights systems like the one I describe are best placed to harvest data in this way and remove the complexity and cost of sourcing data from Dealer Management Systems.  A few words of warning however:

  • This type of system does not displace the need for effective operational reporting within the process-centric tools that run the business, though these are increasingly well catered for by vendors
  • Operational analytical systems are rarely able to feed data back into the Dealer Management System, although why you’d need to do this I struggle to understand.  I suspect most managers want a ‘single version of the truth’ for the data they look at but few people care if it resides on one system nowadays.

 

Key Technology Components

The good news is that cloud computing has introduced smarter ways of harvesting and creating new views of data that don’t require people to invest time manually authoring reports or playing with data in spreadsheets – and thank goodness because anyone that’s had to do it knows how boring and tiresome to task of manually aggregating and normalizing data can be! 

There are a few crucial technology innovations that have made this possible:

Web Server Apps

Popular platforms like the Microsoft Web Platform (comprising of modules including Microsoft SQL Server, Microsoft ASP.NET and Microsoft IIS) are able to publish applications in a format that means they can be viewed on a browser without requiring any downloads and plug-ins to the computer device.  That means you can view applications using mobile phones, tablets, PCs, laptops and smart digital televisions provided you have suitable User Permissions to login. Users are assigned to User Groups and their access and usability permissions are governed by the permissions assigned to the group, or groups, they belong to.  In a 24/7 world, users can experience the Martini moment of – anytime, anyplace and anywhere computing without having to fuss with onboard apps.

Private-Cloud Infrastructure

Deploying hosting web server apps on a private-cloud infrastructure means that buyers don’t need to fuss about installing web servers and managing them.  It removes the burden of installing hardware and software applications; and managing them.  Private-clouds can be configured for each account (so that each account has their own dedicated database and resources), or alternatively clouds can be multi-tenant environments where customers share the computing resources of the host web server.

Data Flow Augmentation and Data Extract, Transform and Load (ETL)

Something has to engineer the automated uploading, normalization, transformation and workflow of data to the cloud environment.  The tooling to do this now is relatively common-place.  What this automated routine needs to do is to watch a folder and wait for reports to turn up, or automatically kick into life at a scheduled time, to then audit the content and coax the data into the technology equivalent of a food blender that will spit out ‘good data that fulfils the upload criteria’. 

One of the clever features of this ‘blob’ of technology is that it needs to be capable of dealing with iterative changes to successive uploads of the same reports.  Let me have a go at explaining this:

When you upload several reports to the data crunching engine in the cloud for the first time, all is good with the world because there’s nothing else up there.  Do it again and the data crunching engine needs to sift through the fresh upload of data and work out: (1) What data exists and hasn’t changed? (2) What data exists but has been updated? and (3) What new records have been added that need to be included?

This is a non-trivial challenge and is an important feature of the data crunching engine.  Otherwise, the next time data is uploaded it will result in duplicates and lots of confusion (not good!).

Operational Analytics Software

There are many different sorts of operational analytics software (see my summary article on http://www.business2community.com/business-intelligence/operational-analytics-best-software-for-sourcing-actionable-insights-0560328 for more details) but some kind of data visualization and reporting tool-kit is needed to make the most of the harvested data.

Combine these four attributes – web apps, private-cloud deployment, data flow augmentation/ETL software and operational analytics software – and you have the essential ingredients of an Actionable Insights system that can harvest data from your DMS without have to work hard to do it!

 

Purchasing Options

There is a wide spectrum of technology vendors able to provide either components or complete platforms for authoring operational insights systems capable of extracting data painlessly from a DMS. There are also companies out there that provide marketing, data cleansing and customer science services targeted towards serving the specific needs of the dealer market. 

When it comes to the computing platform itself, as I summarize above, any solution needs to manage data crunching (to get the data in the right shape and form) together with data visualization and reporting tooling to make sense of it.  These ingredients with then need to reside on a server somewhere; more commonly now on a private-cloud to prevent the need to manually install hardware and software.

Buyers have a range of sourcing options to consider and these include:

1. Build your own system by using a highly dexterous and enterprise scalable cloud platform

There are too many of these to cover all of them but examples include the obvious BIG names like Microsoft Azure, cloud.google.com/appengine, Force.com (from Salesforce.com), WebSphereClouds or Amazon Cloud.  These big cloud tool-kits make development much easier than it used to be and all of the major vendors are on-point when it comes to scalability, security and resilience.  Don’t expect to have a quick solution though because it takes time and effort to get solutions ‘tuned’ to suit your needs.  Nevertheless, once you’re done you should have a first-class system.

In the last few years we’ve also seen a proliferation of smaller, expert cloud app platform vendors like CloudFoundry, CloudAppStudio and ActiveState that make it easier to design and publish custom applications to secure cloud environments, often demanding lower skills overheads.  The challenge facing these vendors is to ensure they can offer sufficiently complete platform capabilities.  They need to satisfy customers that they’re able to go the last mile on developments: The last thing customers want is to find, after months of a development, that some capabilities are missing and they have to start over on a bigger platform like IBM WebSphere, Amazon Cloud Web Services or Microsoft Azure that profit from the many millions of R&D dollars that bigger vendors have at their disposal.

2. Buy breed tool-kits

Getting a solution up-and-running faster can be achieved by selecting best-of-breed components. Two will be necessary to ‘fast-track your development;

  1. A platform for designing the apps you need and managing the cloud data crunching using platforms like Interneer, Encanvas and OutSystems that offer out-of-the-box tooling to meet the majority of needs.  All of these providers provide ‘low or no’ coding overhead to the task of authoring applications.  They also possess rich data connectivity and workflow features.
  2. An overlaid expert analytics tool-kit like Qlikview, Tibco Spotfire, Tableau, Yellowfin, Birst, iDashboards, Jedox and Jaspersoft.  These providers offer data visualization, dashboarding and reporting tools.

Of course, the nature of competition means that if you ask any of these vendors they will probably say they can offer a complete solution ;-)

3. Pay someone to build it for you

There are many companies out there like CSC, CACI, Canon, US Tech Solutions, Wipro, TCS, PA Consulting and countless smaller industry expert companies like DealerSolutions, Nybble and Ambridge Consulting that specialize in the data centric custom applications authoring arena.  These companies will provide fixed price projects to deliver solutions to buyer specifications.

4. Buy a ready-made service

I have no doubt that, like NDMC Consulting and introhive, there are other companies have entered the automotive market in the past few years thanks to the available of suitable tools to provide ready-made online services that deliver the outcomes needed without requiring dealers and motor manufacturers to build their own solutions.  The challenge facing providers is that each and every system will require heavy customization and tailoring.  Encanvas Remote[Spaces] is an example of a cloud architecture that enables every customer to enjoy their own individual and private cloud service.  Competing platforms like Interneer, Tibco Spotfire, Force.com and OutSystems (to mention a few) are no doubt able to offer a similar capability.

Summary

Cloud-based operational analytics solutions are growing in popularity as a way to extend the life of Dealer Management Systems investments.  They lever value from sleepy data held in administrative systems by finding smarter ways to turn data connections into new reasons to engage customers in dialogue.  These solutions do create a single version of the truth but in a different way; not by seeking to install another system, but instead by adding a value extracting capability in the cloud that gives dealer executives the actionable insights they need without the pain of yet another major IT project.

 

About This Series of KeyNote Articles on Customer Science in Motor Retail

How does Motor Retail benefit from applying operational analytical tools to source actionable insights?  In this series of keynote articles I explore how the coming together of mobile computing, innovations in customer science and advances in big data analysis are creating the perfect storm for marketers in motor retail.

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