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Monday, January 16, 2017

Will Microsoft Simplify Collaborative Innovation Management?

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Will Microsoft Simplify Collaborative Innovation Management?

By leveraging LinkedIn in their Enterprise solutions

Jigsaw GroupWhen Microsoft announced last June its intention to acquire LinkedIn, there was speculation in the media about the reasons[1][2]. Many thought the value of this acquisition relied in the size of the “social network” – 400+ million professionals who are members of LinkedIn. Some thought LinkedIn would enable Microsoft to become a bigger player in the CRM market. Now that the acquisition is complete, I am excited to share my thoughts on what it might mean for Collaborative Innovation and network management.

Last March I gave a presentation at CIMdata’s annual PLM Market and Industry Forum. The title of my presentation was “Materials Innovation Ecosystems: Finding, Building, and Managing Your Networks.” In this talk I shared a simple vision for enterprise network management architecture, see Figure 1.

Figure 1
Figure 1. A vision for Enterprise Network Management
(Courtesy of CIMdata)

The key elements of this vision are “rich” profiles for people, organizations, and projects. The profiles are connected across, and mostly automatically populated with people’s critical activities in their workflow through connectivity with their digital tools and apps. When I recently learned more about how LinkedIn engineers their profiles[3], I thought their approach could support realization of this vision. Should this present a new business opportunity for Microsoft in helping their enterprise clients simplify management of their innovation networks? I think so, and here is why.

There is no more debate. In today’s accelerated and connected economy, turning an idea into product innovations that customers’ love requires integrative thinking and multi-disciplinary collaboration, often including industrial design, science and engineering, process engineering, and hardware and software engineering. Given the diversity of expertise and knowledge that must be integrated to create new innovative products and to introduce them successfully to the correct markets, collaborative innovation is a must—no one can do it alone.

Yet enterprises suffer from inefficiencies in collaboration and managing their networks because the data relevant to their collaboration activities are distributed across functional silos. For example, externally submitted ideas are kept in a database by the organization that manages the external innovation portal. R&D manages collaboration with academic institutions and external labs. HR sequesters employee skills and experience related information. Purchasing manages supplier relationships and associated data. The Legal department manages legal agreements. Typically, there is no digital mechanism that links data across these functional silos. Given this reality it is difficult for an enterprise to maintain a holistic corporate memory on what has been done or is being done. Even the simplest questions, such as “Has this idea or solution been shared with us before? What has been decided, and why? Have we worked with this company before? What was done with them? What was our experience like?” are hard to answer. People are the connectivity enablers, and they are, therefore, consumed by a never-ending flood of emails and meetings. In today’s fast moving digital world, this is unacceptable.

Therefore, a key value creation opportunity for digital innovation platforms such as Enterprise Innovation Management (EIM) and Product Lifecycle Management (PLM) is to enable data connectedness across these solutions to increase process efficiencies for users. People’s activities are the source of new knowledge and information that define and realize new innovation. Budgets and other resources support peoples’ activities. Programs and projects are the vehicles for deployment of budget and resources to people to do the work. Therefore, each of these elements—people, organizations, and projects—should have visibility in an EIM / PLM environment. This can be achieved by creating profiles for each of these elements. Preferably these profiles are populated automatically with on-going activities, eliminating the need for manual entry. Some data could come from systems managed by functions such as HR and Legal. This will allow for data integrity, but data exchange and interoperability between the systems should be enabled across an enterprise’s business platform that enables its end-to-end processes and data connectivity.

I imagine that LinkedIn’s approach described in the blog referenced earlier could be reapplied to creating the enterprise knowledge graph to solve the “data silo” problem. Given most enterprise users conduct their daily work activities in Microsoft products, I also imagine that having LinkedIn profiles embedded in Microsoft solutions [and vice versa] would allow users to seamlessly share their collaborative activities. An integrated enterprise knowledge graph (as opposed to separate ones shown in Figure 2) might be the way to achieve the vision I presented in my CIMdata Forum talk. I believe with the LinkedIn acquisition Microsoft has the perfect opportunity to get there sooner.

What do you think?


Figure 2
Figure 2. Depiction of the Microsoft Graph and LinkedIn Graph today
(Ref: Building the LinkedIn Knowledge Graph blog3)


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