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5 Ways to Use Advanced Analytics to Make Better Purchasing Decisions

Here’s how electronics buyers can streamline the supply chain by integrating advanced analytics into their daily routines.

In a business world where “going with your gut” and “flying by the seat of your pants” have both given way to decisions that are based on data, metrics, key performance indicators (KPIs), and benchmarks, a growing number of procurement teams are turning to advanced analytics to make better purchasing decisions.

“As we tap into both structured and unstructured data sources, advanced analytics help us draw conclusions about demand, inventory, production, and distribution operations to quickly drive more informed business decisions,” Henry Canitz writes in SupplyChain247. “An important goal of a supply chain analytics initiative is to enable better business decisions that improve operating results and allow you to be more responsive to customer needs.”

5 Ways to Get Started

Defined by Gartner as “the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations,” advanced analytics incorporate processes like data/text mining, machine learning, pattern matching, forecasting, and visualization.

Here are five ways advanced analytics are helping electronics buyers work smarter, better, and faster this year:  

1. More effectively forecast customer demand. The process of predicting consumer demand for a product or service, customer demand forecasting entails buyers using historical data to identify seasonal fluctuations in demand, consumer trends, and even weather-data purchase correlations. “By properly forecasting market demand,” Orlando Trott writes in Advanced Analytics Within the Supply Chain: Demand Forecasting Process + Inventory, “management can eliminate holding costs, lower operational expenses, and improve efficiencies during peak periods.” This, in turn, helps buyers fine-tune their inventory requirements so as to avoid both stock-outs and excess.

“Data analysis can be used to pinpoint changing customer requirements and predict changes in supply and demand for electronic component purchasing,” Tony Powell writes in 5 Ways Data Analytics Improve the Electronic Component Supply Chain. “It can also be used to improve customer service and loyalty programs, to make planning and logistics more efficient, and to eliminate waste, error, and duplicated effort throughout an organization.”

2. Identify trends before they happen. Using an advanced analytics strategy, buyers can more accurately identify trends, understand their customers’ purchase habits, predict purchase behavior, and drive strategic decision-making. “Big data and predictive analytics can help suppliers plan their businesses beyond the next order horizon, and extend this planning all the way out to 12-18 months,” JDA’s Danny Halim points out in How can enhanced data and analytics optimise your supply chain?

“They can do this without taking too many risks by providing insight into the downstream customer demand and buying behavior,” Halim continues. “Providing better visibility helps customers run their businesses better and suppliers to grow their businesses.”

3. Reduce total landed costs. Optimizing production and sourcing to reduce total landed costs (56%) is the most important use case of advanced supply chain analytics in the next two to three years, according to a new report from The Hackett Group. Defined as the total price of a product or shipment once it has arrived at a buyer's doorstep, total landed cost includes the original price of the product, transportation fees (both inland and ocean), customs, duties, taxes, tariffs, insurance, currency conversion, crating, handling, and payment fees.

By automating landed cost calculations, procurement can improve the organizational bottom line while also enhancing customer retention (due to more accurate pricing and less “over-estimating”).

4. Create a more transparent, efficient end-to-end supply chain. A supply chain that’s supported by integrated data analytics tools is more transparent, with duplicated efforts and manual processes both replaced by automation. “The electronic component supply chain as a whole becomes more efficient and, as visibility is increased all along the process, opportunities for improvements are more easily spotted,” Powell writes, “and the focus can turn to implementing better business strategies. Increased efficiency, along with cost reduction, has a direct effect on the bottom line of the company.”

5. Take the guesswork out of root cause analysis. To figure out what causes, for example, higher reports of damaged items among custom-ordered products, procurement can leverage analytics to determine that improper packing and shipping of fragile materials was not the problem. “Instead, the company may find that sales and return data point towards incorrect orders,” Financial Management magazine points out. “To resolve the issue, the company can then retrain its sales team.”

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