Silafrica has been on a journey to adopt industrial IoT technology and use real-time data to optimize factory operations. Akshay Shah, the Group Executive Director of Silafrica, recently had an interview with the CEO of ThingTrax, a company that supplies this technology, about Silafrica’s journey, challenges and what has been learned. If you are considering investing in similar technology, you may benefit from some of these learnings discussed in this interview. Connect with Akshay on LinkedIn to share ideas.
In the final part of this three-part interview series, Akshay and Paul Reader, the CEO of Silafrica’s technology partner, ThingTrax, discuss what has been learned, and what is possible with the right technology in hand.
PART 3: The Future of the Silafrica and ThingTrax Partnership
Paul – The next question on my mind is what stage of the journey you think Silafrica is on, and what challenges do you think that every CEO is going to face when they embark on this journey? Maybe just reflect on where you started, where you are, the challenges that you see, and what you think you’re learning about how to navigate through those challenges of going on a journey such as this.
Akshay – I think that the initial stages are about becoming familiar with the technology. What’s the hardware, what’s the software, just buy a few of the devices and get familiar. After that, we can start putting together a pilot business case and then run a few machines on it. We decided to do that in the three countries where we operate – Tanzania, Kenya and Ethiopia – for two reasons: One is to collect data from a different talent pool, connectivity and infrastructure, and then also different types and ages of equipment with different types of performance. Like in Kenya, we’ve got a machine that does a 2.6-second cycle time. In Tanzania, we’ve got a 2200-ton injection machine that does like a 120-second cycle time. So, just doing that initial pilot allowed us to see how to operate in different contexts and different situations. Once that was clear, we started rolling it out.
During that time in the initial rollout, we started facing a lot of resistance from people on the shop floor; saying it was giving false positive data. Maybe the operator says cycle time is 38 seconds, but the system shows it’s actually 32 seconds. So, that disconnect between what people are seeing to what the system is showing created a huge lack of confidence in the system. Remember, the status quo had always been depending on data that was coming from people. So, we can’t keep doing that and having people wasting time double-checking. That’s what installing IoT was all about – it doesn’t have to second guess.
As for where we are today, we are using new ThingTrax devices which don’t need network infrastructure, so at least connectivity issues should all be resolved even in remote locations. Lessons learned are that the technology cannot be second-guessed. Once the technology is proved beyond any doubt, that’s when we can start focusing on the change management and human element. We can’t focus on the human element if people are still second-guessing the technology.
In order for us to prove this to our staff, we hired someone from outside the factory whose performance was based entirely on delivering business benefits but who had no allegiance with people involved in the current factory culture. People who have maybe been running a particular moulder at 38 seconds for the last ten years, and all of a sudden, it becomes apparent that they have been padding an extra six seconds to the cycle time when we could have been running at 32 seconds all these years. It’s not that hard to pad an extra five or six seconds to cycle times and give yourself a much easier workday. We needed an outsider to reveal the reality of cycle times that could be achieved if people weren’t taking it easy and show what is possible for us if workers are skilled and sharp on their game.
Paul – You mentioned bringing someone in from the outside that doesn’t have any allegiances or any reason to protect information and so on to preserve themselves: What skill sets do you think are absolutely essential for that person to have for them to be successful?
Akshay – When we were going through the interview process for this role, it became very clear that the person had to have a data analytics capability where they could link data analytics to business outcomes – this is the key thing. We don’t really need someone who is an IoT hardware specialist per say. They need to appreciate it and believe that this data is coming from something that they can understand, and not coming out of some black hole. If not, they will go back to that behaviour change and change management issue, “Can I trust the data? Can I rely on the data?” Having an understanding and an appreciation of IoT so they can believe the data is the only hardware capability they need.
After that, then it’s really about knowing how to use the ThingTrax platform to connect and ascertain business outcomes. That is the main capability. Analytics and a commercial understanding of what we want from the business. They should essentially be someone who isn’t responsible for achieving a better outcome, but they are responsible for showing gaps of where we could be versus where we are. It then goes to the technical team, production team or the HR team; or whoever is needed to be able to close the gap. If we give the maker the checker’s responsibility, then we’ve kind of gone back to square one from a change management perspective. So, it’s also important that the analytics person is tasked with using the data to identify improvement areas. The more improvement areas they can identify, the higher their performance. It has to counteract the biases and incentives on the shop floor.
Paul – One of the audiences for an output of this conversation is fellow CEOs in the plastics industry. If you were to speak directly to another CEO in your industry, what haven’t you said that you would want to say to them? What advice would you give them if they were thinking about this type of thing?
Akshay – I think the main thing is to overcome the belief that the people on the shop floor are giving you an accurate idea of what’s happening. There’s this internal paradigm shift of believing in data vs. believing in people. I’m not saying don’t trust people – but if there’s a lot of time being spent collecting data, and there’s inherent mistakes and biases and filters in that data – which you probably have no idea about – make the paradigm shift. Believe in the data, and then empower the people with that data to go and do the right thing.
If you’d like to learn more about implementing ThingTrax in your own factory, simply input your biggest manufacturing challenges into this form and one of our Factory Advisors will come back to you with a list of solutions tailored specifically to your needs.
Or, if you want to see ThingTrax in action first, book a free trial with us here, where we’ll connect your factory and give you access to real-time analytics and insights from your own machines in less than a day.
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