Innovation Automation –

Proposal for a Strategic Research

Agenda

Presentation at DIGILE Foresight Seminar

28 January 2015

Helinä Melkas & Jari Porras

Lappeenranta University of Technology

Agenda

− Background

− The idea

− The first draft of research themes

− What kind of partners are needed

− Initial potential breakthrough targets

− Motivation for the proposal

− Contacts for discussion

Background – Paul Hobcraft

“…Yet today we still have a fragmented, often broken innovation

process, very reliant on the manual processes, where the human

intervention dominates. Can this be changed? Technology must

form a greater core of the innovation process.

We still are very reliant on stage gate intervention points, often more

due to dogma and imposed oversight by committees occasionally

meeting. Decisions are determined by the human, based less on hard

knowledge or dynamic intelligence, often these have tended to be

thinner on the ground to validate concepts and judgement becomes

highly personal and reliant on (past) experience. What can we change

within this? There are leading practices to compare and contrast with

but we do need to push this automating the innovation process

further, in different ways.”

Background – Haydn Shaughnessy

“What you have now is a set of data streams that will allow

you to automate your company’s innovation priorities. The

data is reflecting what needs to be changed in your product

to make it perform its functions in ways that are better

suited to different types of users.”

“The likelihood is that innovation programs in the future

will be much better coordinated within a system, and

they will be dictated by algorithms rather than decision

making.”

Innovation

automation

− Efficient and effective use of ”co-creative intelligence” – the fusion and mixture of

artificial intelligence, human intelligence and the intelligence of the crowds

− Aimed for a new kind of operational environment

− Changing business logic; new kind of entrepreneurship: micro-enterprises,

(social) networks, ecosystems, platforms, technology adjacencies

− Expertise does not depend on organizational boundaries

− Too much information and knowledge; too many opportunities

− No standardized product development process, out of the box of traditional

R&D&I thinking, R&D departments will vanish?

− Changing values of generations, differences in values of generations

Obtainingthe information and knowledge

What to do with it? By whom?

Innovation automation

Technology and automation

Innovation and people

The idea

− In our view, innovation automation is strongly related to and depends,

first and foremost, on acquisition, refinement and transformation of

information and knowledge.

− We focus on four types of knowledge:

− The giant space of bits, available for data mining – codified

knowledge.

− Processed versions of the above-mentioned codified knowledge, i.e.,

big data (achieved with algorithms as data mining tools).

− Assessment of needs concerning what knowledge should be

considered in those algorithms. This comes close to tacit and self-

transcending (highly future-oriented) knowledge.

− Implementation of the innovation process itself as interaction

between people (with the help of technology). The aim is to speed up

the process and improve quality. This is also a playground for tacit

and self-transcending knowledge.

Innovation processPeople’s interaction, knowledge interaction,

process quality, need for speed, innovation tools and automation, crowdsourcing

Data sources – Big dataCustomer data – Market data – Research data…

Codified knowledge

Self-transcen

din

g kno

wled

ge

Data processing – algorithmsProcessing codified knowledge

Demand of knowledge in different phases of innovationAnalytical and synthetic codified knowledge for innovation process

Self-transcending knowledge

CO-CREATIVE INTELLIGENCE THROUGH INNOVATION AUTOMATION

Draft research themes

− How can innovation processes be promoted at different levels with the help of

technology: Environments – where? Processing – how? Assessment of needs – how?

− The element of surprise in the process: from exploration to exploitation

− Speed of the process – but not as an end in itself (promotion of self-transcending

knowledge while simultaneously raising things from the wealth of data, information and

knowledge, also experience knowledge)

− Early recognition of trends. Using big data to find trends? Effects of colliding trends?

− Problem and solution: how to automatize finding them and how to combine them?

− How to combine creativity and scalability/repeatability? Different actions for different

parts; not possible to automatize the whole

− Knowledge conversion processes (their automation), quality considerations of

knowledge

− Which are truly functional groups? Innovation is a cultural thing (note also languages,

culture; bias towards English). What structure is needed for the organizational level?

− Use of idea/innovation management tools to make ideas and hunches collide. Matching

these according to the company.

− How do hunches occur? How to increase sensitivity towards various things to enable

more hunches?

Possible partners (competences)

- Information systems and software solutions experts

- Big data experts: data mining, fuzzy logic, self-organizing maps,

neural networks, pattern recognition, text analytics, social network

analysis

- Innovation management, innovation systems experts

- Knowledge management experts

- Creativity experts

- Design and visualization experts

- Linguistics, cultural experts

- Behavioural sciences experts

- Social psychology, occupational health experts

- Start-up businesses, entrepreneurship

- Business models, business and asset management experts

- Political science, law experts

Initial potential breakthrough targets

- Conceptualizing an innovation automation ecosystem

- Innovation by computation

- Conceptualizing innovation automation as a Finnish success story

- Strengthening the element of surprise

- Skilled automation of creativity-related things; co-creation

- ”Need of the day”: people’s thinking has an impact on what becomes a success in the community. Big data on people’s thinking as a basis for simulation.

- Intellectual cross-fertilization: creating more hunches by bringing in seemingly irrelevant and non-connected things and inputs

- Inclusion, equality: enabling different approaches for different people

- Sustainable innovation (socially, economically, environmentally)

Motivation for the proposal

- Experience in obtaining deep customer insight with novel

methods

- Strong innovation research + strong competence in ICT

- Systemic thinking

- Truly holistic views are needed when discussing

innovation automation to have feasible aims for it

- intellectual cross-fertilization

- people and innovation vs. technology and automation

IF INTERESTED - ACT

• Send email to innovation-automation-sra-interested-partners@digile.fi

• Content

– Name of the interested organization

– Name of the contact person

– Potential interesting research themes

– Initial annual budget for participation

– Willingness to participate in writing the SRA

• Contacts for discussion at LUT, School of Business and Management, Innovation and Software

• Prof. Vesa Harmaakorpi, vesa.harmaakorpi@lut.fi, tel. 0405751965

• Prof. Helinä Melkas, helina.melkas@lut.fi, tel. 0405881400

• Prof. Jari Porras, jari.porras@lut.fi, tel. 0400555427

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