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Return to: 2014 Feature Stories

CLIENT: HALO BUSINESS INTELLIGENCE

Oct. 27, 2014: Computing Now

Understanding the Supply Chain Collaboration Continuum

Collaboration of information and timing and are two extremely critical aspects of supply chain business intelligence and information management. 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 Collaboration?

Use the Halo Business Intelligence Maturity Model™ to develop a roadmap that increases the overall effectiveness of your company's BI implementation and beat the competition through superior insight into your business.

» Take the Assessment Now!

About Ray Major

Ray Major is Chief Strategist of Halo Business Intelligence. The company, with offices in San Diego, Atlanta and Auckland New Zealand offers a suite of business intelligence and predictive analytic solutions. Halo BI specializes in supply chain analytics and S&OP in the food and beverage, manufacturing, and retail verticals worldwide. Ray is a frequent lecture and blogger on successful BI implementations through the alignment of People, Process, Technology and Data. His passion is helping companies get the most out of their BI and analytic systems by becoming data driven.

Return to: 2014 Feature Stories