Supply Chain Management : Exploring the 4v’s of Big Data
U.S. retailers have lost billions due to excess inventory.
Companies have traditionally relied on sales forecasts to anticipate what they’d make and ship to their customers. In an increasingly competitive and rapidly changing marketplace, historic sales figures are far less reliable, and the value of such data is far less valuable.
Modern technological platforms such as middleware and SaaS products allow companies to use real-time data. Point-of-sale devices scan the product barcode into files for upload, and information from the past week or past day is available for statistical analysis. This enables companies to quickly respond to what’s happening in real time as opposed to when it may be too late.
How data powers product and creative is shipped overnight.medium.com
Small businesses with such systems can integrate ordering to better manage inventory and save money. Sales forecasts provide an element of risk, compounded by expenditure in boosting stock levels. Connected companies can automatically re-order inventory as it’s sold, in any increments or timeframes they see fit.
Big data is often used when describing large volumes of data, however, the technological support function is actually about handling and processing large clusters of data…in real time.
Small businesses can tap into the capabilities of Big Data analytics and gain a competitive advantage in the market with only a small initial investment.
In many ways, the analyzation of big data is geared towards small businesses because they are often more agile and can pivot quickly on the data-driven insights surfaced by these analytics.
With increasing pressure to reduce costs, especially with competition from countries with lower-cost production, supply chain management has increasingly meant using big data analytics to drive competitive advantages in the market.
Technology is helping transform global supply chains in areas such as demand sensing/forecasting, spend analytics, inventory optimization, transportation route optimization, and production scheduling.
Regardless of your business’ prime focus, supply chain data within an enterprise has to have all four dimensions. This is what i refer to as the 4Vs of Big Data — Volume, Velocity, Variety & Value.
From drop-shipping Shopify e-stores to brick and mortar businesses looking to expand their footprint via Amazon Fulfillment Services, it’s crucial to understand the process in which your business is operating to improve efficiency and eliminate hiccups ultimately improving the customer’s value-chain.
Some organizations look to Amazon FBA Services to offset the headache of shipping patters and package accountability. How does this work? When a sale is made, Amazon picks it, packs it, and ships it to your customer. Quick shipping makes for happy customers, and happy customers make for more sales for you. This may seem like a seamless process, however, Amazon does require you supply items in a timely fashion as well as having the items pre-packaged. Understanding the 4V’s pf big data and lend your organization an upper hand even when a third party fulfillment system is in place.
Small businesses can tap into the capabilities of blockchain and Big Data analytics to gain a competitive advantage in the market with only a small initial investment. With in-house or outsourced technology expertise, small businesses can start the journey towards cost-effective operations. Supply chain management can be much more agile and managers can act quickly on data-driven insights, as Big Data optimizes and transforms supply chain processes within a business. More and more organizations are investing in Big Data, using data to help leadership make smarter, more accurate decisions.
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