Supply Chain Collaboration Continuum

Not getting data to the appropriate decision makers renders the information nominally useless. Not giving it to the right people, or right group of people, via the right mechanism also means that data loses value.

The truth is that moving information between humans is much more difficult to do in some cases than it is to calculate reports and analytics that need to be disseminated.  This is because collaboration between humans is a behavioral issue, and no amount of technology thrown at the problem can make people silos disappear.

With that said, it’s important to understand where data, analytics and business intelligence can be used.  The following offers a model to classify the different aspects of collaboration

Individual
Human decision making in large part relies on intuition and gut-feel.  Data simply validates their gut-feeling and the decisions they make that drive the part of the business for which they are responsible. As companies become metrics or data driven, more reliance is placed on the data, and individual access to data is even more important.  Data used for specific purposes, by individuals for instance the CFO, is usually not formally shared between employees except to point out or highlight particular data items.

Ad-Hoc Team/Group
Many decisions are made by ad-hoc teams and empowering them with the ability to query and retrieve data whenever they need it results in meaningful information, helping companies leverage their investment in data and improve their business performance. Supply chain data or intelligence is pulled from the BI system and presented to the team on an as-needed basis with or without the assistance of IT for analysis.

Scheduled E-Mails
The next level of maturity on the collaboration continuum is the availability of a system to push critical business information to the appropriate parties on a scheduled basis.  Relevant data regarding supply chain effectiveness, disruptions, open orders and inventory levels are pushed to key stakeholders inboxes on a pre-set schedule. Companies need a reasonably high level of maturity in regards to their data analytics in order to know what information is critical to push.

Alerts
More mature is the ability of a company to alert key decision makers when some aspect of the businesses is not meeting predefined levels. Regardless of the time or their location decision-makers are automatically notified of changes in key metrics, allowing timely decisions on important aspects of the business such as falling inventory levels.

Integrated Collaboration
The highest level of maturity is reached when people can come together and collaborate on solving business problems. When these problems occur, systems allow the right individuals to have input into helping to solve the solution. Individuals inside and throughout the organization’s supply chain are able to access data, share views, ask questions, and track progress within the business intelligence platform.

How mature is your Supply Chain Data?
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About the Author
Ray Major is the Chief Strategist of Halo Business Intelligence. A data scientist, economist and statistician by training, he’s a life-long practitioner in the mysterious arts of data intelligence and analytics.

You can contact Ray by email at [email protected] and also follow him on Twitter at @majorbi

Related: Understanding the Supply Chain Data Continuum