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It’s Time to Get Circular with Data

Rewriting the rules for collaboration in the digital age.
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While considering a theme for this column, I read an IW piece by supply-chain expert Paul Eriksen calling for a new era of collaboration between OEMs and suppliers. It confirmed my thinking that really capitalizing on the Industrial Internet of Things (IIoT) won’t just require changes in what we make to benefit from the new potential to gather and act on real-time data about things. It will also require changing how we run the companies that make those things.

As I concluded in my book on IoT strategy, it’s time for the IoT-based “Circular Company”—a company that has real-time data as the hub around which every internal function as well as the supply chain, distribution network, and customers continuously revolve.

This vision of circular organizations is speculative. Yet I believe it is a logical consequence of the IoT.

Here’s why.

When the Industrial Revolution began, there were two models for large organizations, the Catholic Church and the army. Because of the lack of real-time data, it made sense for new companies to manage information the way those organizations did: top down, and in linear fashion, parceled out to different departments sequentially and only when senior management decided it was relevant. In fact, the early railroads often turned directly to the army for policies and procedures.

Today, the limits on data gathering and sharing have been removed. In addition, collaborative tools have become robust and increasingly popular. Yet even IoT startups are still structured on the old hierarchical and linear models.

Others, most notably Russell Ackoff in the 1990s, have proposed circular organizational styles in the past, but they have never taken off. I argue what makes today different in terms of the potential for circular organizations is that, for the first time, the real-time data from every aspect of the organization can be gathered and shared instantly (and that potential sharing also includes the supply chain, distribution network, retailers, and customers using the products every day in the field).

Real-time data sharing changes everything from the days when it was equally hard to gather the data and to share it, making sense for management to parcel out things as it saw fit.

Contrast that to real-time sharing of real-time data. Data coming in right now via the IoT from a product’s operations can be analyzed and used almost at the same time by:

•     Maintenance, to predict possible problems and intervene via predictive maintenance to minimize cost and interruption to the customer.

•     Design, to document patterns of problems either with parts or ease of use that can be used to design upgrades that will be more dependable and user-friendly.

•     Marketing, to see if there are consistent patterns of product misuse that indicate the need to rewrite the manual, or to add new features.

•     Supply chain partners, to see if certain parts need to be replaced more frequently in one area than another (for example, jet turbine parts in areas with windblown sand).

Even more important is the potential for innovation and creativity if all those groups look at and can discuss the data— ground truth — simultaneously. That’s where new groupware such as Monday.com and Smartsheet come in. Clearly, the growing popularity of these programs and collaborative workstyles such as Scrum shows the underlying demand for collaboration and circular approaches.

Think of how many benefits in the various interrelated phases of the IoT could be maximized by such an institutional framework:

•     The digital twin could be the consistent focus for all functional groups, so they would always be focused on the smart, connected product. The cyclical design process that has shaved off so much time for GE could become the norm.

•     Supply chain partners who could see the current status of production could resupply in time to avoid interruptions. Most likely, this would be done automatically, through machine-to-machine processes. Suppliers could also suggest refinements in parts based on actual data from the field.

•     Realtime sales and distribution data could alert the assembly line to slow or increase production.

•     Predictive maintenance data would help designers target parts and assemblies where there are consistent problems.

The results could be dramatic. In a survey by WiPro Digital and Forum for the Future, they found that “… focusing on cross-functional discipline can lead to the creation of disruptive and systematic solutions. When employees are networking and actively sharing projects and resources freely across departments, it creates a fluid exchange of information among groups and individuals of varying areas of expertise, which in turn can spark new ideas and inspire experimentation. Innovation often follows.”

Matthias Roese, global chief technologist for Hewlett Packard Enterprise, describes a similar concept in an emerging approach called “closed-loop manufacturing,” which:

“…leverages the vast amounts of data that are already available to industrial companies but are often locked away in silos and, therefore, underutilized. The general idea is to take all the data generated by different departments and stages in the process and, instead of keeping it in data silos, make it available for participants across the organization.

The data is not shared haphazardly, however. For an auto manufacturer, closed-loop manufacturing uses structured processes and continuous data flow that starts with R&D, design and prototyping, production and aftermarket services, and circles back to R&D, creating a virtuous cycle.

We have seen how the IoT can change how we design, manufacture, market, and maintain a staggering variety of things, inextricably melding the physical and digital worlds. Doesn’t it make sense that such sweeping change might also affect how we structure and run the companies that make these things?        

Yes, there are thorny questions to answer to make such a system work. There still would be a need for a formal reporting structure to avoid chaos. Supply chain and distribution network partners would only get limited information, on a need-to-know basis, and this could only be done with those partners with which you had built long-term, trusted relationships. Assembly line workers using software such as Tulip would only get the information relevant to their work for their “no-code” apps.

Many managers would also have to change their attitudes, according to a Harvard Business Review Services survey, which found that for any company that wants to be more collaborative:

“First, the culture must allow decision-making input from the workforce, with a flatter, more open organizational structure. Second, a collaborative organization must promote interaction among departments, enabled by state-of-the art communication and document sharing and remote access to information and each other.”

There would also be significant attitudinal obstacles. The same survey found that the biggest obstacle to collaboration was lack of management support, and that real management participation was ranked higher than simple management support for collaboration.

It may well be that there are insuperable obstacles to the Circular Company vision that make such a shift impossible, such as how to protect corporate secrets or how to enforce accountability. Or maybe, despite their problems and shortcomings, hierarchy and linear processes are good enough.

On the other hand, hierarchy and linear processes were necessary coping mechanisms to deal with the “Collective Blindness” that afflicted us all in the past, but the IoT removes that obstacle. If nature is cyclical and the earliest forms of human organization (think of gathering around the campfire) were cyclical, wouldn’t the Circular Company be more natural?

W. David Stephenson, principal of Stephenson Strategies (Millis, Massachusetts), is an IoT consultant and thought leader. His The Future Is Smart (HarperCollins Leadership), is one of the first books on IoT strategy.

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