Although data and workflow systems of today are becoming more digitalised, complete confidence in the numbers reflected in inventory management systems is still lacking as data fragmentation remains an issue for most organisations. Information systems are often working in silos, outside and inside the business, even though operational functions and supply chain organisations are increasingly becoming more co-dependent.

As the challenges faced during the pandemic continue to endure, more accessible, affordable, and adaptable solutions have developed. The pandemic has demonstrated what the industry is capable of when it considers the symbiotic role of hardware, software, and people in inventory management.

The next step for data: Automating data capture to data analysis

As pointed out by my colleague Suresh Menon, Senior Vice President and General Manager of Software Solutions, while the barcode had been around for decades, it only became a game changer recently as e-commerce sales are expected to top $1 trillion for the first time. The ease of click-to-buy models complicated inventory management and fulfillment workflows. The supply chain was no longer linear and so the business case for barcode-based track and trace solutions grew quickly, with more developments in QR code scanning and further expanding inventory monitoring capabilities being made.

With a single scan, multiple data fields could be automatically and accurately funnelled into back-end systems, compiled into functional data sets, then distributed for further analysis by inventory and operations managers, buyers, and planners. Workers could report the status of every item they handled in real time, as well as inventory sitting on the shelf or stockpiled at the receiving dock. The labour and operational costs of inventory management dropped, even as technology spend grew.

As radio frequency identification (RFID) technology matured, it proved that data capture and track and trace could be further automated. Thousands of tags could be read each second by fixed readers placed throughout facilities or handheld readers operated by workers, and data could be fed in bulk into inventory management systems with increased accuracy.

This influx of data was a surprising workforce multiplier. As demand for skilled data scientists increased, so did the realisation that businesses must automate analytics if they want to be able to sense, analyse, and act on both supply and demand trends in real time.

Putting a value on inventory data and actions

Real-time inventory status is key to making the right labour, procurement, merchandising, pricing, and promotion decisions. However, that data needs to be analysed to be understood and actioned in order to be valuable to the business. That is where software and independent software vendors (ISVs) come in.

The industry has seen a leap in inventory management capabilities ever since cloud-based software-as-a-service (SaaS) platforms became available at scale. Structured and unstructured data generated by Internet of Things (IoT) components can now flow freely through a data pipeline or directly to a data lake. As a result, application programming interfaces (API) and machine learning algorithms can be used more frequently to access and mine data in the context of a specific operation or function in a low-cost manner.

Anyone can use APIs to connect to the same information systems and extract the actionable insights most pertinent to their roles, from loss prevention specialists to procurement planners.

Similarly, a platform for intelligent demand sensing can combine inventory data from several business systems and analyse it alongside contextual third-party data such as weather, traffic, holidays, and other demand-influencing events. It can then specify certain activities for merchandising, pricing, or promotion to balance supply and demand.

Opening ecosystems brings new solutions

This software-led transition from “systems of record” to “systems of intelligence” and, ultimately, “systems of engagement” has been crucial to gradually increasing inventory availability and performance over the last decade. SaaS solutions have even partially automated decision-making, eliminating some manual labour and risk from the inventory planning and management process.

However, businesses must do more to ensure all stakeholders have full transparency into inventory status from the stockroom to the store floor by removing solution development silos. Businesses must ensure that solutions are actively communicating, analysing, and taking intelligent action on data so that all supply chain participants can accurately forecast, sense, and shape the demand for inventories to better prepare themselves for the next batch of challenges the industry will undoubtedly face in the future.

Brett Newstead is director of sales for Zebra Technologies Australia.