The IoT – high ambitions, slow conversion: What’s going wrong?

The 4 most common strategic responses and why they don't always yield the expected results

Today, one could say the IoT has successfully proliferated and by now it is almost the exception if there is still an industrial company out there that is not concerned about the Internet of Things (IoT). According to a recent Gartner survey, 75% of industrial companies had already invested in IoT projects by the end of 2018. Before 2018, the figure was <25%.

However if you ask around among the IoT managers of those companies, each of them has the feeling that they are "behind" and do not believe that they are making progress as fast as they should in order to remain competitive.

Today, one could say the IoT has successfully proliferated and by now it is almost the exception if there is still an industrial company out there that is not concerned about the Internet of Things (IoT). According to a recent Gartner survey, 75% of industrial companies had already invested in IoT projects by the end of 2018. Before 2018, the figure was <25%.

However if you ask around among the IoT managers of those companies, each of them has the feeling that they are “behind” and do not believe that they are making progress as fast as they should in order to remain competitive.

In many places this has the effect of companies trying to “catch up” by starting many individual projects at the same time. Barely leaving time to set up a common strategic direction and long-term vision in advance. Innovation departments (aka Innovation Labs, Corporate Innovation Units, Digital Accelerator or similar) are seen as a way out of this dilemma and supposed to generate ideas in record time, set up projects and implement them as pilots.

If these individual projects then do not bring in enough money quickly enough, they are stopped in large numbers. Especially if there is a lack of traceability of how the individual projects contribute to the overall success. These projects are regarded as failed individual projects and not as steps in the companies’ transformation. What is the reason for this?

The recurring patterns in the majority of cases that I experienced during my time as a consultant and as a manager, increasingly lead me to believe the biggest reasons are: sweeping strategic reactions and missing or hastily defined IoT visions, mostly due to lack of time or fear of megatrends.

Strategic blanket reactions and how to avoid them

Let me try to summarize what I have observed as being the 4 most common strategic reactions of IoT managers in industrial companies and why they don’t always bring the wished-for results.

Response 1: Our core business is losing differentiation, we need IoT to remain competitive (“commoditization” response)

This reaction is probably the most typical for industrial companies. For traditionally product-driven companies it is a natural reaction to see IoT as a way to enhance and “upgrade” their products with additional (digital) value-add. Also culturally, this reaction is easiest for industrial companies to digest. IoT services are sold as add-ons or as part of the product and are therefore mainly used as a sales promotion lever. This means that hardly anything changes in the sales and development process.

IoT as “digital add-on” – the convenient way

However, it is also the strategic response that generates the least additional revenue. If the scope of IoT is limited to the refinement of its products, the sales potential is limited to indirect sales (especially pull through from product business). The direct monetary impact and thus the return on investment for IoT projects are difficult or impossible to measure and often negative if one considers the high investment against the additional revenue in the first 1-5 years.

This reaction usually initially triggers “open ears” in management boards and leadership teams, but increasingly fails in the implementation phase due to negative or unverifiable business cases.

Often completely forgotten in this reaction are the internal efficiencies, although these are currently still the biggest driver for profitable IoT business cases. Does your business case already include production and quality optimization or service and product optimization? In successfully implemented cases in larger industrial enterprises, the savings easily amount to two to three-digit million figures per year. There is also significant unused potential for small and medium-sized companies.

This reaction is also often coupled with the belief that customers are not willing to pay for additional services. Based on the experience that it is becoming more and more difficult to keep prices or even more so to enforce price increases in hardware and component sales, there is often the feeling that selling additional services is difficult or close to impossible.

This reaction thus leaves the two largest direct value generators in IoT – internal efficiencies and monetization of value-added digital services – unused.

Response 2: We must become THE platform provider for our industry (“lock-in” response)

At present, proprietary protocols and standards are still widely used, especially in asset-intensive industries (such as automobile production or energy supply) or traditional M2M industries (such as ATMs or telecommunications) due to historically large installed base. Here, many companies are accustomed to being the market leader in their field and are used to market shares of >15%.

Striving for market dominance

Many industrial companies then start their IoT strategy with the ambition to have at least 15% market share in their industry. Considering that there are currently 400+ IoT platforms in Europe alone and that Amazon Web Services (AWS) and Microsoft Azure share >50% of the IoT Platform as a Service (IoT PaaS) market, it is clear that this ambition is completely unrealistic, especially in the short term and for smaller industrial groups. In comparison, even the market shares of tech giants such as IBM, Microsoft or SAP are <10% in most IT markets, with average market shares of around 1%.

The investment and global structures required to offer an IoT platform worldwide are also often underestimated. The sad reality is that lonely teams of 10 – 50 developers try to build an IoT platform for the market of their parent company. All too quickly it becomes clear that there is a lack of hands and skills to build an “Enterprise-Ready” platform. The teams are often overwhelmed to deliver security requirements, scalability and usability in the quality required for such a platform. The operation and costs of such a platform are often not even thought about in advance.

From a cultural and sales point of view, this reaction represents a drastic change. Will the distributors of the industrial groups, who have mostly sold hardware products all their lives, sell the IoT platform or will a new worldwide force of distributors be established? And how does this compare to the 30,000+ Microsoft and just as many AWS sales representatives who are on the road worldwide?

Response 3: Data is the raw oil of the 20th century – We must secure data ownership to gain competitive advantage (“Data Ownership” Response)

Similar to reaction 2, it is a tempting conclusion that one only needs to hire a few data scientists to generate valuable insights from the data of the above mentioned devices.

The deceptive thing about this reaction is that the first pilots seem to prove exactly that. The customer seems thrilled that the pilot has pulled valuable data from the connected devices and the data science team proudly presents the first results, which may even lead to significant savings. The first results are presented to the board and the IoT project seems to be successful. But what happens after the pilot?

The future of IoT is open

As other network and cloud trends have already shown, the trend is towards open systems. IoT and AI will most likely only be able to realize their full potential if work is done in ecosystems and data is exchanged via open interfaces. It is already becoming clear in the first industries that customers will only accept open interfaces in the long term. Those who resist will sooner or later realize that customers do not want to be ‘locked in’. However, this also means that the trend will likely move away from data ownership towards partnerships for the value-added processing (Data Value Add) of data. The party that can process the data in the most meaningful way (e.g. through domain expertise or more sophisticated AI systems) will be the one who gets the most out of it. The future of IoT thus will in all probability be determined by partner networks. It can already be seen that companies that actively participate in IoT are more successful. A recent survey predicts that the number of partnerships in Europe will more than double by 2022.

Response 4: IoT is changing business models – we must offer ‘as a service’ (“XaaS” response)

Rolls Royce has shown the way and the keynote speakers of the world will never tire of repeating the same examples. But is “XaaS” (Everything as a Service or Result as a Service) really the solution for every use case?

At first glance, this reaction seems absolutely correct and takes up many correct aspects that make IoT the pioneer it is. It becomes dangerous when companies try to transfer the strategic idea 1:1 to their business.

What is absolutely important and right in thinking like this is that IoT enables us to sell our customers added value rather than just a product. For example, thanks to IoT, a construction equipment manufacturer is able to invoice its large machines per hour. The customer literally buys “the hole in the wall” and only pays for the time spent. The customer’s problem and its solution are clearly at the center of attention, recurring sales and the long-term monetization of the overall solution are the right basic ideas of an IoT market strategy – but is a “as a service” model really the right model for your chosen target market?

Change for the sake of change?

At first glance, a XaaS model sounds interesting for many customers, as they do not have to buy expensive products and the default risks, guarantees, etc. are borne by the provider. So this model is convenient for the customer. For the company offering the service, on the flip side any ‘as a service’ model means that it does not sell its products directly, but instead have to be shown on its balance sheet and the company bears the full capital risk. Here, many companies already fail due to their own internal financial processes.

It becomes even more difficult if customers (especially their purchasing department) are not yet prepared to implement such models. Many are afraid of a ‘vendor lock-in’ or of paying more in the end.

The main criterion for or against XaaS should therefore always be the additional customer value and sales through IoT from the provider’s perspective. Or will the new business model possibly only bring about changes in payment methods? If you understand the customer problem and can grasp the added value, you have everything you need to set up profitable XaaS models.

So why does it work in the above example of the construction equipment manufacturer?

  1. The market structure allows for a scalable solution: The model works on the basis of controllable costs in the implementation (simple Bluetooth sensors allow monitoring of usage and the place of use) and there is a manageable number of major customers for whom billing can be done via existing customer relationships.
    ⇒ But careful: Would such a model make sense in a market with thousands of (partly unknown) customers, for example in the end customer market? Probably not – the costs would be prohibitively high.
  2. The model creates additional added value for the customer – not just changed payment methods: Here, the construction equipment manufacturer indirectly solves a problem for the customer – the theft of the equipment is automatically curbed. Thus, monetary impact from equipment that often disappears from construction sites is alleviated. ⇒ But careful: The model will not bring the manufacturer any additional service revenues – through the changed business model, the manufacturer has strategically positioned itself to secure market share as a long-term partner, but will have difficulty proving that the change has generated significant new business.

Also popular are the so-called gain share models (business models in which providers are given a percentage share of the savings or revenue). This model unfortunately all too often fails due to the first point mentioned above – scalability. Providers are often not aware that these models involve a high project management office (PMO) effort. Many large projects that started on a gain share basis have already been stopped or in some cases switched to fixed price contracts.

Of course not all of these reactions are wrong for every company. What all 4 reactions have in common: If applied generically, they are not market-driven. IoT is primarily a vehicle for creating added value for our customers.

But what does this mean strategically and can IoT really earn money in the short term?

How IoT generates sales

IoT Use Cases, which are currently already profitable:

  • Easy to understand (clear added value)
  • Achieve immediate impact (<1 year ROI and measurable)
  • Scalable (solution can be applied to a broad base of target customers without adjustments)

An example is ServiceMax. While many people underestimate the potential of pure digital IoT services and believe that “IoT Apps” can only bring in a few extra Euros per month, ServiceMax shows that with the right services it was possible to generate a turnover of 100M€ already in 2017. The company has proven how to do it with clear added value (such as an average 14% reduction in service costs) across multiple industries in a scalable market.

So, yes! IoT has the potential to contribute significantly to future revenues and especially to increased profit margins (thanks to high scalability at low additional costs). But for most industries there is a big difference to the ServiceMax example. IoT services can be sold in very few industries without a direct sales model. ServiceMax achieved extremely rapid scalability by offering its software for download through the Salesforce AppExchange marketplace, giving smaller businesses access to the technology without significant sales effort. However, this works in the first step for very few IoT cases. Most companies are currently experiencing that IoT service sales involves a sales process of at least 1 year, often significantly longer.

IoT requires stamina

This means that board members and managing directors need to have endurance and confidence in their own IoT strategies. Especially in the current economic situation this is becoming increasingly difficult – but experience shows that those who persist and stick to their course will be rewarded.

Natalie ist eine der weltweiten Leads im Aufbau der Serviceabteilung für IoT & digitale Services für Danfoss Climate Solutions. Sie treibt in ihrer Funktion, als Leiterin des Produktmanagement Digitale Services, die IoT-Markt- und Produktstrategie voran, baut globale Partnerschaften auf und gestaltet die Go-To-Market Strategien. Zuvor leitete Natalie für Gartner Consulting Top-Management-Engagements bei globalen Fortune-500-Unternehmen rund um KI und IoT.
Source Gartner IoT Adoption

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