A few weeks ago during one of our regular meet up sessions, a plant manager expressed his excitement over his company implementing the first phase of its digital transformation – and that they were now moving to phase two.
My immediate response, after offering my congratulations, was to find out what business issue he had addressed. This surprised him momentarily before he replied “I don’t know.”
Far from being a one-off, I see this more often than you think. Companies in the pharmaceutical industry know that a data-driven transformation is the way forward. They invest in the latest hardware and software solutions, but what they don’t always consider is the individual issues that a transformation is supposed to address.
There is so much hype around technology, with Industry 4.0 driving a lot of what we see today. But I have even heard talk of Industry 5.0 and even 6.0… where does it stop?
Investing in technology is only a small part of the overall picture. Companies need to take a holistic approach and examine every facet of their operations and then examine the solutions that are available and determine which ones best fit their overall objectives.
It’s pointless having a Ferrari if you can’t drive. Sure, it looks good outside your house, but you are not realizing the value of what it can deliver. And this is what you are missing out.
What we are seeing, especially in the software realm, is more of our pharmaceutical customers looking to find solutions that will allow them to personalise products, reduce costs, become leaner while being able to launch products to the market quicker.
But the pharmaceutical industry has additional realities too, especially when it comes to regulations and compliance. These realities mean that a lot of work is going into their data capabilities and integration, not only in terms of gathering data, but also working with the right data and using it as a basis to make decisions.
The most evocative question to then ask in this instance is: do they trust their data and the resulting reports?
Customers are telling us that they want help getting more insight into all the data they have around their supply chain and then get this data into a useful form. When we discuss this challenge, more often than not, the first response is “give me the use case.”
“Don’t implement technology for technology’s sake. Have a plan – have a few plans – and prepare to have some of them rejected.”
But how can you give a use case for something you don’t know? They say “we want to launch products faster” or “we want faster FDA approvals on installs and products,” both of which involve aggregation of tremendous amounts of data. Our response: don’t focus on the first use case – look at all the other objectives you can achieve using this data.
The more you mash data, the more you find out, such as trends and correlations. You can even start making predictions using analytics, which can help identify areas to improve speed and efficiency.
But will they take into consideration all of the consequences? This upsurge in data volumes is leading to the creation of new job titles. I have seen “growth engineers” and “data scientists,” whose roles are to deploy algorithms to find correlations and insights.
But they can only be effective if they look at the big picture and get buy in from all disciplines – otherwise they are still isolated decision makers working on a plan that was designed to remove the very silos they have just recreated.
There are certainly a lot of algorithms out there that can solve single scenarios, but algorithms cannot add contextual or conceptual intelligence. This type of analysis and decision making must be done by a human. Which leads us neatly onto the next issue: do your people have the right skillset?
Organisations must manage people and train them so they can learn and collaborate with all this new cyber intelligence. They need to be able to ask “what do I need to know to make wise decisions?” as opposed to “what will the data tell me?”
So, my advice. Don’t implement technology for technology’s sake. Have a plan – have a few plans – and prepare to have some of them rejected.
Make sure phase one is not just to tick a box, but instead implemented to solve an issue or create the foundation to solve many others. Don’t get tempted by buzzwords – understand the benefits and ask what they can do for you.
Learn how to implement technology, taking into account that it changes every three to five years, and then balance this with the fact that us humans can take longer to adapt.
Think about scalability, upgrades, ease of use and migration. And once you have all these bases covered, your digital transformation should actually provide the springboard you are seeking.
Originally published here at Rockwell Automation’s Blog.
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