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Big Data Analytics

Analytics, Business Intelligence, Posts, Supply Chain, Warehouse Management

Big data is all around us.  As we have seen, big data is characterized by its volume, velocity, and variety (the infamous three ‘V’s).  Great, you have a lot of data…now what?  Well, these untapped ‘dark data assets’ give rise to vast opportunities for those organizations that seek new ways to compete.  Studies have shown that organizations that compete on analytics by focusing on their core competencies fare much better than those who do not.  Some have gone so far as to call big data the ‘new oil’.  In part two of this four part series, we will take a closer look at big data analytics.

Big data provides organizations with deeper and broader data sets that when combined together with traditional transactional data, and on which the proper analytical techniques are applied, can produce a holistic view of the organization’s current and future performance, across a wide spectrum of business functions.

Take for example an organization (let’s call them ABC Supply) that has chosen to focus its analytics on its core competency, which happens to be customer loyalty and satisfaction.  They have established this strategic differentiator by making sure that they always have the right product at the right time (i.e. they focus on their supply chain).  A good forecasting model is fantastic, but what if you wanted a crisper level of foresight?  What if you could tell how much product you are going to sell in a region and know which customers were likely to buy the product.  This is what big data analytics can offer.

ABC Supply pushes the envelope by looking at the predictability of demand.  Big data is an asset that provides ABC Supply with rich and invaluable insight into their customers’ buying behaviors (e.g. what are they buying, how much do they spend), preferences (e.g. what types of products do they buy), social interactions (e.g. how are they influenced by their contacts in social media), and sentiment regarding your organization (e.g. what are they saying about the company on social media).  ABC Supply applies analytical methods on big data to predict what other products consumers will likely buy, and ensures their inventories are adjusted accordingly.  They track social media and customer support, in real-time, to understand emerging trends, or identify an issue that is brewing with one of their products.  They run regular, well designed, customer surveys to constantly monitor overall sentiment, and cross reference the sentiment with business performance to identify correlations.  They integrate 3rd party benchmark data to bolster their perspective even further.  Lastly, they share this information with their vendors and engage in collaborative partnerships.

As ABC Supply sees the enormous value in analytics, they apply it to other aspects of their business.  They begin to predict the risk of customers defaulting on their payments, the risk of vendors failing to deliver products on time, and how these risks could ultimately affect ABC Supply’s bottom line.

What is important is that limiting your focus to what occurs between the four walls of your warehouse is just not going to cut it in this new competitive landscape.  You need to be an analytical innovator and competitor.  Take Amazon for example;  their core competency has always been based on having a world leading supply chain.  Their advanced analytics has led them to actually ship product to DCs before they are even ordered, purely based on the likelihood that customers will order those products.

This is the promise of big data, and the potential payoff is huge.  In my next post, we will look at the implications of big data, namely cultural, technological, and ethical.

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