Whilst there has been a lot of hyperbole around the impact Artificial Intelligence will have on field service operations, Nick Frank points out that it is not the answer to life, the universe and everything and we should understand our own potential use cases before rushing to implement such solutions...
What does AI mean for your business?
A sea of blank faces.
This was my experience having recently talked to about 25 service leaders at the Field Service Forum, in Amsterdam. Their reaction was not due to a lack of understanding. Most had just listened to a futurist painting a picture of the potential impact of AI, followed by various solution providers providing their own visions. They had been told that “data is the new oil” and that there are amazing mathematical technologies emerging 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 said: “AI is so overwhelming; it is blocking peoples thought processes”. As the discussions deepened, what became clear is that AI will not automate their business processes as such. For those fans of the cult book The Hitch Hikers’ Guide to the Galaxy, this statement is like providing the ultimate answer to everything ‘42’, before the question has been asked.
However, give them a problem and work back to the solution and the tone of the discussion completely changes. For example the $billion Caterpillar distributor Zepplin, in order to speed up the completion of service reports for their self-developed mobile app, introduced voice recognition software for use with mobile phones. The technology at the core of this application comes under the umbrella of AI.
Another example might be how to use the knowledge that resides in service reports to be more effective. To say we can use AI to extract insights is meaningless. It is much more useful if we understand that we are looking for patterns of failures in our service management reports and that technologies such as Machine Learning can help us identify failures that seem to have the same or similar root causes.
The conclusion is that it is more important for managers to understand the use case and how it can be applied to their processes, rather than the technology itself. The truth is that being fed bland benefit statements by the media and solution providers does 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 potential of 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.
"The truth is that being fed bland benefit statements by the media and solution providers does not solve business problems...
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. Maybe we take it for granted that ‘Digital Natives’ know about data. They may understand the handsets, social media and the world of apps, but do they know how to use data to drive decisions and actions?
What also emerged from the discussions is that when using advanced data analytics techniques, the objective is to achieve a business result. In particular, first understanding the KPIs 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.
"The way to harness the technology is not the technology itself but changing how we think about our jobs and our business..."
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. For most practical business people, the use of these technologies is not so much about the technology, but its application and when it comes to data, to have the cultural mindset to use data to find insight.
A powerful example is to look to Formula One, probably one of the most competitive data centric businesses you will ever come across. In a recent article from The Manufacturer Toto Wolff, Team Principal and CEO of Mercedes-AMG Petronas Motorsport said:
“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, 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 AI 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 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. The mindset of “data to improve business” is as important if not more than the AI technology itself!
If you would like to get your team thinking about how to develop meaningful business solutions that may or may not use AI, then you can contact Nick at email@example.com