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Discover why your innovation strategy needs more autonomous teams

Half of the Fortune 500 will not exist in ten years, say c-suite executives. Corporate Venture is at all-time high. Deep Tech start-ups look with envy at established firms’ assets. This post explains why corporate facing digital disruption need to enhance their innovation strategy by creating complete autonomous teams working exactly like start-ups. It also highlights the unique advantages of these autonomous teams / corporate start-up studio in pursuing successfully breakthrough and disruptive innovation as they follow a design and data driven innovation journey.

Digital innovation mapping

To build an effective innovation strategy, it is important to map the different types of innovation. Abernathy & Clark, Clayton Christensen, Robert E. Johnston, J. Douglas Bate and Greg Satell made some important contribution to this topic. The most relevant measure of innovation level or intensity is measured against each firm’s referential by looking at the changes it introduces both on the technology/application and business model/market dimensions.

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Becoming Digital implies often for companies to make important changes in terms of technology/application and business model/targeted market.

The Path Dependence theory explains us why corporate develops overtime a strong immune system that will prevent them to adopt negative but also positive changes. This immune system, embedded in the firm’s DNA, creates a strong roadblock to radical innovations (disruptive and breakthrough ones).

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This map defines the overall level of innovation according to the technology and business mapping. Becoming digital requires firms to become more efficient at managing disruptive and breakthrough innovation projects.

Digital disruption concerns all industries

A new wave of digital technologies – often referred as Deep Tech – is impacting all sectors of the economy. Due to its massive impact in terms of value creation or value re-distribution, it is defined as the 4th industrial revolution by Pr. Klaus Schwab (Founder and Executive Chairman of the World Economic Forum) .

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Deep Tech are impacting all industries driving the 4th industrial revolution. Companies need to change drastically their DNA and operations to survive.

Bitcoin emerged as the first digital international currency. Uber and Telsa have higher market valuation than historic car manufacturers. AirBnB is competing with Hilton and Marriot in terms of valuation. Amazon is transforming and taking the lead on the retail industry. Netflix is doing to the TV industry what Apple did to the music industry few years ago. These are the most known examples of digital disruptions and represents just the top of the iceberg. In fact these unicorns are hiding thousands of new companies that are planning to leverage Deep Tech to challenge established players and to redefine markets.

Corporates are outsourcing their radical and disruptive innovations to start-ups

Although established firms excel at incremental innovation, breakthrough or disruptive innovation projects are rarely successful (too slow, too expansive, not scaling, not radical enough). Therefore, many corporations – afraid to miss out on the 4th industrial revolution – decided to outsource this work to entrepreneurs. In order to do so they invested heavily in corporate venture.

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Corporate venture is now part of the innovation strategy of all major industry leaders

In 2016, the most active Corporate Ventures in the world were Intel Capital and Google VenturesSalesforce Ventures, Comcast VenturesQualcomm Ventures, Cisco InvestmentsGE Ventures, and Bloomberg Beta.

The Corporate Innovation EcoSystem

In fact, corporate developed more advanced innovation strategy and create a complete ecosystem to become more effective at developing new radical and disruptive innovation projects. Corporates aim indeed at developing more synergies between their digital innovation initiatives and the digital transformation of their core-business.

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Optimised Corporate Innovation Ecosystem for an effective innovation strategy in the age of digital disruption.

In order to prevent the corporate immune system to prevent the creation of new successful ventures, firms need to increase the autonomy of the teams working on new digital initiatives. These initiatives should be managed as individual ventures running like start-up. This organisation model is described by Bain & Company as The Firm of the Future.  

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The next level of Corporate Innovation EcoSystem

Autonomous Innovation team are like a start-up

Start-ups are obsessed by getting market traction for their products and services. They are also continuously seeking confirmation that they are on the right path to succeed. Mastering the art of pivoting is important for entrepreneurs.

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Founders understand that in their quest to gain market traction, they have to continually reassess their decisions and so being open to change – as market required – any aspect of their venture: strategy, price /brand positioning, targeted customers, business model, etc.

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When it comes to digital innovation (including Deep Tech), entrepreneurs have access to large amount of customer behavioural data. These data play a critical role in helping entrepreneurs to shape the strategy and offering of their venture. This freedom and pragmatic approach enables start-ups to discover new paths to success in uncharted territories.

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Stanford Business School’s Startup Garage Innovation Process Graphic is a teaching tools for Stanford University Graduate School of Business to help students understand the innovation process. This graphic is displayed as a large banner in the classroom to keep the students on track throughout the process.

Deep-tech start-ups need corporations

It would be dishonest to draw a too positive picture of the entrepreneurial world. The success rate of start-ups remains low. 71% of the start-up failed in their first 10 years. It is interesting to see corporations betting their future on Corporate Venture and so on a system with such high failure rate.

BCG ran recently a survey with 400 Deep-Tech start-ups and identified the most important needs for them to support their development. It happens that two of their most important needs – market access and technical expertise – could be answered by corporations.

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Deep-Tech start-ups welcome the help of corporate to gain market access and technical expertise. Both are critical items for the development of their digital venture.

The corporate start-up studio is a optimised solution for digital disruption

Entrepreneurs and the start-up ecosystem have the right DNA to develop successfully new digital ventures.  But on the other end, when it comes to Deep Tech, corporations have some unique assets that start-ups need.

Corporate Start-up Studio gather the right culture, skills, and assets to develop the successfully new radical digital ventures.

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A Corporate Start-up studio gathers in one environment the best of the two worlds.

Future Economy Studio offering

The Future Economy Studio is the first start-up studio helping corporations to create and manage autonomous innovation teams.

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From Augmented Reality to Augmented Experience (AR-X)

In this post we will introduce what we believe will be the next evolution of the AR/VR market: the Augmented Experience (AR-X). AR-X is an emerging mode for augmenting the physical world beyond the current use of flat screen and smart glasses. For example interactive projections, smart objects , voice and audio. We will explain that the success of mobile applications like Pokemon Go suggest that AR applications on mobile devices will lead the mass-adoption of AR-X market (cf. investment plan announced by Mark Zuckerberg).

Augmented and Virtual Reality: state of the union

2016 was a special year for AR and VR. The combined market grew aggressively and reached 3.9B$. The volume of VR units sold was strong but below the ambition of the major corporations behind (Facebook, Sony, Samsung, Microsoft). Selling millions of units is not enough for these actors who are looking for numbers in the billions of recurrent users. At the same time, in 2016, thanks to Pokemon Go and its 650M downloads, AR made an outstanding performance far above expectation. It demonstrated that tablets and smartphones had the potential to drive mass adoption of the AR applications. Mobile APP based AR presents a set of unique advantages:

  • Remove the entry cost to experience AR. Everybody has a smartphone nowadays.
  • Give direct access to massive installed base of potential users.
  • Leverage a more socially accepted way to consume digital content. People are used to seeing other people with their phone in all occasions. People don’t have to wear additional awkward AR devices or isolate themselves from the world with a VR unit.

This Pokemon Go unicorn was enough to convince most of the players (Apple, Facebook, Samsung, and Google) to reinforce their investments in mobile AR.

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From mobile AR to Augmented Experience (AR-X)

AR-X extends the concept of AR by making it more ubiquitous but less intrusive. It will not be necessary for the consumer to use their own device to experience the AR-X. Even a passive customer can be activated by interactive projections or audio.

AR-X leverages additional media to augment the world around you. Such new medias are for example : animated digital projection, voice enable devices, and smart / IoT devices.

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We believe AR-X technology represents a brand new way to engage with customers. This new form of communication presents the same capabilities of AR by being highly contextual and personalized but is by nature effortless for the customer.

The following video is a simple implementation of Augmented Experience (AR-X) concept by creating a brand new interactive interface.  This prototype was realised by a US creative agency called argodesign.

 

The AR-X concept and this article is the outcome of the research work done by Nicolas Payen (Founder of the Future Economy Studio) and Gregory Cornelius (founder of Protiotype). 

Dreaming out loud…

It is always entertaining to imagine what the future could be like. It is a part of my job that I enjoy very much. It is – I believe – an activity that everybody should practice. It only requires curiosity, audacity, and a playful mind.

“If you can dream it, you can do it.” – Walt Disney

In the last years, creativity gained more attention and respect in the business world.

PWC’s 19th Annual Global CEO Survey reports that 51% CEOs are making significant changes to their organisation in order to better use digital technologies. This ranks as the most important driver for change according to the 2016 CEO survey.

Many companies faced by potential disruptions or opportunities associated with the new digital word adopt new practices at the core of their strategy and execution. For example they embrace activities like design thinking or growth hacking. Those rely heavily on creativity.

The Future of Jobs Report from the World Economic Forum is confirming this trend. Creativity is set to become  #3 most wanted skill in 2020. It was “only” ranked #10 in 2015. Creativity will only be topped by #2 critical thinking and #1 the ability to solve complex problem.

As a society we need the private and public sectors to become more efficient innovator and value creator. In the last decade, productivity gains slowed down drastically.

We can hope that this plateau of productivity is only the warning sign of major improvement driven by new digital technologies. Indeed the demography of our societies is going through a massive transformation. By 2050, there will be only 3.5 working-age persons per person aged 65 years old or over. In 2015, this ratio is 7 to 1. This means at the world level we need to double our productivity in the next 35 years. One working person in 2050 will have to deliver the same output as 2 working person in 2015. That would required at least a consistent net gain of 2% of productivity for the next 35 years! If not then we may face a pauperisation of our societies.

People should not be concerned by radical innovations like autonomous driving, artificial intelligence, or robotic as long as they create value for the society. We indeed need plenty of them to fill up the productivity gap.

“I have no special talents. I am only passionately curious” – Albert Einstein

At a time where our society is crying for innovation and progress, at a time where digital technologies seems to have more to offer than ever, CREATIVITY seems the most important thing we need.

Building your IoT All-Star Engineering team

IoT (Internet of Things) projects can be very challenging for an organisation due to the large scope of competencies required. In the past, companies often focus either on HW products, or SW products, or services delivery. But in order to build IoT solutions companies need to acquire and assemble an incredible set of talents. In this post, I describe the main competencies required in order to design, industrialise, and operate an IoT solution.

IoT refers to different architecture typologies. So the set of competencies you need to assemble depend on the architecture(s) you selected and the place in the value chain / ecosystem you want to hold.  For this list, I considered the most complex situation where you would like to offer a full end-to-end solution (multi-devices to cloud). This is the most challenging from an engineering / operation point of view but it is the most rewarding in terms of value creation.

If you are the founder of an IoT start-up, the engineering head of a MNC, or the  HR leader supporting them then this list of 20 competencies could quickly become your nightmare. So I would recommend to first evaluate the competencies that already exist in your organisation, the IoT architecture(s) you aim at, the latent value associated with IoT for your business, the expected number of connected devices, your budget, and your timeline.  Scoping and selecting your first IoT projects is very important and these should lay a progressive learning path in front of your engineering team.

 If you are starting your IoT journey then you should be obsessed with the  search of the MVP (minimum IoT viable product) in order to manage correctly the risk for your organisation.

This list comes on top of the critical APPLICATION knowledge that would be specific to your industry, to the problem you want to solve, to the application you have in mind for the IoT technology, and to your targeted customers. Building application knowledge in your engineering team should be one of your top priorities. It is indeed the best way to ensure that the creativity of your team is put to the best interests of your customers and so ensure the best practical use of technology.

Top 5 competencies to build the right IoT solutions

Design Thinking / UI-UX design: Helps you to focus on customer’s job-t0-be-done and customer experience, seek for minimum viable product, creative and practical use of technology. There is something magical that happens when you build something beautiful and easy to use! This is relevant in both industrial and consumer IoT applications. It is very important to bring the designers at very early stage in the ideation process and to give them a strong mandate. They will need a good support to stand for their values in front of the engineers!

System design: End- to-end IoT solution is composed of several HW and SW components. Designing a reliable, scalable, maintainable solution requires upstream analysis and thinking to understand and define how each of these blocks will interact or interfere with each other. You don’t need all detailed requirements to start working on system design and a lot of work should be done once you have a macro view of what you want to build.

M2M (telecom, network, device management): Choice of the technology(ies) for the connectivity is strategic and will depend on various technical, geographical, and business factors. There are many different technologies /standards (Fixed, LoRa, Sigfox, Cellular IoT, Cellular) and providers to choose from. Connectivity is a core part of any IoT solution and it includes for example topic like: device management, messaging technologies, SIM card management, authentication, and encryption, etc..  You will need to select and manage the right technology providers.

Cyber security: Security principles and mechanisms shall be built-in. Design for security is the best way to achieve high level of protection while reducing the cost of security features. While having competencies allow you to embed security mechanisms in your design, it is best to hire security experts to perform security assessment, intrusion tests, and destructive tests. By putting your design at test you will achieve good level of security!

Data protection and privacy legislation: While cybersecurity concepts are global, ; data protection and privacy legislation vary from country to country. It is important to identify the different regulations you have to comply with and how to integrate them in your system design (EULA, user profile & access rights, data base structuration, data anonymization).

Top 5 competencies to build IoT solutions right

Agile methodology: when the direction is fogy, when the path is unknown, when you are learning on the go, there is no better way to work than Agile. Agile methodology is an alternative to traditional project management (waterfall, or traditional sequential development) typically used in software development. It helps teams respond to unpredictability through incremental, iterative work cadences, known as sprints. Agile developments work best when it is also adopted by other functions (marketing, sales) as it ensure quick market feedback to the team (fail fast, keep learning and experimenting) and really improve the speed of implementation. If you are starting your IoT journey then this is the (only) way to go!

Design-to-cost: Typically sixty to seventy percent of a product’s cost or life cycle cost is committed based on decisions made during concept or architecture development. That is the best way to maximise the ROI for your IoT investments and to favour a market pull approach vs a technology pull one.

Failure Mode and Effect Analysis (FMEA): End-to-end solution require the collaboration of multiple components and sub-systems. Even world-class engineering and manufacturing teams make mistakes. Your design and your architecture will minimise the impact of unplanned events on your operations and customers. FMEA is powerful tool to build-in quality and robustness. Good engineers always think about degraded modes, about self-recovery mechanisms, about maintainability, about data integrity,  and about edges cases. This is a big part of the system design work.

Configuration management / Test automation / Continuous integration: If you are developing an end-to-end IoT solution then this will reach a completely new level. Make sure that your basic quality / development tools are in place to ease the work of your SW engineering team. You will increase your velocity and reduce your non-quality costs in the long run by making sure these foundations are solid. Provide your engineering team with development tools in which Agile methodology concepts are built-in.

Vendors / suppliers management: IoT solutions are the combination / integration of multiple technology bricks available. Selecting, forming, and managing these technology partnerships are a very important part of building your IoT solutions. Select carefully what you will do in-house versus what you buy as putting all these pieces together is already massive work!

Top 5 competencies to build IoT devices 

Sensing technologies / actuators: This is the reason you build your own things. This is a major area for research and innovation. They play a key role in the value creation for any IoT solution.

Electronic / PCBA / Mechanical design:  Smart Things are made of electronics. End customers don’t buy PCBA, everybody loves cool and good-looking things.

Embedded software: You would be amazed by the computing power of some micro-devices and by the level of logic you will end-up embedding in your end devices (sensors / actuators) or machines (gateways, controllers) . Power consumption is always a concern and requires a constant care from both HW and SW developers.  For machines ARM, Linux, Java, and OSGI are a popular combo.

Wireless: Local connectivity is often a requirement for multi-devices systems. Here also many technologies are available (Zigbee, Bluetooth, EnOcean, Wifi, and /or other proprietary technologies) and their selection will be a strategic step. Security, antenna design, power consumption, self-recovery, certifications, and stack tuning are some of the typical hurdles you will have to go through during implementation.       

HW industrialisation (manufacturing, tooling, supply chain): What is the point of building and selling great products if quality is not here? Here lies the difference between a proof of concept / value and a real product / business.   

Top 5 competencies to build IoT services

Cloud architecture / Cloud database: With different cloud strategy available (public, private, hybrid) there is a cloud solution for all businesses. You will need some in-house expertise to select and manage the right providers (Amazon, Rackspace, Azure, Google, HP) and so harvest the benefits of cloud technology (scalability, lower OPEX, flexibility, glocal).

Data scientist / Big data processing: So you spend million dollars to build an end-to-end IoT solution. You finally get data about your installed base, your customers, and the application of your technologies. What’s next? How to extract maximum value based on these data? A data scientist will help you, working with the business team he/she will identify new way to process your data to create value for your existing customers or for new ones.

Mobility / Mobile APP: Both in B2B or B2C, mobile devices shall be your prime area of research to enhance the UX-UI of your solution. Different technologies and different frameworks are available and they all present some unique features. You will need to master iOS platform and a large amount of Android ones. There is no end to this work as the devices and platforms keep evolving and customers expect to receive updates on regular basis.

API design / management: When it comes to B2B business, APIs play a key role to enable collaboration with other technology companies. They are also an efficient way to enable third parties to build on your solutions in order to increase its market value or attractiveness. APIs should be thought through as they are defining the limit / scope of your solution. If you decide to publish them they you will have to manage them like a SW product.

IT Service Management (ITSM): IoT solutions are very often associated with services oriented business models. It is rarely a Sell and Forget model. You will have to create an customer service /operation team with the responsibility to ensure your IoT solution is running according to the (SLA) Service Level Agreement you committed to. ITIL (Information Technology Infrastructure Library) is a widely accepted approach to IT Service Management (ITSM), which has been adopted by individuals and organisations across the world.

Industrial IoT, putting customer services at core

The Internet of Things (IoT) is described in the industrial world as the 4th industrial revolution. Industry 4.0 concept originates from an German government initiative launched in 2011. IoT market is sized at 1,7T$ by 2020 (according to IDC) and can have an economic impact of 4 to 11T$ by 2025 (according to McKinsey). These numbers give vertigo but they covers different industries , and a very long value chain (sensor / chipset to cloud / mobile applications). According to most of the market surveys, the Industrial sector is the biggest potential market for IoT. In this post, I focus on this vertical and on – what I believe is – a transformative part of the Internet of Things, its impact on business models.

LEGACY industrial enterprises are like ONIONS

In order to understand the changes, lets look first at the legacy systems and past conditions. For years, enterprises have been enhancing their business operations by assembling in-house technologies. Over the years, software  became more and more strategic and is now at the core of how enterprises run their operations (from the shop-floors to boardrooms).  

Most of the legacy entreprises have the following characteristics

  • Enterprise data are confined in the company IT network. Field data are collected, filtered, computed, and reported through the different layers of control & IT systems (PLC, DCS, SCADA, MES, BMS, ERP, CRM, etc..).
  • Knowledge and competencies are maintained locally or in-house to secure operations.
  • Enterprise network acts as primary security mechanism against outside threats.
  • Assets suppliers or services providers do not have access to the field data. Access to the equipment involved in mission critical operations is strictly restricted.
  • Most of the business operations are related to the manufacturing of the goods and their distribution

We saw a first major transformation of this system with the introduction of the Cloud technology in 2006. Cloud technology and especially the BPaaS, SaaS, PaaS, and IaaS associated business models are driving a major evolution of the entreprise software world.  Most CIO have already integrated cloud based solution in their portfolio and in the next 2 years cloud will become mainstream (will represent the majority of the enterprise software deployments). As a results cloud’s CAGR is 3x faster than on premises. Depending on the targeted cost, security level, and peak performance demand of their application, IT departments will choose between private, hybrid, and public cloud solutions.

Connectivity, as the starting point of the Internet of Things

In 2013, there were already 7B machines connected to the Internet. By 2020, we expect 30B machines to be connected. When talking about Internet of things, people often refer to the adoption of M2M, Cloud, and mobile technology to enhance the enterprise operations.  IoT enables the asset supplier and authorised third parties to access a physical device located on the customer’s enterprise premises (a plant for a industrial company, a public space for cities, etc…).  Connectivity is achieved by using M2M technology (fixed, cellular, cellular IoT,  Lora, Sigfox) with 2 main goals:

  • Maintain a secured and reliable communication channel between the physical asset (fixed or movable one) and the IT applications.
  • Bypass local enterprise IT networks to ease deployment and maintenance of the asset.

Mobile devices and Apps have been a key driver for the adoption of the Cloud technology in the industrial sector. They will also play an important role in the adoption of the Internet of things by enabling new innovations. Apps are indeed the most powerful way to expose data to different stakeholders and to extract value from the connectivity.

Connectivity is the enabler of the Internet of Things but the major transformation lies in the way IoT changes the nature of the business relationship between the enterprise and its asset suppliers.

IoT applications in the industrial sector

There exists many applications of the IoT concept in the industrial world. We can classified them according to the 3 main categories of the type of assets connected:

  • Work forces: The most important asset of any company: operator, technician, supervisor, engineer, manager, etc… They are either employees or contractors but all contribute to the operations.
  • Machines: Assets that have their own intelligence and are able to operate autonomously.  They perform complex tasks based on the information received from operators and the different control systems.
  • Sensors and actuators: Assets with only basic or no computing power, collect information on the field and pass it to the control system, perform basic actions based on central system requests.

Lets look at the most common industrial application of IoT

Often the first use case for connectivity arrives from the after sales operations. After sales market operations are critical for most industrial companies as they represents a very large part of the company profit and they also play a key role in maintaining customer loyalty over time. By connecting their assets, after sales support teams can tackle many of their daily headaches:

  • Lack of data when customer reports an incident.
  • Lack of manpower as only few people have the required skills-set to solve complex customer issues.
  • On-site interventions are too expensive (manpower cost, transportation) and disturb customer operations. Industrial equipment can  be located in not-easy to access locations.
  • Need to monitor assets on the field over time to analyse issues and identify root causes.
  • Deployment of the changes/ corrective actions takes too much time and requires on-site presence.
  • Difficult to forecast demand for spare parts due to lack of knowledge of the installed based, customers, and customer applications.

Product teams and sales departments figured out quickly the potential associated with such connectivity. Thanks to the analysis of field data, they are indeed able to gain a deeper understanding of their customer activities and to build product/application knowledge faster than before.

By connecting to large numbers of their products, suppliers are able to build new added value services that enrich their asset:

  • Asset tracking, remote monitoring and control
  • Preventive maintenance & remote diagnostic tools, remote (re)configuration and update
  • Enhance HMI with mobile APP
  • Performance analytics, and cross-customers analytics
  • Digitalisation & virtualisation of the physical asset

These added value services, often primary developed by the after-sales team, are the building blocks that will enable the supplier to automate its service delivery and by doing so create and scale brand new business models.  In this new competition landscape, the players with the largest number of connected devices, the best analytic, and the largest number of customers per asset will enjoy a unique competitive advantage. 

Connectivity enables service-oriented business models

IoT is changing the HARDWARE industry in the same way CLOUD technology changed the SOFTWARE industry .

With connectivity, the nature of the customer relationship evolves. The asset supplier enters in a long term and continuous relationship with its customers and by doing so create a more “customer centric” organisation. Armed with data and statistics, it becomes possible for the physical asset provider to move towards service-oriented business models with confidence without expose itself to a major financial risk.

We can list 5 major steps in this evolution of the business model:

  • SELL & FORGET: The supplier hands over the asset to its customer. Supplier provides only after-sales services according to warranty.
  • SELL & MAINTAIN: The supplier hands over the asset to its customer. The supplier provides additionally maintenance and support services to its customers.
  • SELL / LEASE & CO-OPERATE: The supplier hands over the asset to its customer. Supplier and Customer enter in a long term relationship where supplier commits to take required actions to maintain availability and performance of the asset over time according to mutually agreed SLA. This is a joint management of the assets. But here is the catch, many customers still often prefer to buy hardware over a bundle of hardware and software and services. As a results, even if a major part of the supplier asset unique value proposition lies in its software and its services, supplier can still adopt a  revenue models that is still mainly hardware (HW) based.
  • SELL & OPERATE, PRODUCT AS A SERVICE, or PERFORMANCE BASED CONTRACT: The supplier commits to do the job it has been hired for by its customer. Supplier is measured on the business outcomes (volume, cost, quality, availability) and solely manages its asset in order to maximise business output. The supplier takes accountability for the overall productivity of the asset and also for the potential liability associated with its defaults. Here again, the supplier can adopt an HW based revenue model while most of its business model is service based. 
  • ASSET MUTUALISATION:  With connectivity, asset suppliers are able to extract value from different customers. Indeed the data and the communication channel associated with the assets may be valued by other enterprise than the asset owner. With the agreement of the asset owner, the asset supplier could provide additional digital services to third party customers and so reduce the cost of ownership of the physical asset. Smart Grid / Micro Grid, insurance, environment monitoring, cities,  are typical customers of mutualised assets.

Players able to transition to the new business models will win over time over the ones adopting a traditional supply models like SELL & FORGET for the following reasons:

1)  Industrial customers in search for productivity (maximise their output,  or reduce their fixed cost, increase their agility) will be interested by suppliers able to provide them with not only assets but also commitment on business outputs.

2) By merging hardware and services, suppliers extract more market value from their assets over their product lifecycle and by doing so they will build more profitable businesses.  The SELL & FORGET / SELL & MAINTAIN players will end-up squeezed in a commoditised market with lower margins.

3) Industrial customers , interested by delaying their investment or reduce their cash out,  will favour OPEX engagement models (Product as a Service, performance based contracting) over CAPEX intensive ones.

As a consequence, every asset manufacturer should investigate how connectivity will enhance their product features and which services they can enable.

With IoT, enterprises become more interconnected

In order to maximise the benefits associated with connectivity while being able to scale their business, IoT players will need to automate their service delivery. Service automation requires  the use of advance analytics, and artificial intelligence technologies.

Asset suppliers and their customers will both see value in automating their data exchanges and transactions through the use of APIs (Application Programming Interface) for the following reasons:

  • Asset suppliers use APIs in order to: scale the number of connected devices, lower customer support costs, allow channel partners (like digital integrators) to realise customisations and specific integration work for their customers, to create an ecosystem of software developers / digital integrators to extract more value from the already deployed assets, to comply with standards over time.
  • Asset customers welcome APIs in order to: reduce cost of managing the suppliers, to have clear and define software interfaces and so to avoid dependency on single supplier, to make possible the creation of enterprise specific logic on top of the supplier solution, to integrate the asset supplier’s data in their own analytics and business processes.

With IoT, modern Industrial companies will present a complete different outlook. There will be as much attention on the operation technology used to run the manufacturing and supply chain operations as on the operation technology used to manage the installed base and to optimise the services delivery. Both will contribute to build a healthy P&L based on a combination of HW, SW, and Services sales. Integration of data flow and transactions with other asset owners or asset suppliers will become mandatory to survive and scale in this hyperconnected world. Current control layers (PLC, DCS, SCADA, MES, ERP, etc…) will continue to process most of the real time data, but a growing parallel flow of data will emerge and the newly virtualised assets will expose their advanced services to all authorised IT systems willing to consume them.

The race is on!

The adoption of the Internet of Things requires profound changes in the way enterprises design their product, manage their assets (hardware and software) , and run their operations.  It took nearly 10 years for cloud technology to become mainstream in the enterprise world and the SaaS business model has been a key enabler . It will take time before IoT gains similar traction (targeted by 2020) and here again new business models like Product as a Service will be a key driver of adoption. The next major step of productivity and innovation is on its way and the race is already on!