Last week I spoke individually to over 50 business professionals about artificial intelligence, and maybe 10% at most understood the capabilities of the different mathematical technologies that fit under this umbrella term. It is not that they don’t understand in broad terms that “data is the new oil” or that there are amazing technologies out there that can recognise words, faces or solve complex problems.  Where they appear to be bemused is being constantly told AI is the solution, but to what? As one very experienced Service Leader mentioned; “AI is so overwhelming, it is blocking peoples thought processes”.

The bland benefit statements professionals are fed by the media and solution providers do not solve business problems. Business is far more complex than that. If you believe, as I do, that the ability to turn data into intelligence is what gives companies a competitive advantage, then maybe the answer to harnessing these technologies goes deeper than understanding the maths. Perhaps what holds companies back is that despite the rhetoric of leaders, ‘Data Thinking’ is not truly an explicit part of the DNA of their organisations.  For those old enough to remember, a similar issue was observed with implementation of Six Sigma and Lean principals, which integrated the use of data and analytics into the continuous improvement process. My experiences this week made me question how deep was this shift and maybe we need to start the cycle again?

So what tipped me over the edge to write this blog? Well let me tell you about my week.

I was involved in running workshops for a Luxembourg Government initiative call the Digital Skills Bridge. This excellent initiative in partnership with local businesses aims to help people develop their digital skills. It was a chance to talk to very bright business professionals who were generally engineers, project managers or analysts about data. Some of the companies involved would regard themselves as being leaders in their digital journey. Given this, we were expecting a good conceptual understanding on the ‘mathematical technologies’ that support data analytics such as machine learning, business intelligence, predictive modelling & visualisation.  We found a very limited understanding, which was surprising as these were well qualified numerate and intelligent professionals. To us it indicated that the culture of using data to solve business problems is not quite so sophisticated as one might have thought.

I was at the Field Service Forumconference in Amsterdam, talking with over 150 B2B service professionals. The round tables I ran were on ‘Artificial Intelligence to Automate Service Management’ and discussion on Augmented Knowledge.  To the question, ‘What is Artificial intelligence’, perhaps 2 or 3 were able to articulate some of the technologies that lie under the AI umbrella. What surprised me was that this was after they had an excellent 2 hours presentation from a leading futurist on the impact of AI on the world, as well as 3 – 4 solution provider presentation, each of which told them how AI was being used to improve business performance. Yet here we were, a matter of hours later and a sea of blank faces to a simple question. 

What was happening? As we progressed the discussion, what became clear is that Artificial Intelligence will not automate their business processes as such. That statement is like providing an answer before the question has been asked.  The approach they felt most comfortable with was to understand the problems they have with their processes, and then work back to the solutions, which might involve advanced analytics. A great example came from a Zepplin, a $1billion Caterpillar distributor who had developed a mobile solution for their service technicians. To speed up the completion of the service report using their mobile phone, they started to use voice recognition software. The technology at it’s core is based on advance analytics, but what is important for everyday managers is an understanding of the use case and how it could apply to their processes.

Another example might be how to use the knowledge that resides in Service Reports to be more effective. To say we can use Artificial Intelligence to extract insights is meaningless. It is much more useful if we understand that we are looking for patterns in our Service Management reports and that technologies such as ‘Machine Learning” can help us achieve this goal.

What also came out is that when using advanced data analytics techniques, the objective is to achieve a business result. In particular first understanding the KPI’s we are trying to influence, the business challenges we are solving, and then understand the technologies we might deploy. What was also interesting is that to get started, many companies tried a series of pilot projects to better understand what these technologies could do for them. It is a bit like the age-old question ‘what comes first, the Chicken or the Egg’. They emphasised the most important action is to ‘START’ and break into the cycle of innovation, even if the outcome is not initially clear.

But what does start really mean. Yes we can do technology projects to learn how to use these concepts, but on reflection this is too superficial to be lasting and can lead to burning a lot of money (just look at GE Digital). For most practical business people, the use of these technologies is not so much about the technology, but it’s application and when it comes to data, to have the cultural mindset to use data to find insight.

I am no data expert, but I know my own early professional experiences shaped my data mindset.  From being a young engineer being taught to use advanced statistics to reduce the number of tests to optimise a system, to realising that our Fastener Full Service that kept the Ford Fiesta assembly line running was more a data than hardware business.

A more powerful example is to look to formula 1, probably one of the most competitive data centric business you will ever come across. In a recent article from The Manufacturer, Toto Wolff, Team Principal & CEO of Mercedes-AMG Petronas Motorsport stated:

“Data is becoming increasingly important – not just in the world of Formula One, but the world in general. In F1, we use our data on our relentless search for performance, across all functions of the team – both at the track and at the factory,”

Indeed in the article there is a striking parallel drawn to service where structured data comes from the F1 Car and supply chain, and the unstructured data from the drivers (your service technicians).  One can sense that  for the Mercedes F1 team, data is at the centre of every decision making process. It is simply part of what that team represents.  

To be clear, I am not saying that Artificial Intelligence and the related technologies are not relevant to today’s world. Far from it, with the exponential changes in computing power they are more relevant than ever before. What I do believe is that the way to harness the technology is not the technology itself, but changing how we think about our jobs and our business.  Now for some that may be to put Digital in front of job titles and change projects. If it is a case of raising awareness that is fair enough, but in itself will not move the organisation on in the long term. What is needed is to bring the power of data into the DNA of our organisations, to develop cultures where data and innovation go hand in hand and where people understand appropriate tools to use in different situations. Only then will an organisation really leverage the data in their organisation and their value chain. 

On that note I will leave you with a short story about Graham Cooper, Site Manager at Agfa Graphics Leeds Production site, who I had the pleasure to talk to and write about last year. In 2001 after a major restructuring, to survive and prosper his manufacturing site turned to the data being produced by their production system to manage quality and maximise throughput. They succeeded and are still here today!  A significant reason for their success was a change in culture from  ‘How do I stop that fault from happening’ to ‘How do we understand what happened, how do we get the process under control, how do we eliminate the problem’. A much more sophisticated way of thinking about their business from the shop floor to the leadership. And now, only some 15plus years later, with a fundamental culture change in place, does he now feel they are mature enough to work with advanced data analytics. 

Many of you will want to go faster than this but the message is clear: 

The mindset of “data to improve business” is as important if not more than the AI technology itself!

Nick Frank is Managing Partner and Co-Founder of Si2Partners helping companies leverage services to win in industrial markets. If you have any questions on this blog, he can be contacted at