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The processes used to gain insight and extract value from the large amounts of data associated with the procurement, processing and distribution of goods, supply chain analytics has become a critical aspect of overall supply chain management. Armed with this “actionable” information, supply chain analytics helps improve forecasting and efficiency and allows companies to be more responsive to customer needs.
According to IBM, supply chain analytics can be broken down into these four categories:
Descriptive analytics. Provides visibility and a single source of truth across the supply chain, for both internal and external systems and data.
Predictive analytics. Helps an organization understand the most likely outcome or future scenario and its business implications. For example, by using predictive analytics, you can project and mitigate disruptions and risks.
Prescriptive analytics. Helps organizations solve problems and collaborate for maximum business value. Helps businesses collaborate with logistic partners to reduce time and effort in mitigating disruptions.
Cognitive analytics. Helps an organization answer complex questions in natural language—in the way a person or team of people might respond to a question. It assists companies to think through a complex problem or issue, such as “How might we improve or optimize X?”
Using some or all of these supply chain analytics, companies can make smarter, quicker and more efficient decisions. IBM says analytics also produces significant returns on investment (ROI), helps identify known risks, predicts future risks (by spotting patterns and trends throughout the supply chain), predicts future demand and runs leaner.
“Advanced analytics can process both structured and unstructured data, to give organizations an edge by making sure alerts arrive on time, so they can make optimal decisions,” IBM adds. “[It] also builds correlation and patterns among different sources to provide alerts that minimize risks at little costs and less sustainability impact.”
Major Market Growth
According to a new report from Allied Market Research, the global supply chain analytics market generated $4.53 billion in 2019, and is expected to garner $16.82 billion by 2027, growing at a compound annual growth rate (CAGR) of 17.9% over the next seven years.
The research firm says that the need to improve operational and supply chain efficiencies; increased adoption of big data technologies; and the need for more efficient transportation and logistics are all driving growth in the global supply chain analytics market.
And while data inaccuracies and a lack of skilled IT staff tend to restrain market growth in this area, Allied Market Research adds that “growth in awareness regarding benefits of supply chain analytics and surge in demand for cloud-based supply chain analytics solutions are anticipated to present new opportunities in the coming years.”
North America contributed to the highest share of the global supply chain analytics market in terms of revenue, holding around two-fifths of the total market share in 2019. Growth in e-commerce, along with rising government funding to support big data projects in the U.S., is driving that market growth, the firm adds. The Asia-Pacific region is estimated to manifest the fastest CAGR of 20.8% from 2020 to 2027, it continues, based on the adoption of advanced analytics across multiple industries and growing use of supply chain analytics to gain a competitive edge.
Key Market Drivers
Few would argue the massive impact that COVID-19 had on the world’s supply chains. Now, the scars left behind by this unprecedented event are pushing more companies to invest in supply chain technology—including platforms that can effectively gather and assess data, and then make intelligent recommendations based on that data. “The COVID-19 outbreak has considerably enhanced the growth of the supply chain analytics market,” the research firm points out.
With companies now planning for the next potential supply chain disruption, the need for good supply chain analytics is expected to grow. A recent MHI Annual Industry survey found that 30% of supply chain managers were using predictive analytics in 2019 (up from 17% in 2017), and that number likely increased this year. MHI says 57% of companies that aren’t using predictive analytics plan to start doing so within the next five years, with many of them banking on the fact that predictive analytics will help transform their supply chains.
