Customer Science in Motor Retail: 5 Actionable Insights That Every Dealer Should Have

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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Keynote 3.

5 Actionable Insights That Every Dealer Should Have

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 are the top 5 actionable insights that every motor dealer should have?

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Motor Dealerships are a complex multi-disciplinary business operation.  The aspects of activity are so many and varied that managing performance and growth requires a clear head and clarity over the objectives that really matter.  Every dealership has a different combination of capabilities and franchises that add an extra layer of ‘uniqueness’ to the reporting systems required.  So is it possible to pinpoint just five actionable insights that all dealership exec teams should have access to?  I believe it is.  In this article I suggest my top 5 list of actionable insights together with an explanation of why they’re important.

1. Consolidated Performance Scorecard

A scorecard is a dashboard that incorporates a series of objectives that an organization is striving to achieve.  In most organizations the number of objectives defined in a scorecard is in the order of 12-16 as any more becomes unmanageable.  A consolidated performance scorecard provides a topline view of progress towards business outcomes.  It’s essential for any organization to know how it defines success and seek to achieve it.  Scorecards are therefore valuable and useful management tool to articulate and communicate progress towards strategic outcomes – BUT… the point about objectives, and the key performance indicators used to measure progress towards them, is they should be ‘stuff’ that managers already know to be important.  This type of reporting is therefore ‘handy’ but it would be difficult to argue KPIs are ‘actionable insights’ as they rarely encourage managers to take action in themselves.  What starts the journey of objectives and KPIs becoming ‘actionable’ insights occurs when managers can drill-down into the data that is the source of the KPI.  When managers drill into data and ‘become curious’ the magical and mysterious kapow! explosion happens that leads to processes being improved, new initiatives tabled and the like.   A Consolidated Performance Scorecard gives the entire management team a snapshot of how THEY are performing to meet strategic outcomes.  It’s my FIRST actionable insight because it STEERS the ship.

2. Consolidated DOC Side-by-Side Dealership Analysis

The Daily Operating Control is a report that summarizes how each revenue generator and discipline of a motor dealership is performing.  What normally gets covered are the revenue generating pipelines of the dealership including MOTs, parts sales, red and amber Vehicle Health Check (VHC) / deferred works, service hours, warranty repairs, oil, tyres, bodyshop repairs and more.  Most dealers I know favor a side-by-side analysis of branch performance because it encourages competition – and the comparison between franchises and dealerships makes for interesting reading (to understand which business units are performing well, which are performing poorly, all judged on the same scale given that organizations commonly struggle to compare performance between business units when managers seek to qualify ‘what good looks like’ using their own scale.  The Consolidated DOC gives managers across the business a daily progress report and a month-to-date summary that provides opportunity to correct sub-optimal performance before it’s too late.  It is the epitome of ‘actionable insights’ in the operational reporting world and becomes my SECOND ‘must-have’ actionable insight for dealerships.

3. Customer Persona Profiling Summary

It’s always been important to manage customer relationships one customer-at-a-time as Don Peppers andMartha Rodgers put it but as customers become ever more distant and empowered, the need to build digital personas has moved on to a new level of priority.  I’ve struggled to understand why the Motor Retail industry has been so slow to adopt customer profiling and persona building when retailers such as Tesco with their Clubcard system and online companies like Amazon have so clearly demonstrated the business rewards, but I do see this initial reticence is changing as more dealers become ever more aware of the potential to boost growth by simply harvesting their most important asset – their customer relationships. There are many sides of a customer relationship – communications preferences, activity history, contact points, location, buyer behavior, life-time value, future life-time value, affluence… - and it’s when you combine these views that exciting things happen.  There are many ways to build personas and through them, marketers and sales leaders see patterns of likes, spend habits and relationship characteristics that lead to new campaigns and better ways of sourcing customer value.  A customer profiling persona summary presents a one-page view of the many different facets of your customer community.  It covers not just ONE customers’ characteristics but overlays ALL of your customers in one ‘map’ of your customer universe.  It makes for very interesting reading and becomes my THIRD actionable insight.

4. Customer Happiness Index

Customer happiness matters because it’s the lion in the cave that comes out to bite your business unless you keep an eye on it.  There are many ways organizations can measure and monitor customer happiness but dealers can still struggle to place a ‘happiness index’ on their business that produces a snapshot of happiness and trending.  In addition to manufacturer sponsored analysis, many dealers are creatively sourcing happiness data by using simple tools on their websites and paying third party.   I’m also a big fan of soft-measures that systems like www.tag-check.com are excellent at sourcing.  You can’t hope to buildLoyalty Beyond Reason when your customers are unhappy; it’s even a big call to ask for respect(sometimes described as love in plain clothes!).  Installing a customer happiness index is my fourth actionable insight.

5. Mapping Customers and Qualifying Addressable (Local) Market

Understanding the opportunity of a dealer within their locality helps to qualify how well a dealer is doing compared to how well IT COULD be.  It’s not difficult to plot customers on a map.  In countries like the UK and the Netherlands mapping customers is made easier by the quality of the postcode system.  In other countries like the United States and South Africa, postal codes are not very accurate and it takes street address details to accurately plot customers (far less convenient!).  Once customers are plotted it’s relatively easy to assign customer attributes to records so map views can be filtered by dealership, sales team, sales person, affluence, persona, outstanding MOT reminders – whatever.  If your customer records include a CAMEO (‘affluence’) profile, companies like www.improvemydata.com  make it pretty easy to obtain a listing of similar customers in your region.  This makes it possible to understand your MARKET SHARE! How cool is that?  Maps are great!! I’ve never produced a mapping application that hasn’t shownsomething interesting for dealers to see.  That’s why creating a map view of the customer landscape and qualifying the addressable local market is my fifth actionable insight that every dealer should have access to.

The list above is MY top five.  If you have other opinions or examples I’d be very interested to hear about them!

Real-Time Data Diagnostics - How Encanvas Takes Agile To A New Level

Have you ever created an application only to find it doesn’t work?  

Sounds crass doesn’t it.  The fact is that most manually programmed applications have errors in them.  But modern codeless applications design environments like Encanvas overcome the majority of programming ‘hick-ups’ by auto-generating the code that underpins authored applications through the use of drag-and-drop, point-and-click and wizard based interfaces.   That means almost no testing, tuning or re-working costs for business IT projects.

This is important to the software and data integration industry that has a pretty sour track-record of project delivery.  The article ‘Why Your IT Project May Be Riskier Than You Think’ by HBR (November 2011), that followed a survey of 1,471 IT projects with an average spend of $167m, found that:

• The average overrun was 27%
• One in six of the projects studied was a black swan, with a cost overrun of 200%.
• Almost 70% of black swan projects also overrun their schedules.

One area that has remained to challenge the software development industry has been how to overcome data integration errors on deployed applications.  No matter HOW a design environment links to data sources, such is the complexity of the task that it becomes almost inevitable that some data integration errors will creep in when developing a complex database-centric application.  For example, a field in a table could be re-named or deleted in the source database resulting in no data appearing on the published site page because the database is unable to find the requested data.  Sometimes it’s quite easy to track down these issues; other times – with complex applications – it takes a pretty neat understanding of the application and how the data hangs together in order to overcome the issue.  When applications designers have spent hours working on a great application, the very last thing they need is to fall at the last hurdle and find ‘the app doesn’t work’.

Thankfully, Encanvas now overcomes this problem area too with its new real-time data diagnostics technology.

Those familiar with Encanvas will know that the design of applications all takes place in ENCANVAS CREATE DESIGN STUDIO in a codeless environment.  It offers design elements, data linking and action linking features to build content and logic into applications using an easy to learn design interface that has the look and feel of a desktop application. What it actually produces are cloud deployed ASP.NET portals that present data in HTML so they can be used on desktop, tablet. Mobile and digital TV platforms.  While it adheres to Microsoft Enterprise Platform standards of security, performance tuning and scalability, it removes the use of programming and means application can be authored in workshops with users and stakeholders.

When applications are published to the cloud, Encanvas’s new visual diagnostic mode allows designers to review the data connections employed in applications using an innovative visual referencing system.

Each field is audited for its data connections and the results are presented on the screen.

Full details of connections are presented when clicking on the associated icon. Using the live data diagnostic features of Encanvas removes the last major hurdle in applications engineering for authors of business applications.

The roll call of applications authoring productivity features in Encanvas now includes:

• Codeless platform and server installation
• Codeless private cloud creation (and replication)
• Codeless data connectors
• Codeless information flow automation
• Codeless data mashup and automated data structure creation
• Codeless design elements
• Codeless logic link creation
• Codeless action layer automation
• Codeless KPI creation
• Codeless map creation
• Codeless upload/ETL automation
• Codeless download (export) with formatted reporting/printing
• Codeless social network creation
• Codeless graphing (and graphing logic) creation
• Codeless email workflow creation
• Codeless publishing
• Codeless UI design 
• Codeless federated user identity management augmentation
• Codeless site structure design
• Codeless and real-time data diagnostics
• Automated design element creation from data structures
• Automated database creation from designed data structures
• Automated lookup table generation
• Automated form creation

If you’ve yet to try Encanvas, it’s easy to arrange. Simply email sayhello@encanvas.com and request a secure private-cloud Remote[Space] to have a go at codeless situational applications authoring for yourself.

Big Data Training Workshop 1: Introducing Situational Applications

BIG DATA TRAINING WORKSHOP 1: INTRODUCING SITUATIONAL APPLICATIONS

Situational Applications are any software applications designed to serve the long-tail of demand from individual information workers (or small communities of workers) for ‘better ways to analyze data, capture it and act on it’.  They may be created for a moment and then discarded, or later adopted and absorbed into enterprise systems.  Sometimes they are unkindly described as throw-away or experimental applications but I prefer to think of them as the first step on the accelerated business innovation journey.  They are key to the world of BIG DATA because they are the tool-kit to apply learning lessons from data and turn it into better ways of working.

I’ve had such overwhelming feedback and interest on the Big Data Situational Applications articles I’ve penned that it’s encouraged me to write a few more that walk through how we use Encanvas to assimilate data from various sources, analyze it and act on what matters.  Of course there are a wide variety of Encanvas partners and solutions providers that offer ‘off-the-shelf’ industry solutions so in this series of articles I’m assuming that the application is something ‘custom’ or new that hasn’t been addressed before.

In this series of articles I plan to include the following topics:

1. Introduction to situational applications 
2. Data assimilation: what it is and how to do it
3. Operational Analytics: making sense of data with useful tools
4. ACT: designing apps to iterate processes one canvas at a time

The obvious article that’s missing is a training course on HOARDING technologies like Hadoop, Microsoft Business Intelligence, SAP hana etc.  The reason I’ve missed this step is because (a) I don’t know anything about it and, (b) In many cases you don’t need to hoard data and organize it before creating situational applications.

Just a few brief introductions before we start…
If you’ve not encountered Encanvas software before, it’s basically a business computing platform designed to exploit data held in different places and different formats by designing situational applications to analyze data and apply learning lessons. Unlike business intelligence systems and other platforms that HOARD data and create a data warehouse before you can do anything, Encanvas connects to, and organizes data into new structures by exposing data to designers in a consistent format to enable ‘drag and drop’ selection and formation of new data structures.  It’s really easy to use for business analysts, and it produces results quick, so it’s realistic to develop situational applications in workshops with stakeholders, users and sponsors present (yes really!).

Companies like USTech Solutions, NDMC Consulting, Ambridge Consulting, Nybble, SovereignTech and others use Encanvas as a tool-kit to author situational applications as a service.


Everything you wanted to know about situational applications but were afraid to ask
The first ever situational application platform was the spreadsheet.  Times are changing.  Information workers need to deal with much bigger data sets and IT leaders must ensure that data is organized, always-secure and any software application must adhere to necessary standards of governance and compliance.  The new generation of situational applications platforms like Encanvas are engineered to meet ‘IT hygiene standards’ of security, performance and scalability, yet they provide unrivalled self-service tooling to enable web workers to fully exploit accessible data resources.

History
Encanvas was conceived in 2002 by the founders of NDMC Consulting.  It was initially an idea (perhaps a belief) that in future, business users would seek to work in social groups that would span across and beyond enterprise boundaries and, having experienced this new form of business workplace, key knowledge workers and creative contributors to business processes would seek to be able to author applications for their communities in a form purposely sculptured to the needs of the community of use.

This idea of socially-centric, built-for-purpose and potentially thrown-away software was unknowingly endorsed by technology thought-leader Clay Shirky in his essay ‘Situated Software’ published in March 2004 when he wrote, “Part of the future I believe I'm seeing is a change in the software ecosystem which, for the moment, I'm calling situated software. This is software designed in and for a particular social situation or context. This way of making software is in contrast with what I'll call the Web School (the paradigm I learned to program in), where scalability, generality, and completeness were the key virtues.”

In August 2007, Luba Cherbakov and a team from IBM wrote the first of two articles on what they described as ‘Situational Applications’.  In their paper titled ‘SOA meets situational applications, Part 1: Changing computing in the enterprise’, Cherbakov and her colleagues defined the attributes of Situational Applications, stating, “The loosely accepted term situational applications describe applications built to address a particular situation, problem, or challenge. The development life cycle of these types of applications is quite different from the traditional IT-developed, SOA-based solution. SAs are usually built by casual programmers using short, iterative development life cycles that often are measured in days or weeks, not months or years. As the requirements of a small team using the application change, the SA often continues to evolve to accommodate these changes. Significant changes in requirements may lead to an abandonment of the used application altogether; in some cases it's just easier to develop a new one than to update the one in use. The idea of end-user computing in the enterprise is not new. Development of applications by amateur programmers using IBM Lotus® Notes®, Microsoft® Excel spreadsheets in conjunction with Microsoft Access, or other tools is widespread. What's new in this mix is the impressive growth of community-based computing coupled with an overall increase in computer skills, the introduction of new technologies, and an increased need for business agility. The emergence of Asynchronous JavaScript + XML (Ajax)—which leverages easy access to Web-based data and rich user interface (UI) controls—combined with the Representational State Transfer (REST) architectural style of Web services offers an accessible palette for the assembly of highly interactive browser-based applications.”

Today
Situational applications remain a largely misunderstood concept in enterprise computing due to pre-conceived notions about how IT works that are now proven to be fatally flawed.  These include:

• Applications that can be designed cheaply enough to ‘throw-away’ can’t possibly be expected to meet enterprise data integration, security, performance and tuning expectations.
• It’s not possible to create the critical-mass of building blocks and tooling required to remove the majority of programming overheads.
• Organizations are better off buying best of breed solutions, to then mackle them together.
• There is no competitive advantage to be gained from IT as companies now use the same platforms. 
• If players like Microsoft, Google, Oracle and IBM haven’t made it work then it isn’t possible!

In many ways the demand for situational applications has never gone away but, until the emergence of the BIG DATA story, the message of Situational Applications has struggled to find a voice within organizations as it is a genre of technology designed to meet the many and varied ‘small’ needs of a variety of communities. It has lacked any understandable clarity of purpose in IT architectures.  Instead of sourcing expert tools, CIOs with other things to think about have instead done their best with 'approved enterprise tools' – Content Management applications like Microsoft SharePoint and Enterprise Applications Platforms like IBM Websphere and Oracle Weblogic.

BIG DATA has led to the re-discovery of the important role of expert situational applications tooling as organizations acknowledge the need to equip analysts and middle-managers with self-service, community-centric applications to assimilate, analyze and act on the actionable insights they’re surfacing.  Technologies designed support the creation of Situational Applications are by necessity ‘codeless’ which means the authoring of applications is done using drag and drop, point and click or wizard based interfaces that automatically generate the programming code rather than it being authored ‘manually’.  This reduces errors in code.  It also means that applications can be authored in near real-time; very often within a workshop environment.  Having stakeholders directly engage in the authoring process creates better applications in a shorter time.

In the next article in this series, read about the first stage in Accelerated Business Innovation: Data assimilation: what it is and how to do it.

BIG DATA with Encanvas (infographic)

In this infographic I explain how Encanvas employs big data as its raw material to accelerate the pace of business innovation.  Of course, data doesn't have to be BIG to be useful.  Over the last 10-years I've seen many good ways of extracting value from data by simply having more data of different types accessible to business analysts. For example, one professional services company was able to improve their presentation of credentials by exploiting data from a third party database to enrich their customer records and map their customer records onto their project data to build a richer understanding of what they'd delivered (how and to whom) to improve the quality of their case stories.

Accelerating the pace of business innovation requires not just the means to harvest data and analyze it - businesses ALSO need the tools to improve their processes and embed learning lessons into their day-to-day activities.  This is by far no mean feat!

Encanvas overcomes the natural reticence of organizations to change, break age old 'norms of behavior' and embrace better ways of working by creating applications without asking organizations to invest in IT infrastructure or spend days, weeks or months on IT projects with no clear ROI.  Building a situational application in a day or half-day workshops session means that businesses can understand the value of data - and apply it - removing the risk and cost of process change.

Speaking to users of Encanvas, they will very often rebuild apps many times as they learn from their data and re-apply learning lessons to improve processes.  This would not be practical or affordable if a traditional software development or enterprise platform like Microsoft SharePoint was used to fashion applications.

The original infographic can be viewed on slideshare here.

Profit from BIG DATA: Using actionable insights to accelerate business innovation

Actionable insights are those that make managers and workers 'curious' and cause them to act. The big data revolution is giving organizations many more reasons to exploit data so they can improve customer experience, personalize offers, improve sales engagement methods, optimize processes and surface BLUE OCEAN opportunities.  Even your existing data that's locked away in back-office systems can become extremely value when combined with other data to answer new questions. But what PROCESS do you need to harvest actionable insights and act on them to accelerate the pace of innovation in your business?

In this article I've summarized the obvious 5-steps to turning sleepy data into (first) actionable insights and (then ultimately) better processes using big data cloud computing and operational analytics technology.  Then I've explained the 2-step process (yep just two steps) that Encanvas makes possible. While the example below is based on the capabilities of the Encanvas platform because we're familiar with it at NDMC there are other technologies from Tibco, IBM and Oracle that you could also consider to achieve the same outcome (though this is probably an 'IT' project if you do).

The reason we developed and continue to use Encanvas at NDMC is because it produces the fastest time to value by reducing the number of steps in the Accelerated Business Innovation process - and it deskills the activity of process innovation so you don't need to be an IT expert or programmer to implement it.

A typical 5-step innovation life-cycle process using a mix of enabling tools is:

1. Capture Data -  2. Hoard Data - 3. Harvest/ETL - 4. Analyze -  5. Act

This can be a long-winded and technically challenging process: It requires a different bit of software for every stage, and this results in large IT teams, expert skills and slow time-to-value projects.

Why 'Acting' on actionable insights is like exploring for oil
The accelerated business innovation process is modeled around oil exploration where you first make sure you've hit oil before you start to build infrastructure.  This means that when actionable insights surface a better way of working, the solution is to create a situational application (at little or no cost) to validate the process change.  If the new process works better and provides incremental value then it is adopted, if not, it is discarded.  That takes a new approach to IT and new tools. The most challenging part of adopting an accelerated business innovation process using legacy enterprise software is therefore the 'ACT' bit.  Adapting legacy platforms like Oracle, SAP and Microsoft Dynamics is more akin to turning an oil tanker - really difficult and expensive:  It requires IT people with deep skills.  That's why we use Encanvas to serve the long-tail of situational applications that are used to 'explore' value and then adopt those applications that prove valuable as a layer that sits above the fragile 'heavy-lifting' enterprise software that most businesses operate today.

1. Assimilate data

Data assimilation describes the task of bringing together data to a level of consistency and completeness that makes it useful.  The term means more than simply harvesting data - because anyone who has tried to bring data together from different sources (even using a spreadsheet) knows how time consuming and painful it can be to extract, organize and structure data.  Fortunately, tooling is available nowadays to automate many of these very manual tasks.

Many people assumption - probably due to the norms of behavior encouraged by decades of data warehousing - that it's necessary to hoard data and organize it before you can start to lever insights from it.  Nope.  Today, the data harvesting, data source integration, data augmentatation and normalization tools are so powerful that most operational analytics systems can 'get at the data' wherever it is and exploit it without having to first HOARD the data in some great big massive repository that you have to pay for.   (That said, if you do want to hoard data, technologies like Hadoop have made the task of hoarding data of different forms immeasurably less expensive and more scalable.)

Encanvas, and technologies like it incorporate a full range of data connection and ETL tools that obviate the need to code or use lots of APIs and middle-ware tools in order to harvest data.  It supports data integration with CCTV, security databases, hardware, sensors and telematics.  Whats more, it enables situational applications designers to exploit structured data (like relational databases, web services, CSV files etc.) and unstructured data (such as PDF documents). Their Information Flow Designer application gives applications designers the means to formalize data gathering workflows from data sources, transform, cleanse and normalize data - and then expose it for operational analytics applications like Encanvas Create Design Studio to exploit.

One thing we realized at NDMC a decade ago is that authoring exploratory (situational) applications to source actionable insights requires designers to play-around with data, forms and logic tools - all the toys needed to create exploratory apps in the same integrated design environment. That means you need the data sources to play around with too.  Encanvas allows us to try things out, get things wrong and work with stakeholders until we get a result.  Assimilation of data is tricky, sometime painful and rarely straight-forward!

2. Create and Deploy Situational Applications

Sourcing actionable insights normally means connecting to many different data silos and exposing the data held within them.  The 'clever bit' that technology can help you with is to bring data together in new ways, to then formalize business processes to act on it.

This 'iteration' of the enterprise computing environment requires to perpetual creation of situational applications that serve individuals or small communities of users that traditional IT can't service because this long-tail of demand is simply too long to be addressed by technology platforms that need coding - and users have such a diversity of requirements for tooling.  While there is a natural instinct to employ existing tool-kits like IBM WebSphere, Microsoft SharePoint or applications platforms like Force.com, art NDMC we foudn this to be a costly approach because it requires large IT teams and the tooling is limited by the capabilities of the platform. None of these enterprise platforms were engineered for the purpose of authoring situational applications and so IT people find themselves knee-deep in APIs, forms and database programming projects and third party data analytics and data source connectivity tools.

Using built for purpose environments like Encanvas, situational applications are created in a codeless integrated design environment. We use the same environment to author operational analytics as we do actionable applications - and very often an exploratory application for operational analytics can be progressively extended to become a key part of the enterprise operating environment.

In the normal course of an accelerated business innovation project, stakeholders will start by creating operational analytics applications to analyze their data.  Then they will create applications to ACT on the results of the 'data analysis' exercise.

When data does not exist, new applications are authored (for desktop, tablet or mobile devices) to capture data.  When authoring such applications it make sense to control the quality of data input wherever possible by adopting the use of drop-down choice fields, radar buttons,check boxes and check-lists. When working with Encanvas, even applications used to capture data can be 'situational'.  Very often these applications are eventually absorbed by 'platform' systems like Microsoft SharePoint, Oracle and SAP.

How long does it take to execute an accelerated business innovation project from 'concept to completion?
After a decade of examples we know that the answer depends on a number of factors:

1. The size of a project - Smaller projects (i.e. Something akin to displacing the use of spreadsheets for analysis of audit and accounting processes) can be actioned within a day, sometimes two.  Large projects take significantly longer.  When we've employed accelerated business innovation to upgrade a regional transport system, enhance an eLearning system, install federated risk or compliance across a business - that sort of thing - it normally takes around 6-weeks to get through the situational applications phase and move on to User Testing or 'embedding' the technology deployment into the enterprise platform.  While 6-weeks is a long time it is nothing compared to traditional IT projects that span many months, sometimes years.

2. The change methodology - We are supporting a change process and so inevitably HOW you run a project will impact on the pace of achieving outcomes. An NDMC we've created a Computer Aided Applications Development methodology to support accelerated business innovation projects.  This combines the 'good thinking' found in Outcome Driven Innovation (ODI) and Blue Ocean strategy mapping in addition to a few other methods that are unique to our approach.

3. The tools - If you're using a codeless and complete situational applications design environment like Encanvas Design Studio then 90% of the programming, testing and tuning overhead authoring process is normally removed from the exercise - and stakeholders can contribute to workshop-based developments.  This speeds up the innovation process because project leads can achieve an outcome during the course of a 3 or 4-hour session rather than just creating 'a list of things to complete'.  If you are required to use tool-kits like Microsoft SharePoint THEN YOU CAN still achieve great results but it does mean you will need a dozen more IT people to support the process.

I hope you found this article on accelerated business innovation interesting.  Do let me know of your own experiences.

Ian.

BIG DATA - The Killer-App for Motor Dealerships

BIG DATA is a big topic at the moment in IT... and that interest is gradually working its way down the corridor to the marketing office and the boardroom.

In the Motor Retail industry new IT innovations emerge somewhat slower than other verticals because many dealers rely on partner suppliers to manage their IT.  This creates a bit of a lag in adoption of new technologies.

I doubt it will be long however before the topic of BIG DATA filters into motor dealerships because the competitive advantage it brings is compelling.  Another reason why BIG DATA technologies are likely to take off so fast in this market is because there is pent up demand in dealerships to 'get moving' with innovation.  Many of the Dealer Management Systems employed today are WAY behind the curve on technology - some are not even based on web technologies.  The fragmented information environments that dealers have to cope with day to day are embarrassing to anyone in the computer industry (on behalf of all us nerds in the software in 'sorry guys').

At NDMC we're leading the charge to introduce BIG DATA solutions into the Motor Industry and the level of interest and take-up has been rather overwhelming.  In this presentation I've provided a short summary of the role and impact of BIG DATA for anyone who's yet to encounter the technology.

I hope you find it informative and a little fun! I.

BIG DATA - The Killer App for Motor Dealers from Ian Tomlin

Bloomberg interview with CEO of APT exposes BIG DATA value benefits

This is an interesting propaganda story by APT - interesting how US companies get so much air-play for things that UK companies like Dunn Humby have been doing for years ;-)

What's more interesting to me is that APT's perspective on what Big Data 'is' is so similar to NDMC's description of Data Investment Management with its end-to-end process life-cycle of discover data, interpret it and act on what matters.

I.