How to turn the right mental knobs to change the way people (want to) work

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Introduction

Hi, I am Sarah Zheng, a cognitive business consultant at IBM in Amsterdam. In this role, I advise clients on how they can leverage the power of AI-technologies to improve their business processes.

In this blog series, I want to give you my vision on why many projects where new technologies are introduced, fail to scale up. More importantly, I will propose a social-behavioural approach to form a human-centric strategy to successfully integrate technological innovations in your business.

To do so, I will do a psychological deep dive with you on the topic of how to achieve behavioral change and apply this to the adoption of new technologies. Essentially, we will answer the question: how do you achieve behavioral change in the way people (want to) work? This is a relevant and often overlooked question especially if you are in a senior management position and you are wondering how to innovate. In this first post, I introduce the drivers of current problems I see that clients face with adopting new technologies.

Cycling through innovation processes

Last year, I visited the director of an innovation hub within a Dutch governmental organization to talk about their innovation development process. A colourful image of a cycle with six different stages was laid out in front of me. After letting his much younger, bright colleague talk me through the process, the director asked me what I thought of it. I liked how it seemed a good attempt of establishing the basis for the organization’s approach to keep up with technological innovations. However, it lacked a more quantifiable, objective success measure for each of the cycle’s phases.

Moreover, I did not see how this approach would truly engage and enable his staff to start using whatever innovative technology would be put forward throughout the process. For instance, the last phase’s process of scaling up successful use cases with both technical and organizational conditions was not described further at all. This way, it will be very hard to objectively justify towards employees why they should start using any new technology at all.

Like in the above case, we still see different shortcomings in innovation management with clients which show how many organizations simply do not seem ready yet for large-scale implementation of new technologies.

Why so?

Many “proof of concepts” illustrate how early adopters are dipping their toes into the (technological) innovations pool, but even they often do not dive deeply into it to embrace all that is possible. In just one year I have heard of many cases where people would be enthusiastic about a successful use case, but the client does not decide to further implement the technology. Why do we see this problem of not upscaling successful use cases to full-blown implementation in complete business processes?

I believe there are three main factors that explain why this happens:

1. No willingness to change (therewith, improve) ways of working.
2. No possibility to change (improve) ways of working.
3. No sense of urgency to change (improve) ways of working.

No sense of urgency to change

From bottom up: no sense of urgency could mean the organization perceives itself as working fine as it is. It may not see why it should change its current operations. Maybe production flows are already optimized with state-of-the-art machines and employees seem to be satisfied with their work. In Dutch we may say “alles loopt op rolletjes”. On the other extreme, senior management could be too preoccupied with keeping current processes running, with no time to think of the longer term (“alle ballen in de lucht proberen te houden”).

No possibility to change

No possibility to change or improve ways of working encompass practical conditions which are mainly of budgetary or technical nature. For instance, lack of investment budget to upgrade IT-systems to smoothly run more advanced applications or a shortage of technical personnel.

No willingness to change

Lastly, no willingness to change is mainly due to a lack of or biased understanding of what value new technologies can bring. Maybe the organization has a wrong understanding of what AI actually is. Maybe you rather choose to maintain the current situation, because you are afraid of the impact new technologies will have on your own employability.

How do you deal with these situations when (you know) there is a great technical solution that will improve a client’s business? In the case of a lack of sense of urgency: how do you let the CEO understand that the organization is not actually producing at its maximum capacity and that investing in a robust predictive model for production logistics could help to increase profitability? How do you redistribute internal budgets to create investment possibilities for technical innovation? How do you convince your employees of the value of working with new technologies?

The answer lies in first having a clear vision, understanding the technology and then understanding the psychology behind changing behaviour – not in designing a structured innovation development approach per se. Because implementing new technologies from small proof of concepts to scaled-up integration in practice demands a change in the way people work. This is why my upcoming blog series is dedicated to the science of understanding why people behave the way they do and how to change the way they behave. So that you get to understand better how to create the right organizational environment and turn the right mental knobs of people to change the way they really want to work.

In the next post I will outline the conditions for a constructive innovation approach and introduce the behavioural framework with key factors that can explain, predict and change behaviour.

Until then!