From non-data-rich plants to dealing with disparate data, in this mini-series, we look into the most common issues and constraints that industrial plants face when it comes to improving operations through data. In this edition, we discuss the difficulties that operators encounter when partnering with large technology companies.
In today’s world, utilising data and AI to drive growth and efficiency is in high demand. Despite this, many industrial plants that have partnered with large tech companies are struggling to effectively use data to drive real performance improvement. But how can this be the case when there is a multi-national digital technology company with an impressive track record driving the transformation? The answer is simple. They’re just not that into you, or rather, they do not understand your plant or your industry.
Unfortunately, this an all too familiar scenario. Large tech companies (let’s call them Big Data inc.), may be data innovators and be in possession of clever digital IP but when it comes to really understanding how to effectively solve problems in a way that gets a plant to operate as efficiently as possible, just being data scientists and digital engineers is not enough. The issue isn’t lack of ability, but rather a shortfall of boots on the ground experience, and a lack of knowledge in how to solve the sometimes complex problems faced by the industrial world.
With no real insight garnered from the initial phase of work with Big Data inc., operators are left in a predicament - feel demotivated and continue to spend an inordinate amount of time working with Big Data inc. to try and get them to the right place. At this point, the entire purpose and value of the exercise will no doubt be questioned.
The fourth ‘D’ - design is also commonly overlooked when operators look to solve complicated plant issues with off-the-shelf software. Often, when an operator wishes to improve their plant and realises the potential value in unlocking data, the journey looks something like this: a phone call is made to a company that offers data solutions, a pitch takes place around a piece of software that not only sings, but dances, the software is implemented, problems arise.
These problems often come as a result of either the software being designed and built around an alternative application for a past client, or it providing a framework that’s far too generic. While the solution in question may have demonstrated benefits in the past, success in one area does not simply equate to success in all applications.
Shoe-horning data into off-the-shelf software packages can lead to a frustrating situation for operators; route causes of pain-points may not be addressed and solved, and valuable opportunities to maximise efficiency and make significant savings can be missed. Instead, a product or tool tailored to specific needs is far more valuable.
AI indeed represents a big business opportunity, but to exploit this opportunity it’s essential to work with a partner that are not only experts in data science and digital technology but are also experts in engineering and your industry. This is necessary in understanding your current strategy, challenges and opportunities faced by your plant and its data capabilities. Combining this understanding with domain expertise, means that the most important and fruitful AI initiatives can be identified quicker, getting to route of the issue more efficiently and proving more cost effective.
At Ada Mode, we work through a framework for implementing data products and digital twins. This framework follows a logical progression to develop the best solution for your plant. From initial high-level reviews to define the problems and the systems through the review of data availability, to exploiting this data and integrating a solution. We include a number of touch points throughout this process, where you can confirm you are happy with the direction and approach.
Would you like to leverage data to make your plant operate more efficiently? Get in touch and let’s work together.