The Third Generation of Open Innovation Methods

In the industry we have now three generations of open innovation methods. They differ in the way, how they are enabled:

  • either by people
  • or by social media technology
  • or by open industry platforms (or call it app stores)

All three generations are still alive and important.

1st Generation: the people enabled methods

they are characterized by face-to-face communication, as it is the case for

  • startup collaborations,
  • R&D ecosystems,

but also

  • Hackathons or
  • Lead User Workshops

2nd Generation: the social media enabled methods

they are characterized by web-based communication
as it is the case for

  • Open Innovation Contests or
  • Call for Proposals

but also for our internal methods like

  • TechnoWeb and
  • Quickstarter

3rd Generation: the industry platform enabled methods

The third generation is currently the youngest generation. The idea of the industry platform enabled methods is to provide an open hardware/software platform which opens the innovation ecosystem to third parties including startups and SMEs. The main interaction takes place by machine-to-machine communication.

We could also call this the “app store enabled methods”. In the consumer market we all know the open platforms like the app stores from Google and Apple.

In the industry market it is our job to provide open platforms for the industrial automation.

What have all this three generations of Open Innovation methods in common?

The answer is: building ecosystems,
either by people, by social media, or by open industrial platforms.

This text is based on my statement about “Open Innovation in the Industry” for the visit of Carlos Moedas, EU Commissioner for Research, Science and Innovation at “Austria’s Open Innovation Strategy. The road towards a European Open Innovation Cultur”.

Carlos Moedas, EU Commissioner for Research, Science and Innovation at “Austria’s Open Innovation Strategy. The road towards a European Open Innovation Cultur”

Carlos Moedas, EU Commissioner for Research, Science and Innovation at “Austria’s Open Innovation Strategy. The road towards a European Open Innovation Cultur”

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Open Innovation is the warm-up exercise for the working world of the future

Open Innovation stands for the conscious opening of organization borders for the innovation process. “Opening the borders”, however, frequently leads to reservations in established industrial companies: “Innovation is the most important factor for competition and safeguards the survival of my company. Why should I therefore share my innovations with the rest of the world?“ If Open Innovation approaches are falsely understood in this manner and, as a consequence, therefore not implemented, it can happen that companies lose their grip on the innovation ecosystems and thus also lose their ability to compete.

Open Innovation as a catalyst for the flexibilization of the value creation chain

The more services and products become globally available, the more important it is to be perceived as the best provider. What is the best for a customer, depends on his needs: Quality, price, time, place, ecological and social footprints are typical parameters in this regard. How these parameters are weighted, varies. For industrial companies it is significant that their value creation chain only consists of the best subcomponents. Which subcomponents are the best for manufacturing companies can change as a result of new requirements or new solutions. It is therefore essential that the subcomponents of the value creation chain can be flexibly exchanged, and can be replaced by the currently best ones.

At present many customers still prefer industry solutions from one source. In future, the focus will also be on the exchangeability of individual subcomponents, no matter which company or startup actually delivers them. Some customers will also wish to bring components into the ecosystem themselves. Those companies, which offer open platforms, which function as Open Innovation ecosystems, will have the advantage.

Modularization follows digitalization

In more complex value creation chains, the lock-in effect of established solutions is presently still too high for them to be simply exchanged. The ongoing digitalization and the coupled (de facto) standardization, however, will result in a further modularization and encapsulation of the individual subcomponents, which will ultimately lead to a complete exchangeability of subcomponents. In the consumer segment we are already familiar with this effect in terms of apps on our smartphones. In the industry, exchangeability will affect both, hardware (e.g. machining tools, automation systems) and software (e.g. procurement, planning, simulation, automation, optimization, operational and invoicing software) as well as processes and services (e.g. logistics, maintenance, integration). Digitalization technologies such as for example the digital twin promote exchangeability and/or make it even possible in this generalized form.

New business models and platforms, so that opening the borders is economically attractive

This is where Open Innovation has to focus. We must learn to collaborate beyond organizational borders, industries and disciplines and develop new business models and platforms, which subsequently make an opening of the borders attractive. Open Innovation does not imply giving everything away for free. Instead, Open Innovation means that one has learned to establish collaboration models in the sense that it is not clear right from the start, who will contribute which innovations over the course of time. Smartphone apps also serve as a good example in this regard.

Open Innovation is more than just innovation contests

It is important to understand that Open Innovation is more than just innovation contests. No Open Innovation expert will ever claim that open innovation contests are the sole solution for industry innovations. At present, industrial Open Innovation methods such as for example “Hackathons” and innovation marathons, co-creation, call for proposals, lead users, Startup Founder Spaces and crowd funding are already in use. In far too little cases, however, are hardware/software platforms and their ecosystems also perceived as Open Innovation methods.

In the industrial environment, Open Innovation enables SMEs and startups to participate in the innovation ecosystem.

The new Enlightenment: Trial-and-error instead of pure rationality

(Remark: “The New Enlightenment” was the general topic of the European Forum Alpbach 2016)

The new Enlightenment shines in a different light here: Successful is what is acknowledged as the best on the market, i.e. in the democratic sense, no matter whether it can be rationally explained or not. Here we can observe a – well-known innovation-facilitating – much stronger bottom-up trial-and-error approach than in centralistically planned approaches.

All Open Innovation approaches are important “warm-up exercises” in order to prepare for the future working world, which will be strongly determined by flexibilization. Those who think through to its conclusion, the trend of continuous replacement by the best, will understand what these major changes will bring for all of us.

This text was written as in input for the Open Innovation panel discussion at the European Forum Alpbach 2016

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The Pitch: investors invest in stories

I read the book “Pitching Hacks” by venturehacks.com:

a thin booklet with a lot of valuable insights how to get in contact with a venture capitalist (VC) via middlemen and how to setup a pitch. They are not talking about the classical 3minute pitches which are known from pitching contests, but about a

  • written elevator pitch with ideally just 100 words, containing a
  • high-concept pitch: a single phrase like (e.g. “Flickr for Videos” for YouTube).
  • and sometimes a “ten-slide” deck as an attachment.

My learnings from the book:

  • Investors care about traction more then everything else – or how the authors say: “Trackion speaks louder than words”. If you are not able to demonstrate real traction numbers like increase of users per month, increase of revenue or profit per month then “put the idea on a piece of paper and start testing it with customers”
  • VCs want to invest in you if the market is large and your traction is great.
  • The best middleman is somebody who successfully brought business to the VC in the past (and never accept another investor who declines to invest in you as a middleman)
  • There is a difference between a high-concept pitch (e.g. “Flickr for videos” for YouTube) which addresses the investor, and a tagline or claim (e.g. “Broadcast yourself” for YouTube) which addresses the customer.
  • The high-concept pitch is important as you want others to spread the word about you. They cannot remember a 3minute pitch but they can remember one phrase.
  • The 100 words elevator pitch must contain: traction, product, team, and social proof. It can be forwarded per email by the middleman. A template/example is given in the book.
  • The slide deck schould follow the “10/20/30 rule“:
    10 slides
    20 minutes
    30 point font size
  • The slides start with the cover with the logo, tagline and contact info; the summary (key facts similar to elevator pitch); the team; problem; solution; technology; marketing; sales; competition; milestone for the next 1-3 quarters; a conclusion stating what can be accomplished if the plan is realized; and financing. See book for details.
  • Storytelling is an art, not a science“. Storytelling is not covered in the book but refers to http://bit.ly/Uw4h and http://bit.ly/hUTy (read it!).
  • Talk about what you have done (lessons already learned, testing and revising hypotheses) and not what you could do (today, almost anybody else could do it, too).
  • Do not submit confidential information and do not even think to aks the VC to sign an NDA – a VC will never sign an NDA. You can add a sentence: “please don’t forward this outside your firm”.
  • Many startups think they have secrets: “They tend to believe there is a lot of value in their idea alone (there isn’t) or the idea is particularly novel (it usually isn’t).”
  • VC have to spend their money. If you don’t get it somebody else will get it.
  • Be sure your pitch is great – not just good.
  • Focus the pitch on the key questions of your stage!
  • They recommend some must-reads for startups, e.g. their own venturehacks.com or avc.compaulgraham.com/articles.html, 37signals.com/svn and startuplessonslearned.blogspot.com and many others.

 

 

 

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Innovation: reduce cycle-time of the built-measure-learn loop

My learnings/book review from:
Eric Ries: “The Lean Startup” Penguin, London 2011.

For me, one of the most fascinating books about innovation under conditions of extreme uncertainty. Every day you delay to read this book you risk to waste money.

Most of the innovation books are not concrete enough but this book is full of concrete recommendations – a must-read book for IT-based innovators, and not only for startups but also for large enterprises.

Key Messages:

  • The worst thing regarding productivity you can do is to build the wrong product – a product which nobody wants. The Problem: most of the innovators build the wrong product and fail. Therefore:
  • The key success criteria of innovation (under extreme uncertainty):
    make the cycle-time of the build-measure-learn loop as short as possible.
  • The effort that is not absolutely necessary for learning what the customers want, can be eliminated.
  • Validated Learning: based on real data with real customers. Today we need not to aks “can the products be built?” but “should the product be built?”.
  • Investors (and you) want to know if the value hypothesis and the growth hypothesis are working:
    • Value Hypothesis: does the product really deliver value to the customer? Examples for metrics: retention rate.
    • Growth Hypothesis: how fast will new customers discover the product? Examples for metrics: referral rate.
  • Minimum viable product (MVP): enables a full turn of the Build-Measure-Learn loop with a minimum of effort.
    Examples:
    • Concierge MVP: the CEO himself
    • manually instead of automatically
    • limited feature set (and limited quality)
  • “Vanity metrics” like number of users do not help much. It is easy to look successfully even if you don’t. Use actionable metrics.
  • Split-Test: the impact on a new feature on the strategic metrics needs to be tested before it is completely rolled out. This can be done with a split test (make the new feature available only to a part of the users and measure the difference). The effort for additional development pays off by doing the right things (because of learning more quickly).
  • Cohort analysis: e.g. measure the behavior of the new customers of the last month (and not the average of all users since the go-live as early customers have a different behavior).
  • Kanban (capacity constraint). Four boxes (one for each phase), each of them can have maximal 3 entries at a time: Backlog, In Progress, Built, Validated. As a consequence, the whole process will stop as long as the validation tasks are not done. Without validation – no learning. If validation fails the feature is removed.
  • Problem of Business Plans: they are based on a set of assumptions. If the assumptions are wrong then the business plan is wrong. Therefore short cycle time for the Build-Measure-Learn loop in order to learn quickly if the assumptions are correct.
  • Pivot or Preserve. Pivoting (significantly changing the direction) requires that one foot is kept rooted, e.g. zoom-in pivot, zoom-out pivot customer segment pivot, customer need pivot, platform pivot, business architecture pivot (e.g. from high margin, low volume to low margin, high volume), value capture pivots, engine of growth pivot, channel pivot, technology pivot. Signs that the time is ready for piloting: decreasing effectiveness of the product experiments. Regular pivot or preserve meeting approx. every two month or quarter. If you don’t, you risk to getting stuck in the land of the living dead.
  • Small batch sizes. E.g. continuous deployment (special setup required, good product’s immune system required).
  • Growth: “New customers come from the actions of past customers”.
    Engine of Growth:
    • The sticky engine of growth:
      be locked in to the vendor. Important metrics: attrition rate and churn rate. Rate of compounding: natural growth rate minus churn rate.
    • The viral engine of growth:
      Important metric: viral coefficient: how many new customers will use a product as a consequence of each new customer who signs up. Should be larger than 1!
    • The paid engine of growth:
      buy clicks at Google and Co or hire sales team. Important metric: cost per acquisition (CPA) and lifetime value (LTV). CPA needs to be less than LTV.

Startups should focus on just one of the three.

Attention: at some point the number of early adopters is exhausted. The transition to mainstream customers requires tremendous additional work. You need a different team and a different product to serve either early adopters or mainstream.

  • Innovation Accounting: explicit hypotheses, actionable metrics instead of vanity metrics, show from meeting to meeting the progress on the validation of the value and growth hypotheses based on those metrics (e.g. registration, activation, retention, referral, purchasing rates). Kanban Diagram.
  • Example: buy clicks for 5$ a day, then measure with cohort analysis or split tests the rate of customer registration, app download, trial, repeat usage, purchase.
  • Metrics need to be
    • Actionable: a measure can be derived if the metric behaves different from what is expected.
    • Accessible: understandable also for the investors and the management.
    • Auditable: as the metric decides about dead or life of a feature it is important that everybody has the transparency how the metric is computed and trusts in the correctness of the metric.
  • Toyota: genchi gembutsu “go and see yourself”, or Steve Blank: “get out of the building”.
  • Adaptive organization: The 5 Why culture: when a problem pops up ask 5 times iteratively “why?” until you end up at the root cause, and then assign appropriately resources to each problem level. This acts as a natural speed regulator. You implement just as many processes as you really need. Professionally facilitate 5-Why-meetings, the facilitator needs to have enough seniority, all stakeholders need to be present.
  • Creating the Innovation Sandbox in large companies: any team can create a true split-test experiment that affects only the sandboxed parts. Limited time, limited number of customers.

It is impossible to communicate the content of this 300 pages book in 2 pages. You need to read the book to really understand those messages. There are many examples which make clear how much resources are wasted when not following such a lean concept. The book gives a good insight about the current atmosphere in Silicon Valley and what a professional investor is looking at.

The only problem: you need to read it from the start until the end and cannot skip pages. For me the book was such exiting that it was more difficult to stop reading than to continue.

Link collection:

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Separation of Business Stream and Knowledge Stream

Motivation

The problem is familiar to many of us: you open the inbox of your email or your social media tool and see so many emails that you are not able to open and read all of them. Now you would like to apply a filter which separates the emails in those which you must read (Business Stream) and those which would be interesting to read, if there is enough time (Knowledge Stream).

Separation of Communication Streams

Separation of Communication Streams

Must-have or nice-to-have

If your customer is contacting you, you usually must read the mail and need to act. Most of the official business communication is of the type business stream (must-have).

If one of your colleagues or some partner of your external network is sending you some information which could be of interest to you, then it would be nice if you could read all of this information. However, sometimes you need to focus on more important or more urgent tasks and such mails might scroll down and remain unread. In email communication we have bad feelings if we no longer manage to read all the incomming mails. In social media communication like twitter or Facebook it is no problem to miss some feeds. There are too many anyway.
Most of the knowledge stream is of this nice-to-have category, as we are used to the fact that we cannot manage to have all the relevant knowledge for our work but are satisfied if we have just enough knowledge.

Workarounds

Conventions

I was working in teams which used the subject-line convention that the first letter encodes the type of the mail:

  • A: … Action needed  (business stream)
  • D: … Decision needed (business stream)
  • I: … for your Information (knowledge stream)

This was very helpful but required a lot of discipline within the team and does not work with other people who do not know the convention.

Automatic colouring of emails

Most mail-tools offers the feature to display all emails in your inbox in a selected colour if they fulfill a certain criteria, e.g.

  • your mail-address is in the to-field (not in the cc-field)
  • your are the only recepient
  • your boss is also in the to-field

Automatic filtering of emails

Most mail-tools offer the feature to filter the emails.
E.g. move all mails where the subject contains the words “IEEE” or “newsletter” to a separate folder.

These workarounds make our business life easier but are still not enough. Since 2005 I am waiting for a solution but have not seen one. I am looking forward to the Atos Zero-Email-Initiative: they need to offer a more mature solution for this separation of different types of communication streams. In my opinion this is mission-critical for the success of their initiative. And there are good chances to provide solutions which work at least within the enterprise.

Research Question

  • Analyse the different communication streams of a typical knowledge worker and his communication needs in more detail.
  • Cluster those stream categories and the communication needs. Are the two stream category clusters must-have (business stream) and nice-to-have (knowledge stream) already enough? It should be as simple a possible.
  • Design a desired functionality and a  usability concept how those streams clusters can be identified and displayed to the user. Consider the migration problem.

In my opinion the sender needs to classify the communication manually. If the sender tries to send it without classification then the sender is reminded that is not classified. If it is sent anyway, then the recepient receives it as unclassified. If the sender is a machine than this classification can be done automatically (e.g. the workflow system of the procurement system will send out the notification to sign an order, classified as  must-have).
This can work in a trusted environment, e.g. within an enterprise.

Please, let me know if you are working in this field or if you plan to work in this field or if you know about already existing research in this field.

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Value Steering of Social Media

Motivation

If you are responsible for a social media application you want to be successful with your social media application but you have a limited infuence on the behavior of the users. What you can do is to

  • decide about the features of the application – the features shape the use-cases and workflows of the users,
  • decide what and how you communicate with the users, how you understand their use-cases and how you react to their needs, how you define the terms and conditions.

The question is, what are the decision criteria for your decisions?

Value Steering

We distinguish between value and benefit.

Examples of values in typical social media applications, how they are generated and how can they be utilized to generate a benefit

Fig. 1: Examples of values in typical enterprise social media applications, how they are generated and how they can be utilized in order to generate a benefit for the users/company.

In many social media applications the main value is the digital trace of the users. The high quality digital trace is invisible but is often a pre-requisite for generating a benefit for the users.

Example: If a user posts an Urgent Request in your social media platform, this Urgent Request should be distributed to those users who have the highest probability to know the answer (to generate the expected benefit). Such a  message distribution mechanism relies on the quality of the so-called digital trace of the users. If the application has no information (no digital trace) about a user, it will not be able to identify such a user as a potential responder and will therefore not be able to generate the expected benefit.

Therefore we do not focus just on the visible benefit but even more on the invisible value which is generated within a social media application. Optimizing the value generation is the main decision criterion for all our activities. We call this value steering.

As soon as the value is generated by the users in the desired way it is then up to us to enable them to generate also the benefit.

The other way round it does not work: you can do your best in communicating how to generate benefit from your social media application; if there is no value generated by the users then you cannot generate a benefit for the users.

Remark: the idea is similar to the idea of developing a balanced score card for social media applications (see Heiss 2010, p.13 and the new one considering the value steering concept at Djajakusuma/Heiss/Langen 2014). What is your driver-tree in order to achieve a  strategic goal? Value steering is a less complex approach and easier to be remembered and considered for each decision.

Research Question

Concrete for a certain class of social media applications (my focus is on knowledge networking applications for corporate problem solving):

  • What are the key-values for this class of social media applications? 
  • What are the metrics for those key values?
  • Which measures can be derived from those metrics in order to optimize the value generation?

or generic:

  • Develop a value steering framework for social media applications

See also: https://heisss.wordpress.com/2012/09/29/creation-of-invisible-values-in-enterprises/

Please, let me know if you are working in this field or if you plan to work in this field or if you know about already existing research in this field.

Example: Siemens TechnoWeb 2.0

Some examples of TechnoWeb innovations which have been decided according to the value steering approach:

  • The new Urgent Request Channeling based on our semantic message targeting algorithm is the most important TechnoWeb innovation as this allows to generate a benefit from the invisible digital trace value.
  • A Corporate Tagging Framework was implemented. The Corporate Tagging Framework enables to accumulate the digital trace of users across different corporate web applications. The higher quality of the digital trace improves again the Urgent Request Channeling and is therefore a measure according to the value steering approach.
  • The Sinequa-based semantic search engine of TechnoWeb 2.0 as part of the global Siemens corporate search. TechnoWeb also allows to define search alerts not just within TechnoWeb, but for the whole corporate search. Again a measure according to the value steering approach: if a user orders a search alert via Technoweb, then TechnoWeb is able to enrich the digital trace of this person and can therefore improve the Urgent Request Channeling.
  • The semantic suggestion engine of communities which might be of relevance for the user. Again a measure according the value steering approach: if a user becomes member in all Technoweb communities which are of relevance for him, then the digital trace of this user improves.
  • A Google-Map integration for a visualization of all member locations of a TechnoWeb community. Again a measure according to the value steering approach: if the owner of a TechnoWeb community recognizes that his community is less globally distributed than other Technoweb communities he will be more active in inviting new members into his community. The more experts are member in the relevant TechnoWeb communities the higher is the probability that an Urgent Request receives a helpful answer.

This are just a few examples. Approximately 90% of the daily decision for operating TechnoWeb can be done according to value steering principle.

Compliance with data privacy laws and worker’s council regulations

Note that particularily in German speaking countries there are very strict legal data privacy regulations. It is not allowed in an Enterprise context to analyze click-streams of users and you may not even think about analyzing the mail communication of users. Only voluntary and intentional contributions to the digital trace can be used: e.g. if a user follows a tag than he is not surprised that he also receives Urgent Requests in the context of the selected tags; if a user becomes member in a community which is dedicated to a certain topic than he is not surprised to receive per default also Urgent Requests related to this topic. However the user can turn off such notifications.

The research regarding TechnoWeb 2.0 is partially conducted within the competence network Softnet Austria II (www.soft-net.at, COMET K-Projekt) and funded by the Austrian Federal Ministry of Economy, Family and Youth (bmwfj), the province of Styria, the Steirische Wirtschaftsförderungs-gesellschaft mbH. (SFG), and the city of Vienna in terms of the center for innovation and technology (ZIT).
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The Power of Undercover Innovation Projects

Motivation

Recently I chaired a European innovation conference. The participants were mainly global players in the automotive industry, chemical industry, mechanical engineering  or electrical engineering industry. I asked all participants to tell me how one of their company’s most valuable business sector started at the very beginning as an innovation.

The result looks surprising: approximately 50% of their today’s successful businesses started as undercover innovation projects. In German we call this an “U-Boot” (submarine).

Definition of Undercover Innovation Project

An Undercover Innovation Project is an innovation project which is neither registered by the corporate innovation management nor by the higher-level line management, but only known by the project team and their direct boss.

(Note that this is different from a top-secret innovation project, where at least the one who pays for the project knows about the project.)

Most companies do not allow undercover innovation projects

It is understandable that companies and their shareholders like to know – and want to strategically influence – how money is spent in their company.

Why are undercover innovations projects so successful?

It seems that the team motivation is never a high as in the case of an undercover innovation project.

Research Questions

  • Given a significant sample of successful innovations, how large is the ratio of those who started as an undercover innovation? Are this really 50% as in my non-representative conference sample?
  • What is the rational behind the assumed high success rate of undercover innovation projects?
  • What are the required boundary conditions that such undercover innovation projects are successful? (e.g.: the innovators need to understand very well their business)
  • When is the right moment to uncover the project and make it official?
  • Design a set of undercover project rules which are compliant to legal requirements and to company regulations. Goal:  projects which follow those rules are allowed.
    (e.g. maximal size of the project…).
  • Is it possible to transfer the rational behind the high success rate of undercover innovations projects to official innovation projects?

Please, let me know if you are working in this field or if you plan to work in this field or if you know about already existing research in this field.

Early innovation projects need the freedom to find their right way

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