In today’s connected world, companies are looking for ways to do less with more. They’re looking to slash operating costs, enhance service, boost flexibility in the supply chain, improve forecast accuracy, reduce supply-chain disruptions, increase visibility, and reduce inventory, among other goals. The IoT (Internet of Things) is helping businesses acquire actionable information that can lead to a more customer-centric supply chain based on a more proactive business model.

In the past, supply chain operations got by using disconnected planning tools and summarizing historical trends, but information management and analytics in an age characterized in part by the Amazon Effect must be better than they were in the past. Without a digital supply chain that can provide decision-enhancing insights, companies face the possibility that they will become obsolete.

A new study from Logility, a provider of collaborative supply chain optimization and advanced retail planning solutions, and Peerless Research Group, offers critical insight into how supply chain executives currently view the opportunities and challenges associated with the use of advanced analytics across supply chains. Executives demonstrated high interest in using software to understand customer demand and improve customer service, and respondents listed meeting customer demands and maintaining customer loyalty as top challenges their organizations will face during the next couple of years.

Advanced analytics powered by AI (artificial intelligence) can help executives leverage the huge amount of data available throughout supply chain operations to make the best decisions possible. Analytics solutions are growing in popularity, as more supply chain executives look to technology to meet the needs of their customers and achieve goals such as logistics management and supply chain planning and forecasting.

Logility’s survey says 22% of respondents have already implemented analytics solutions, while 27% are currently evaluating or expecting to adopt analytics within a year and 33% are beginning a needs assessment. Less than a quarter of respondents (18%) have no plans to leverage supply chain analytics.

Hurdles for supply chain executives looking to adopt advanced analytics capabilities include concerns about data integration (53%) and a continued reliance on Excel spreadsheets for analysis (47%). Data quality issues, cost of adoption, a lack of skilled staff to help the business leverage analytics, and legacy systems that can’t support advanced analytics also hold supply chain executives back, according to the study.

As companies look to handle dynamic customer demand and keep up with fulfillment strategies in an world, they must consider how they will transform their supply chains. AI and machine learning can provide decision-enhancing insights that can steer executives toward decisions that will reduce operational costs, help them understand and capitalize on trends in customer demand, and provide top-notch customer service. While these benefits may be considered priceless, the reality is that legacy systems and capability gaps exist, and it takes capital to overcome these hurdles. However, a digital supply chain is the only way forward in a digital age.

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