Feature Story

Understanding the Supply Chain Data Continuum

I will be the first to admit that there are lots of different ways to categorize data. And I would like to add, that there is not necessarily one right way to do it. But at the end of the day, understanding the totality of a problem is easier if you find a way to break it down into component parts, categories, or summarize the information. The following is a framework attempt to categorize by maturity (and difficulty) the important aspects of "Data".

Single Source

When companies first set out to leverage their supply chain data to improve or optimize some aspect of their business, they typically start by trying to "ask" questions related to single sources of data, questions like "how much did we sell last quarter?" are common, and require access to data such as the corporate ERP, CRM, HR, POS or disparate Excel files.

Multi-Source

As companies mature in their analytics, questions become more complex like "Do we have enough inventory to cover our orders?" The answers to these questions usually require data to be pulled from more than one data source. Disparate data sources can be accessed through BI systems and combined, which allows for more complex and sophisticated assessments of the business.

Data Cleansing

Once companies can access their data easily through an analytic system, data quality becomes critical. Bad data = Bad decisions, so Data quality tools and processes are integral to maturing the Supply Chain BI platform. Data quality tools help companies avoid the problems associated with making decisions based on incorrect or incomplete information.

Real-Time

Becoming ever more critical in supply chain information management is the need to incorporate real-time data. Real-time data is more complicated to manage and analyze, but the benefits of doing it right are great. Intelligence in real time systems is updated on a frequent basis, either every few minutes or even continuously as new data becomes available. This allows supply chain managers to respond better to situations as they arise. Customer satisfaction, production efficiency and sales can all be improved.

Big Data

The holy grail of data the data continuum and the most complex to manage and utilize is "Big Data". Big Data refers to unstructured data from external sources such as machine sensors, weather, and social media feeds that are incorporated into the Supply Chain BI system. Used properly, Big Data improves insight into the larger business eco-system.

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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.

Prior to Halo Business Intelligence, Ray was a senior vice president at The Nielsen Company where he oversaw the integration of Claritas, a data collection and predictive analytics firm, into the global Nielsen brand. He headed up B-to-B software development efforts for Equifax National Decision Systems, and also served as a research analyst and statistician, and data jockey for the San Diego Association of Governments (SANDAG). Ray holds both bachelor's and master's degrees in economics from San Diego State University. You can contact Ray by email at majorbi@halobi.com and also follow him on Twitter at @majorbi

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