Marketing the IoT (Internet of Things) – A Major Value Challenge

Marketing the IoT (Internet of Things) – A Major Value Challenge

In the May 7, 2013 “Harvard Business Review” article Stephan Ferber said:

For “Old Economy” companies, the mere prospect of remaking traditional products into smart and connected ones is daunting. (My own company, for example, the Bosch Group, produces over half a million things each day across more than 1,500 product categories.) But embedding them into a services-based business model is much more fundamentally challenging. The new models have major impacts on processes at the corporate center such as product management and production and sales planning. And given the dynamism of the net, the innovations will have to come more quickly. 

A December of 2015 iianalytics.com interview with Jason Mann, Director, Industry Product Management at SAS, confirmed the challenges of turning the IoT into a business still is a major hurdle:

I’ll start with the disappointment, which is the overall rate of progress to date.  Gartner currently list IoT initiatives at the top of the “hype cycle.”  There’s a tremendous amount of buzz, and every event you go to has IoT on the topic list.  Yet when you dig in and talk to people about the next level of understanding, about plans and initiatives underway, and about results to date, you find that most companies haven’t gotten very far.”

While he goes on to say he is starting to see some IoT pilots with returns exceeding expectations, turning the IoT into profitable businesses is still elusive. 

As we enter 2017, the challenge seems to be even more daunting.  Manufactures are generating more data flowing off their machines and making efforts to capture and analyze that data, but there is a gap in turning what that data is telling into viable business models, particularly for established manufacturers and their channels.

Nowhere is this more prevalent than in the construction and agricultural equipment markets where data is being collected almost real-time from machines that are operating in the field.  Precision guidance systems are being turned into viable revenue models in both construction and ag, but companies are finding it very difficult to create additional revenue streams and profitable business models that take machine data, combine it with analytics and turn it into something meaningful for their customers.

It’s not because they aren’t trying.  Every major equipment manufacture has substantial initiatives around the IoT and data flowing off their machines.  But, the business models are elusive.

This is a classic example of a complex go-to-market problem; how to create and capture value in a market with changing products / services and evolving business models.  This is not the domain of the successful equipment manufacturer.

They are successful because they operate in the realm of the known and they possess more intellectual capital – knowledge and experience – than their customers or channels.  As such, they have been able to build structured sale and marketing organizations and dealer networks that are very good in doing what the manufacturer believes needs to be done.

Manufacturers have been very good in this market leadership role in slow changing markets.  They had the time to learn what worked and then to translate that into products and channel marketing programs, even programs as structured as franchise operations guides.

It’s just that in the IoT world, manufacturers have only an idea of what they would like to accomplish, not how to do it!  Their own sales and marketing management models just won’t work in this new world and it’s because of the rate of change in the technology and its explosion across products and customer segments.  Almost anything can be linked to the IoT.

The table below shows the challenges marketers face as both the rate of change and the number of segments increase.

The four cells of the table, C1 – C4, represent different marketing scenarios.  In C1, there is little change and only one market segment to address. In this scenario, the marketer plays a strong role leader, setting the rules of operations for his channels.  As the number of segments increases in C3, the marketer can continue to play the market leader role, but has to devote the resources necessary to do this in multiple market segments.

Cells 2 and 4 represent the challenges of rapidly changing technology.  In C2 the manager can play the role leader as long as he can focus on one technology application and market at a time.  To be successful, he has to understanding the application and be able to teach his channels to successfully capture and serve this segment.  John Deere’s use of technology for the specific application of precision planting is an example of how a marketer can focus its resources to gain market leadership and teach its channels how to succeed in the application.

C4 is the most complicated space.  Here the technology is impacting multiple market segments at the same time and in different ways.  As a result, learning becomes much more difficult for manufacturers and they risk falling further and further behind the market learning curve.  The internet of things falls into this space, as most marketers are struggling to figure out how to create value from all the data they are harvesting.

In cell C4, the result is that marketers are failing to effectively lead their channels – because channel leadership doesn’t work.   This has led to tentative, faltering, and even stagnant technology adoption which is opening the door to new types of competition.  These new competitors are disrupting markets and often weakening existing competitive positions in the market.

QDI’s two recent white papers, “Are your channels failing?” and “Are you failing your channels?”  address this same fundamental challenge.

Product and marketing technology are moving faster than manufacturers and channels know how to integrate them into their businesses.

If you expect to be a winner in this space, then you need a different channel management model and need to apply a different learning model to these channels.

Focus on Rapid Learning

As the “Requirements for Success” table shows below, the requirement for channel management strategy and processes in cell C4 are radically different than those in cells 1 and 2 which are low change markets.  Flexibility, information exchange, broad role definitions and tolerance are the cornerstones in cell C4 – a multi-segment, rapidly changing market.

Channel Management Requirements for Success

As the table below, “Impact of Change and Number of Segments on Channel Management” shows, channel management activities need to change to be successful in cell C4.  You need to move from a highly authoritarian position (explicit roles and measurements) to a collegial position.

This may be too big a change for your sales management team.  Putting in place a specialist group with different sets of incentives and measurements may be required.  The old tools just won’t work and the exiting sales organization may not know or have the interest in learning how to be successful in this new space.  They are much more interested in making money in the space they are in.

Take a look at your IoT go-to-market strategy.  How clearly defined are your business models – how you and your channels make money from this IoT product / service?  What channel management model are you using?  Are you off course?

QDI Strategies has helped clients navigate the emergence of enterprise information and management systems in factories, hospitals, education and now is helping companies manage the evolution of information management – the use of data to make decisions in the rapidly expanding IoT universe.

If you want to talk, contact:

Steve Bassill – sbassill@qdistrategies.com

Mike Barr – mbarr@qdistrategies.com

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