Production innovation: the digitalization obstacles hurting innovation outcomes

• The “innovation orchestration gap” is creating a disconnect between ambitions and outcomes in production environments everywhere

• The causes and costs of the gap are numerous – from fragmented data and the manual wrangling required to create value from it, to insufficient multidisciplinary and cross-departmental collaboration, to legacy complexity dividing IT and OT.

• Closing the innovation orchestration gap is a company-wide challenge that requires partnership between production teams and stakeholders from business units across the whole organization.

First, companies need to constantly validate their innovation focus in context with a fast and unforgiving competitive landscape. Second, industrial players lack the organizational structures to translate their talent for incremental innovation into more radical digitization programs, and so experience a persistent disconnect between their innovation intentions and actual outcomes.This gap between intention and execution—the challenge of transforming ideas and innovation spend into processes, solutions, or capabilities—is called the Innovation Orchestration Gap (IOG).

This blog explores the root causes of the IOG, the challenges it poses to production innovation, and some steps production leaders can take to close the Innovation Orchestration Gap.

Production innovation on the road of digitalization

Your production processes are the single biggest dictator of the business outcomes you achieve. Whether production output, availability of machinery, product quality, inventories, delivery reliability, cost efficiency or waste reduction - your processes create your reality.

The trouble is that most production environments aren’t explicitly greenfield—i.e. purpose-built for the outcomes they’re measured by today. Instead, they’ve evolved piecemeal over time—meaning that your critical business objectives are served by a fragmented patchwork of systems and processes. 

The evolutionary nature of most production environments is a huge driver of the innovation orchestration gap. In this section, we’re going to explore some of the major ways in which that fragmentation obstructs production innovation.

Disconnected process and analytics knowledge

One of the core disconnects in many production environments is between data skills and process expertise. There’s frequently a divide between a connected data platform (and the experts that use it to analyze issues) and the process and subject-matter experts that could act on those insights.           

Part of this problem stems from the inherent fragmentation (of machines, systems and data) within production environments, without a single source of truth to work from (i.e. a holistic data foundation). 

You can’t improve what you can’t see. Process and analytics experts need to form outcome-focused partnerships to identify and solve problems iteratively, together.

Multidisciplinary challenges

The most effective digital solutions within production always involve more than one process, system or organizational unit. That means that effective innovation depends on multidisciplinary and cross-departmental collaboration. 

Domain experts from production practices (like lean production, machinery, assembly, maintenance, quality assurance and logistics) need to partner with new data specialists (in fields like Industrial Internet of Things, edge and cloud architecture, data-science, data-analytics, machine learning, artificial intelligence and more). 

It’s incredibly challenging to mediate collaboration between that breadth of domain specialists. You need a partner with enough insight into each discipline in order to maintain oversight over your objectives and sustain momentum towards them.

The brownfield problem

Most production environments contain massive legacy complexity that makes big-bang digitization impossible. Modern assets co-exist with machines from as far back as the 1970s—often with outdated control units, or from vendors that don’t exist anymore, or customized by people that have since left the business.

Targeted digitization is the only way forward. Before you attempt to retire, refresh or standardize your production infrastructure, you need to build a step-by-step understanding of what every asset does and what you can do with the data it provides.

The IT/OT divide

Digital production solutions need a streamlined flow of data between the source assets (typically managed by operation technology (OT) teams) and the surrounding technology infrastructure (     usually managed by information technology (IT) teams.

So who is ultimately responsible to run digital solutions in the long term? Production innovation needs to be a joint enterprise between IT and OT specialists. Both sides need to embrace each other’s discipline—IT needs to learn about machinery and production requirements, and OT needs to think in terms of cloud-centric, anywhere-to-anywhere networks. The organizational boundaries will continue to blur until they dissolve.

Closing the gap creates value: possibilities for a connected production

There’s no template to close the innovation orchestration gap in production innovation. But there are some key initiatives on the road of digitalization that can help industrial companies attack the root causes of many of the above pain points. So, let's take a look at three opportunities to close the innovation orchestration gap in production:

Build your data foundation for production innovation

Industrial companies already have no lack of data—production environments can produce terabytes of data every day. The challenge is to unify and extract value from it. Digitization is critical to building a solid data foundation for your production environment: an industrial data platform. This way, you can automate and standardize your information flows to make them transparent, responsive and lightning fast.

Effective innovations and large-scale digitalization within production

Overall Equipment Effectiveness (OEE) is the most common key indicator for measuring production environments. It reflects three crucial aspects: availability, performance and quality. 

It’s hard to achieve further improvement with physical automation alone—a data-driven approach makes further potential visible, transparent and exploitable. Digitization is essential to overcome the divisions between departments that each have their own expertise, systems, and working approaches. As long as everyone is working in their separate silos, information flows will always be laggy, imprecise, and slow. 

Transforming your IT/OT architecture

We often still see the classic automation pyramid in production environments. On the IT side, there are large monolithic applications like ERP (Enterprise Resource Planning), PLM (Product Lifecycle Management) and MES (Manufacturing Execution System). On the OT side, there are often minor connected field and control levels represented by SCADA-Systems, PLC's, sensors and actuators, with an overall poor upstream and downstream communication and proprietary protocols.

While this architecture contains a lot of valuable insights as a whole, data is locked into different systems and hard to extract and re-use in other contexts. As a result, there is no overarching sense of what needs to change, making it difficult for innovation to gain momentum. 

To build a common IT/OT architecture, you need to envision a re-defined enterprise software architecture and a true "End2End" solution. To be effective, your solution will need to span multiple organizational units and systems. The ideal is a common architecture that spans and unifies both OT and IT, with a common data platform—based on an edge/cloud hybrid model—on your way to a data-driven manufacturing.

Companies are facing big challenges on the road of production digitalization. With a robust data foundation, OEE maturity, and a transformed technology architecture, your production environment can support sophisticated capabilities that create value across your whole business.