Supply chain analytics is transforming your business

Supply chain analytics

Every day, every hour, and every minute, countless packages and shipments are being moved around the world within never-ending flows of supply chains. These supply chains serve as the backbone of the world economy and, in truth, are what keeps the world moving. But consider for a moment the amount of data, information, and decisions that are required to make a supply chain not only operate but do so effectively. While the end goal is to get packages from A to B as quickly and efficiently as possible, there’s a lot more going on behind the scenes that make it all work. Supply chain analytics is at the forefront of breaking down this data into meaningful insights for organisations.

More than ever before, organisations are faced with streams of data flooding in from various channels at an accelerating rate. Being overwhelmed by data can hamper an organisation’s ability to keep up with data inflows and derive valuable insights. This problem can be exacerbated by interactions between internal and external parties up and down the supply chain, which, in turn, affects business operations.

Advantages derived from the analysis of this data can increase supply chain agility and cost optimisation among a few other things. While supply chain analytics is a relatively new approach, it is being embraced by supply chains globally. Read on to understand how supply chain analytics can transform and supercharge your business.

Plan and forecast better by using supply chain analytics

Supply chain decision-makers are seeking ways to effectively manage big data sources. Big data solutions that support integrated business planning are currently helping organisations orchestrate more responsive supply chains as they better understand market trends and customer preferences.

The ability to effectively forecast demand is essential for supply chain management decisions. In fact, demand forecasts are used throughout the supply chain including supply chain design, purchasing, operations, inventory, sales, and marketing. In large part due to computer processing power, new advances in forecasting and the abundance of new data sources have helped increase forecast reliability.

Value-added forecasting is one-way companies are now realising incremental improvements in their forecast quality and reliability. Additionally, applications of big data at a global level are enabling supply chains to adopt a proactive rather than a reactive response to supply chain risks.

Streamline inventory management

Supply chain leaders are on a quest for more precise estimation capabilities – a trend exacerbated by expert supply chain analytics. Value-added forecasting brings corporate data and expertise to the table, with 4 – 27% reductions in forecast error. These superior forecasts help determine proper inventory controls to minimise overstock and out-of-stock events.

Take IKEA for example. The Swedish giant employed extensive analytics tools to analyse every purchase and every click. This enabled IKEA to not only propose customer preferences for certain products but also manage inventories at their various distribution centres by tracking sales of different types of products and how they impact inventories at the various distribution centres.

Advanced supply chain analytics software was employed to facilitate and guide IKEA to handle their inventory, which spans across 298 stores in 37 countries. So, how in the world does IKEA offer so much at such a low price while always being able to keep items in stock? Superior supply chain analytics software is the answer.

Leveraging demand sensing and shaping to transform your business

Demand sensing bridges the gap between long-term demand planning and short-term forecasting, and order execution that drives much of the supply chain. Supply chain analytics in conjunction with demand sensing and shaping is the key to market-driven forecasting and rapid, efficient inventory replenishment.

Demand sensing and shaping is a capability and technology used to improve near-future forecasts using detailed short-term demand data gleaned from the expert supply chain analytical insights. Demand sensing reduces forecast error by up to 50%, increases inventory accuracy by up to 20%, and optimises the efficiency of your business.

It is worth noting that this serves as an integral part of a company’s strategic process. The Journal of Business Forecasting notes that demand sensing sorts out the data taken from expert supply chain analytical software in a structured manner that recognises complex patterns and separates actionable demand signals from a sea of “noise”.

Key Takeaways

SAS supply chain analytics helps companies harness the power of data sources to make supply chains become more responsive, demand-driven, and customer-centric. Together with their global partners like Selerity, SAS software has been dedicated to delivering unprecedented insights in a way we’ve never seen before. For more information on how you can revolutionise your business by utilising supply chain analytics software, please feel free to peruse our services.

Ari Vivekanandarajah

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