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From stock management to obsolescence: how big data helps us make better decisions

09 June 2021
Article by Joana Moreira, consultant in Industrial Engineering and Management at INEGI.

Ask yourself: are you taking advantage of all the information you have for the benefit of your company?

The easy collection and interpretation of large volumes of data is transforming the world, and the way companies manage their business. In today's competitive ecosystem, the rapid response of companies and organizations to customer wishes and competitive actions is essential, and we must ensure that all the tools at our disposal are used to achieve success. Including data analysis tools, or big data.

The production and sale of products and services systematically generates data, and its analysis makes it possible to identify patterns, trends and anomalies. Adopting a data collection and analysis strategy has numerous advantages – it allows optimizing processes and analyzing the value chain in detail, and facilitates decision-making and operations management, namely inventory management and the consequent reduction in obsolescence.

The product offer is, nowadays, immensely diversified. As a result, customers are less and less willing to tolerate stockouts, and favor convenience and speed over loyalty. The fact that there is no particular item to meet the demand is, at best, one less item being sold by that organization. But, at worst, it can damage the brand and contribute to the loss of future customers.

Data analysis and consequent decisions involve three dimensions, and the effort, but also the gains, can be greater or lesser. Let's see:
  • Descriptive analysis: analysis of past results (reports and historical data)
  • Predictive analytics: using data to predict future situations
  • Prescriptive analysis: generating recommendations based on historical data and using the two previous analysis tools (descriptive and predictive)
It is no coincidence that industry 4.0 relies on the reliability of data and its analysis. In competitive environments, lack of information easily becomes a fatal disadvantage.

The collection and study of data makes it possible to know and monitor the results of the operation. Going further, using capable algorithms developed for this purpose, the analysis allows us to predict possible futures, and even optimize the business by suggesting a focus and alignment within the organization.

In a reality, where data flows naturally, consumers are increasingly demanding and the pace of change is unstoppable. Data-based decision making is a key to success and therefore knowledge in this area will certainly be a shared competence. It is anticipated that, sooner or later, analytics solutions will no longer be limited to one department and will expand to all departments in an organization because of their importance.

Big data supports decision making in stock management

One of the departments that has much to gain from investing in data analysis is logistics and stock management. Being competitive means having efficient and accurate inventory management, supported by real data and good analytics that reflect available stock levels in real time.

It is common to choose to have a low level of stock in order to invest little capital in inventory. The costs associated with stock, often difficult to quantify and compared to an iceberg, are high and need a lot of attention. However, on the other hand, the amount of stock intersects with a reduction in the risk of stockouts, which can compromise the level of customer service and customer satisfaction.

Choosing an inventory management method is, of course, a difficult decision, but it can become a lot simpler when supported by reliable information. By obtaining information about the main market trends, knowing your customers and needs better, it is easier to manage your stock, and increase profitability.

Also, product obsolescence and deterioration is an unavoidable problem in inventory management and one that many organizations mistakenly address reactively. Good management of stock data allows you to proactively manage obsolescence, supporting the creation of an obsolescence risk assessment process, and supporting managers' decision-making to mark items that are most at risk of becoming obsolete.

In short, it is clear why Big Data is gaining ground in management and decision-making processes. The ability to collect and analyze data is growing, and it's imperative that companies equip themselves with the right tools to thrive.

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