Some of the most frequently asked questions LNS Research receives when clients are planning to scale in Industrial Transformation (IX) are concerned with DataOps and data contextualization.

Follow the money to see the real story

Google the phrase “Pilot Purgatory” and you will see a raft of press articles about the state of Digital Transformation and the Industrial Internet of Things (IIoT). McKinsey and Company, Deloitte, and a series of other firms have published several articles on “pilot purgatory” in IIoT, Digital Manufacturing, and Digital Transformation. IIoT and Artificial Intelligence/Machine Learning (AI/ML) vendors often exasperatingly discuss the successful implementations they have done at the company’s home office that have not translated into wide-scale rollouts. These vendors curse “pilot purgatory.”

Given all the brouhaha, one would expect that companies deploying these pilots would feel “stuck in” pilot and that getting to a wide-scale rollout was a key challenge in front of their Industrial Transformation (IX) Program. But when we surveyed industrials, we found just the opposite. Few companies felt “stuck in” pilot mode and only a fraction of companies identified “moving out of pilot phase” to be a key challenge. So clearly, pilot purgatory is fake news! Let’s look at the facts and see how we can reconcile these different perspectives.

We all know the reality of discrete and batch manufacturers. If you walk into virtually any manufacturing plant, you will find literally hundreds of manufacturing computing applications being utilized. A few of those applications, ERP most prominently, are generally supported by the corporate IT staff. A wider number of those applications, automation and MES, are typically supported by operations itself via the OT team or the “shadow IT” team (the manufacturing engineers, etc., that are providing day-to-day support to these systems). The vast majority of applications are custom – often built in Excel, Access, or Java – and are not well-supported and virtually impossible to deploy across sites. And, the picture gets worse: despite all these applications, operational personnel are still looking for more technology to help reduce manufacturing costs and improve quality.

Since the advent of Manufacturing Execution Systems (MES, or MOM for those who prefer) in the late 1980s, life sciences, and especially pharmaceuticals finishing and packing, led the way in useful MES solutions. Some would argue that MES for pharma has reached maturity and there are few gains to be made. At LNS Research, we believe that change is just beginning and it is time for the pharma software industry to wake up or get severely disrupted by new players.

Many pharmaceutical companies, ranging from boutique startups to the global giants, have active Industrial Transformation (IX) programs that foresee structural changes in the way they operate. Existing pharma MES systems provide the necessary functionality for most operations but are hard to maintain, inflexible, and do not provide a data platform for other parts of the enterprise. Such integration will, inevitably, be a part of IX programs. 

IIoT has become a primary talking point about not only Industry 4.0 (I4.0), but all of the other digitalization topics around I4.0 such as analytics, artificial intelligence, augmented reality/virtual reality and digital twins. The ability to get information from the factory floor and move it anywhere and to anyone cheaply and in real time has driven IIoT into virtually every manufacturer and asset intensive industry client and vendor community discussion lately. With so much focus, both from management and leadership and technical and engineering staff, why then, have so few industrial internet of things (IIoT) projects moved out of pilot purgatory and into full scale production. Some will argue the business case isn’t there yet, others will argue that the technology is not ready or scalable yet while others say something else is lacking like leadership support or adequate deployment and support skills. There is possibly an even more fundamental cause projects are stalling; cultural wars inside the organization are inhibiting progress.

Technology has almost always proven most beneficial when it operates within an ecosystem. The adage “the whole is greater than the sum of the parts” is especially true in the world of technology. Smartphones have changed the world because they operate within multiple technological ecosystems. If they did not allow phone calls to landlines or to subscribers of other providers, they would be of limited use. Without GPS much of the smartphones value would gone. Bluetooth makes lining the smartphone to other devices easy and provides not only wireless headsets but connectivity to vehicles and other devices. What makes all of this connectivity work? Standards. The same holds true in the industrial automation sector.

LNS Research was delighted to be invited again to Dassault Systèmes’ (3DS) annual get together for a small band of diverse industry analysts that cover a wide range of 3DS’ industries and technologies. Quite literally right out of the gate, 3DS surprised us on the bus to the event by announcing that Dassault Systèmes had acquired Medidata Solutions, Inc. for $5.8 billion.

Research analysts from LNS attended the Plex Systems Analyst Day in early November at the company’s headquarters in Troy, Michigan. In an unusual move, Plex hosted its Customer Advisory Board (CAB) concurrently, giving customers and analysts a chance to interact directly. This level of direct access is rare among software vendors and demonstrates a strong show of confidence by the Plex executive team. The Plex CAB includes representatives from companies in automotive, metal forming, food and beverage (F&B), aerospace and defense (A&D), and other discrete and batch manufacturing industries.

In our recent work on the Industrial Internet of Things (IIoT) and manufacturing operations management (MOM), LNS Research has highlighted the inexorable journey MOM systems are taking as they become an integral part of IIoT-based systems and solutions. Much of this journey, when looked at from the outside, is somewhat haphazard to date as each vendor is doing its own thing. Hopefully, that will change as we move towards MOM 4.0, the seventh life of MOM.

Click here to speak with Andrew Hughes

In my long career in manufacturing operations, I have had many discussions with product design teams for discrete manufacturing. These discussions have ranged from pure delight to taxing because while the product designers were smart and creative they were also somewhat self-centred. Sharing of data has been a natural extension of sharing ideas, goals, and success for those of us who have worked together in design and operations, and data sharing usually resulted  in new products.

Click here to speak with Andrew Hughes