Industry 4.0 organisations: The Three Intelligences
This is an article supplementing a 4-part series re-thinking integrative aspects of industry 4.0 organisations:
Part 1: Identifying Threats and Opportunities
Part 2: The Organisation (Re)Invented as Player, Organism and Machine
“Do not follow where the path may lead. Go instead where there is no path and leave a trail.”
– Ralph Waldo Emerson
Introducing The Three Intelligences
Research strongly indicates that the most successful corporate innovation strategies are the ones that predominantly focus on people and human capital issues, these strategies include [KPMG 2013, with ref. to Conference Board CEO Challenge 2013]:
- engaging in strategic alliances with customers, suppliers, and other business partners
- finding, engaging and incentivising key talent for the purposes of innovation
- promoting and rewarding entrepreneurship and risk taking
- developing innovation skills for all employees
Humans (HU) and (AI) is [HU + AI]
“For all the focus on software and hardware, Jacobstein’s thesis is that humans are as critical to the AI equation as machines. He points to the number of AI startups (Turi, Nervana, and DeepMind, to name a few) in recent years in which talent was the primary driver for acquisition.” [Singularity Hub. 7 Key Factors Driving the Artificial Intelligence Revolution.]
For those wanting to bridge to AI, what human dimensions need to be understood? We can understand AI and can sum this up as Neil Jacobstein (chair of Artificial Intelligence and Robotics, Singularity University) that [HU + AI] will outperform [AI]. [HU+AI] we call PI, or Process Intelligence, which may or may not involve AI at all, but does involve the use of electronically driven machines inside the organization, acting as a machine.
However, as most ‘experts’ know, this isn’t humans versus machines, but a humans and machines driven future. So we can add Sector Intelligence into the mix, the intelligence of knowing the characteristics, determining factors, value drivers in any given sector. Sector Intelligence = [SI], this is the sector knowledge that leads to effective organisational and business processes.
[HU + AI] + [SI] will outperform [HU+AI]
How do we develop the ability to develop the right insights in the first place?
To develop anything, we need to embrace collective intelligence, using all of the human resources at our disposal. None of which can come into play hello without the addition of collaboration intelligence. Interfacing the three intelligences, we need to understand in detail, what we mean by each in turn that:
[CO-I] + [HU+AI] + [SI] will outperform [HU+AI] + [SI]
The future for digital-human transformation is about developing interfaces, between data capture, integration, analytics and developing New Human Capital.
The Three Intelligences Explained
1. Intelligence from the perspective of the Machine: PI
The one thing separating the disrupters from those doing the disrupting, is intelligence.
What most disrupters have in common is Business intelligence — the gaining of insight from data. Whether being Industry 4.0-driven, marketing and other strategy driven, or simple innovation driven, to be sustainable today means leveraging data to gain insight as intelligence. Insight is about ‘being human’, what Bill Fischer called ‘the only real hope for continued differentiation in the business of expertise’ [Fischer 2015]. Business intelligence is known from the world of data-driven analytics, but it exists exclusively in the context of data. It doesn’t account for the intelligence derived from changing things, but from what has been, is and could become.
This is why ‘machine intelligence’ has become so important — intelligence being for example, the purchaser who spent more than intended, because a venue had more offers than expected, or that the limit to transactions was reached quicker in the month than is normally the case — exceeding the ‘benchmark’.
Machine Intelligence is seeing the reasons behind the data, informing insight concerning what needs to be done next, or what is going to happen in other, similar situations.
DIG DEEPER (link to article on medium.com)
2. Intelligence from the perspective of the Player: SI
To disrupt means to reinvent and create new value, using new technologies to do new things in different ways. AirBnB and Uber are often-quoted, often-hyped examples. Amazon and Tesla are another. What they all have in common is offer lower prices. They also provide the experience of choice — choice, based on data, integrating the drivers needed to define a service: as availability, of locality, of time and location.
So while disruption with regard to IoT is real, very real, telling how far a car is from a pickup at a given location, or the SatNav telling us how long it is going to take us to get to our destination, it is the consequences of IoT that are the most disruptive. By consequence, I mean the experience of choice made available by integrating different kinds of data together. This is not big data, but small data, put to good use - creating value.
Data-driven value development is not about machines, but the experience of gaining intelligence useful to a particular sector. This is telling where things are, what state they are in, or a prospective customer information concerning if they need a new product at all.
IoT is a sector-based ‘big value’ defining agenda
DIG DEEPER (link to article on medium.com)
3. Intelligence from the perspective of the Organism: CI
Industry 4.0 is the ‘intelligence generation’, the engine behind change in any given sector. And to have intelligence, first we need to develop the right insights, using people skills, feeding data into the time-honoured fashion of using guesses, hunches and predictions
[Fischer 2015] and turning them around to provide real, real-time measurable value. When we see value in these terms we can see that, with so many industries and sectors being disrupted and realigned, perhaps the greatest value of all is how we see and view people and people-based expertise; how they can be aligned to the new reality where data-derived services replace managers in suits defining where an organisation will be five years down the road.
The organism optic is about Human Capital and how it can ‘plug in’ to new-tech.
What data is required has to be defined by each organisation, using frameworks that don’t plot one course of action, but define many, ordered by who-with-the-how. This is after all, then age when age itself is an undervalued resource, where sector experience, project-based teams and hybrid jobs descriptions can be infinitely more valuable than a regular workforce composed of new MBA or Ph.D’s, leveraging collaborative intelligence into sector-based processes of discovery.
DIG DEEPER (link to article on medium.com)
In the next article, the last in this series introducing Organisation 4.0, I look at how all three intelligences can be integrated, aligned and used to create value, where value may not already exist, for digital-human transformation.
About Base
Base is a Copenhagen-based network re-thinking the interfaces for digital-human transformation, bridging data-centric sense-making to human-centric value development, by data-centric design.
References
Fischer, B. (2015) The End of Expertise. HBR online Oct 19, 2015.
Fischer, B. (2016). The Death of Strategy. Forbes online Nov 26 2017
KPMG (2013). HR as a driver for organizational innovation. KPMG online publication.
Morris, L. (2013): Strategic Doing: A New Discipline for Developing and Implementing Strategy within Loose Regional Networks, Australia-New Zealand Regional Science Association Conference December 2013
