Listening to Anup Sharma, Vice President, Chief Information Officer & Chief Application Architect GE Digital talk at the European leg of Maximize 2017, I could not help but think of the software maxim ‘eating your own dog food,’ because that’s exactly what GE Digital is doing a year after acquiring ServiceMax. The results to date are impressive (see photo above) but as Sharma says, they’re only scratching the surface.
Where are we at?
Today, the focus is upon marrying asset performance management under the GE designed Predix platform and augmenting that through a tie to field service automation. During the keynote session, Sharma described this as bringing coherence from massive amounts of data generated by extraordinarily complex machines so as to deliver productivity gains. In GE Digital’s case, Sharma says it has delivered $100 million in productivity gains. That’s a big number but there is much more that can be done.
The question comes, how will breakthrough gains be made and where do people fit into the equation?
GE customers in industries like oil and gas, aircraft engines and so on are constantly evolving their business models, acquiring and disposing of assets. Today’s focus is on seeing where the business model can become more service oriented. Tire makers for instance are considering whether it is sensible to rent tires rather than simply sell. Any time you talk service in the industrial context, that translates to a need for highly skilled engineers.
Talking to the example of oil and gas, Sharma said that a few years ago customers started to decentralize operations management and demanded that GE do the same. As is often the case, GE endeavored to build its own solution. That didn’t go so well with utilization rates barely reaching 20 percent and some field engineers flat out refusing to use the home grown product because it created work.
ServiceMax was the solution to what Sharma describes as a “fundamental field mobilization capability.” He says the impact was significant:
Every percentage of utilization improvement equals five to seven million dollars of direct bottom line impact for us. We saw sustained improvement of five to eight percent of utilization just as one metric.
Once they had a reduction in non-productive time, our field service engineers started to become an incredible asset for collecting data in the installed base. We saw on average a ten million dollar revenue increase on parts and additional services. In some parts of our business, we were losing paper tickets that tracked work we did. On occasion, we never got paid for work. So we were able to recoup five to seven million dollars of revenue which was work that we completed, that we weren’t getting paid for.
Moving forward, Sharma envisages a time when it may be possible to operate parts of field service in some industries in similar fashion to retail where you buy and pay on the spot. That day may be a ways off but it is certainly a novel idea.
Skills – lost or enhanced?
However, a concern of mine comes from the impact of technology in skilled areas. I recall when CNC machines replaced automotive tool makers. Today it is robots. At the time, life learned skills were lost as people were made redundant. Will the same happen today?
Sharma doesn’t think so. He is of the view that while data collection helps to a degree in building levels of standardization into service, you can never take the skilled field service engineer out of the equation.
While the machines we build are complex and so are prime candidates for data collection, standardization only takes you so far. If we think about an oil rig for instance, each has its own nuance and what we do is put extremely experienced field service engineers onto those rigs who also have knowledge of that rig.
In terms that I understand, it’s not like you’re taking a car into a repair shop and simply switching out a worn tire. So there are two things going on here.
Standardization…to a point
First, GE is capturing operational data and using that to find ways of improving productivity at the field service level. Second, deep domain knowledge is being captured with a view to using that as the basis for training many more engineers. That makes sense because as I have long argued, you simply can’t buy 20 or 30 years’ experience off the shelf.
Second, that means GE can start to think about how it uses the human expertise to enhance machine based data.
As an example, we might have a standard way to fix something but the engineer knows a better way. They will use that knowledge to get the job done more efficiently because it’s in their interests to do so. That may inform a refreshing of a standard or it may be filed away for use in similar circumstances elsewhere.
Bringing the conversation back to today, the key theme of Maximize is the concept of zero unplanned downtime, a good way to explain preventative plant maintenance. Here, Sharma says:
Take our heavy duty gas turbines as an example, we have almost 65% of all failure modes abstracted into algorithms. So, then you can look at real operating data and say, “Hey, there’s some patterns for failure. These are the types of operating conditions I have.”
All of a sudden, the richer the data set, the richer the outcomes are from learning from other people’s experiences in a very simplified way. So, that allows an operator to mitigate conditions that would cause you to have unplanned downtime. In fact, as an operator, you may not even know there is a likelihood of failure. So if we can demonstrate that preventative action now gives a good outcome, then sure, customers are all for it.
Or allow you to operate within safety margins in unprecedented weather conditions or in a hard winter, or run your machines longer in a summer because you can produce the most electricity, but then plan your outage and decide what parts to replace. That’s on the machine side. On the people side, there’s not enough expertise to go around!
As we concluded our discussion I got the distinct sense that GE Digital sees a bright future that satisfies everyone but without the angst associated with labor displacement. I can see why. There is every reason to ditch inefficient processes or burdensome tasks but when you focus upon outcomes, then the entire nature of the job at hand changes. This I believe is where GE is going.
Finally, I have a personal fascination in machines, largely because I don’t understand them and am totally clueless how anyone can imagine how machines come to life. In that sense, I see complex machines as always having an element of craft about them. I suspect that as GE and ServiceMax go forward, they will end up not simply enhancing service operations, beneficial though that is, but will also discover ways to be creative in areas like the design of future machines. And for that, you’re not going to dispense with human ingenuity.
Image credit - via the author.
Disclosure - ServiceMax is a premier partner at time of writing