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End2End Innovation | Engagement & Collaboration | Tech Management

Everything in One Place: Data Governance Best Practices for R&D

In the world of innovation, Kodak serves as a stark reminder of what can happen when a company’s departments operate in silos, and R&D intelligence is disconnected. This blog will take you through pitfalls and best practices for R&D data governance, illustrating the importance of interdepartmental collaboration and synergy.

How information silos stifled innovation at Kodak

What can go wrong when your R&D department isn’t interconnected with the rest of the company? Kodak is such a cautionary tale. From the 1940s to the 1980s, the American photography company was a market leader. But when digital cameras became widely available in the 90s, Kodak resisted the new technology and began losing market share. The 119-year-old company filed for bankruptcy in January 2012.

The decline of Kodak demonstrates the importance of aligning different departments on innovation and providing decision-makers with a holistic view.

Here’s a surprising fact: a young engineer, Steven Sasson, created the first hand-held digital camera prototype at Kodak in 1975. “Hardly anybody knew I was working on this because it wasn’t that big of a project,” Steven says. He demonstrated the prototype to Kodak business executives, but the response was lukewarm. They were convinced no consumer would ever want to look at their photos on a screen.  

Then, in 1989, working in the Kodak research lab, Steven developed the first digital SLR 1.2 megapixel camera. But Kodak’s marketing department still wasn’t interested in it, saying the digital camera posed a threat to the company’s film-based business model. Management did not appreciate what its R&D lab had developed.

Kodak lacked a holistic view of its R&D efforts and innovation opportunities. Their siloed structure, with information compartmentalized into different divisions of the company, also stifled cooperation.

By the time Kodak realized it needed to make a strategic shift towards digital, it was too late. More agile competitors, less encumbered by internal barriers to information flow, had taken the lead. In a last-ditch effort to catch up in the 90s, the company sunk more than 5 billion into digital investments—resulting in a meager return of $20 million in annual digital earnings; it was the death knell for Kodak after having failed to form a connection between clear external signals, internal R&D projects, and strategic goals.

Establish a single source of truth for your R&D intelligence

With the benefit of hindsight, it’s clear that Kodak lacked the ability to see the potential of what its R&D department was working on. They did not recognize the existential threat of digital photography or leverage internal research to stay ahead of competitors. It’s not enough to invest in R&D and invent something; you need to couple it with market demand and a willingness to pay.

A single source of truth bridges these two perspectives: technology push and market demand. It consolidates R&D intelligence to ease connections between engineering, marketing, and product development.

Let’s explore an example of best practice from our client in the manufacturing aerospace industry. They implemented our Innovation OS because they wanted to capitalize on their assets and ensure strategic alignment of products, technologies, and engineering components.

Single source of truth for R&D data governance: How Product, Engineering, and Research Units respond to market pull and technology push

This diagram shows how having a single source of truth makes it easier for different business units (Product, Engineering, and Research) to collaborate in response to business opportunities and emerging technologies. The three business units work in a bi-directional approach that supports market pull or technology push. In its simplest form, there are two flows to developing a new product:

A. The Product Unit communicates a business opportunity to the organization. If the Engineering Unit has a solution, it can be packaged as a product and go to market. If Engineering does not have a solution, then the Research Unit conducts research to enable Engineering to develop components that satisfy the business opportunity.

B. The Research Unit takes on Research Challenges, resulting in new technologies as the output. This is handed over to the Engineering Unit and, subsequently, to the Product Unit.  

Establishing a shared system like this helps various roles do crucial tasks. A Product Lifecycle Manager can then easily see what components and technologies support products in their portfolio. Engineers can update component information and view the roadmap milestones. Technical Directors can align the portfolio with their investment capability.

Our client uses the ITONICS platform to organize their R&D data, facilitate decision-making, and maximize the value of their investments. This consolidated overview of all activities across business units makes it easier to make connections and collaborate.

The benefit of data quality and consistency

Whatever software you use, it’s important that you have one place to consolidate R&D information in a format that gives colleagues at all levels a clear overview. The ITONICS approach is to standardize pieces of information called ‘elements’ in the software.

Information templates for consistency

Standardizing the entry fields on every project, technology, or business opportunity allows you to quickly and easily make comparisons. This consistency ensures that there won’t be missing information when management needs to make important decisions about the entire portfolio. The ITONICS Innovation OS provides a variety of best-practice templates that you can also customize to suit your unique use case.

Establish an R&D data taxonomy

Disagreements might occur in your team about the exact criteria for what constitutes a technology versus an engineering component, or the difference between an idea, opportunity, and inspiration. So, it’s worthwhile to agree on the taxonomy of information containers and how they relate to each other. You may, for instance, differentiate between a:

  • Business opportunity,

  • Product program,

  • Product line,

  • Product, and/or
  • Component.

Such a hierarchy is not only relevant when connecting elements to show their causal link, but also when organizing them vertically on an R&D Roadmap.  

R&D roadmap in the ITONICS software

Agree on naming and tagging conventions

Your colleagues should be able to see at a glance what a project is about. Using an agreed naming convention makes information more accessible in large organizations. The title of projects could, for instance, indicate what geographic territory and department it belongs to.

Additionally, tagging information with a consistent set of labels helps others outside your team easily filter and find what they are looking for in the system. On the ITONICS platform, there’s the added benefit of the recommended relations feature that automatically identifies elements with similar content for you. This is especially useful when reassessing a large innovation portfolio to spot redundancies or potential synergies between the work of dispersed teams.

A software solution that’s purpose-built for innovation

Our clients choose ITONICS because they have a common problem: bridging market demand and technological solutions. By implementing a central innovation system, they can dissolve the type of information silos that contributed to Kodak’s downfall. If you want to see how the ITONICS Innovation OS can support R&D data governance and informed decision-making, book a demo today.



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