Supply Chain Analytics Market

Supply Chain Analytics Market Size, Share, Industry Growth, Latest Trends

The global Supply Chain Analytics Market size was reasonably estimated to be approximately $5.2 billion in 2022 and is poised to generate revenue over $13.5 billion by the end of 2027, projecting a CAGR of around 21.0% from 2022 to 2027.

SME initiatives in the area are focused on cloud services, which would speed up artificial intelligence and business analytics. Cloud will play a crucial role in enabling new platforms, services, and facilities that governments and businesses want to enable as digitalization occurs throughout the area. The market is segmented based on components, applications, deployment modes, organization sizes, verticals, and regions.

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Supply Chain Analytics Market Growth Dynamics

Driver: Rising adoption of Big Data technologies

Organizations are continuously collecting significantly more data because of the expansion of the Internet of Things (IoT), social media, and multimedia, which has led to a prodigious flow of data. Data generated by robots and humans is growing at a rate 10 times faster than traditional business data. Additionally, it is predicted that by 2027, there will be about USD 41 billion worth of gadgets that collect, analyze, and exchange this data on the market globally. Several enterprises and individuals have adopted big data analytics because of the rising demand for huge amounts of structured and unstructured datasets to be stored, processed, and analyzed. This adoption is projected to drive market growth.

Restraint: Rising cyber threats hindering adoption of SCA solutions

Companies are analyzing data sets to make strategic choices due to the growth of big data across all business sectors. But data scientists across the world are concerned about data set inaccuracies. Unethical behavior and the rise in cyber threats may cause organizations to worry and, to some extent, hinder the adoption of SCA solutions. Despite the seeming promise of integrating technology into supply chain processes, industry executives continue to worry about possible security and data breaches. Data sets that contain errors, inconsistencies, or out-of-date information run the risk of undermining the company's efforts to develop a robust supply chain analytics project. According to IBM, the US economy loses a staggering USD 3.1 trillion yearly because of poor data, which includes inconsistent, out-of-date, and irrelevant data. Salesforce said that 70% of the data in a company's customer relationship management system (CRM) is outdated or useless every year and that 91% of that data is incomplete. Data modeling that is predictive and prescriptive is a part of the analytics workflows. Predictive and prescriptive analytics predict and prescribe future outcomes by examining historical data, events, and behaviors to produce significant insights that are essential to businesses for future usage. The patterns discovered by analytics models could not be linked with future trends due to the unreliability of the data sets. As a result, data set errors are a significant market restriction.

Opportunity: Growing use of supply chain analytics on cloud

Organizations are leaning toward the use of cloud-based supply chain analytics solutions due to the rising complexity and the growing demand for real-time analysis of data throughout the supply chain ecosystem. The usage of cloud-based analytics solutions primarily aids in tracking and evaluating the total supply chain activities throughout the ecosystems of the forward and backward supply chains. Additionally, the cloud's advantages over other supply chain management system providers, including its affordability, agility, simplicity of use and integration, planning, and scalability, are stimulating them. The substantial installations or adjustments required for the global supply chain systems add to the secondary expenses for businesses and raise the investment costs. Organizations adopt end-to-end supply chain visibility, such as a cloud-based supply system for transportation management, in response to the growth in complexity costs. Enterprises can connect, interact, and communicate with clients, partners, and suppliers due to cloud based SCA solutions in logistics and transportation. Additionally, it aids businesses in creating a safe, dependable, and integrated transportation management system that provides customers with real-time information. These advantages support the expansion of cloud-based supply chain analytics solutions in a variety of industry sectors, including the production of electronic equipment, automobiles, food and beverage products, machinery, and industrial equipment, as well as pharmaceutical, the public sector, energy, and utilities.

Challenge: Reluctance to switch from manual methods to advanced reporting processes

The emergence of big data, smart cities, and IoT has rapidly boosted the volume of data and data sources. Company leaders now have the chance to obtain more pertinent customer- and supply chain operations-focused insights, as well as develop business plans based on them, due to this vast data creation. Companies are still having a difficult time implementing supply chain analytics systems, however, for a variety of reasons. Most of the data created is unstructured. The management of this unstructured data and converting it to a structured manner is a significant issue for organizations. To make the data more extrapolative for greater insights, it is crucial to obtain it in an organized way. According to research by Accenture, 97% of the executives polled found it difficult to integrate a supply chain program into their operations. The poll went on to point out that just 17% of respondents used supply chain technology in all their operations. It is also seen that firms are reluctant to switch from manual methods to advanced reporting and dashboard processes, which is why the adoption of supply chain analytics systems is not accelerating. Most businesses have a relaxed attitude toward new technologies and rely more on their gut than they do on cutting-edge technologies to make wise business decisions. Due to the conventional corporate culture of basing business choices on past company data and occurrences, most of the advanced analytics technologies are experiencing low adoption rates.

By component, Inventory analytics segment to register at the highest CAGR during the forecast period

The supply chain analytics  market by component is segmented into: demand analysis and forecasting, supplier performance analytics, spend and procurement analytics, inventory analytics, and distribution analytics. The Inventory analytics to grow at a highest CAGR during the forecast period. The supply chain analytics market is witnessing increased growth opportunities in the Inventory analytics vertical.

Inventory management deals with raw materials, finished/for-sale commodities, MRO (maintenance, repair, and operations) goods, etc. The key challenge handled by inventory analytics is to precisely have the correct number of necessary products in the right place at precisely the right moment. Inventory analytics keeps a tab on various parameters that include Stock Control, Channel Performance Evaluation, Shelf Planning, and Reducing Inventory Levels.

SMEs segments to register to register at the highest CAGR during the forecast period

Due to its innovative business approach and competitive advantage, supply chain management (SCM) has seen a sharp increase in attention. Small and medium-sized businesses (SMEs) are lagging in understanding how an integrated supply chain generates notable changes in company processes and works with good outcomes in improved quality services, cost savings, and efficiency.

North America to account for the largest market size during the forecast period

North America is expected to have the largest market share in the supply chain analytics  market. One of the other key factors driving market development is the growing need for fast analytics solutions for monitoring and managing the regional distribution chain. The area also has a strong economy and has seen significant investments in infrastructure that is Al-enabled; as a result, established businesses as well as startups are placing increasing emphasis on creating cutting-edge analytical solutions that can serve a variety of industrial verticals. The major users of supply chain analytics systems in North America are business sectors including retail and e-commerce, healthcare, automotive, transportation & logistics, food & beverage, and manufacturing.

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Key Market Players

The supply chain analytics vendors have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgradations, partnerships and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. The major vendors in the global supply chain analytics  market include SAP (Germany), Oracle (US), IBM (US), SAS Institute (US), Software AG (Germany), MicroStrategy (US), Tableau (US), Qlik (US), TIBCO (US), Cloudera (US), Logility (US), Savi Technology (US), Infor (US), RELEX Solutions (Finland), TARGIT(Denmark), Voxware (US), The AnyLogic Company (US), Antuit (US), Axway (US), AIMMS (Netherlands), BRIDGEi2i (India), Domo (US), Datameer (US), 1010data(US), Rosslyn Analytics(UK), Manhattan Associates (US), Salesforce (US), Zebra Technologies (US), Dataiku (US), Intugine Technologies (India), Lumachain (Australia), Hum Industrial Technology (US), Pafaxe (UK), SS Supply Chain Solutions (US),  and DataFactZ (US).

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Scope of the Report

This research report categorizes the supply chain analytics market based on components, solutions, application, deployment mode, organization size, vertical, and regions.

By Component:

• Software
• Services

By Solutions:

• Includes Demand Analysis and Forecasting
• Supplier Performance Analytics
• Spend and Procurement Analytics
• Inventory Analytics
• Distribution Analytics

By Services:

• Professional Services
• Managed Services

By Deployment Mode:

• Cloud
• On-premises

By Organization Size:

• Large Enterprises
• SMEs

By Vertical:

• Automotive
• Retail & Consumer Goods
• F&B Manufacturing
• Machinery & Industrial Equipment Manufacturing
• Pharmaceutical
• Government
• Energy & Utilities

By Region:

• North America
  • US
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • India
  • ASEAN
  • Rest of Asia Pacific
• Middle East & Africa
  • UAE
  • Kingdom of Saudi Arabia
  • Israel
  • Turkey
  • Qatar
  • South Africa
  • Rest of Middle East & Africa
• Latin America
  • Brazil
  • Mexico
  • Argentina
  • Rest of Latin America

Recent Developments:

• In January 2023, the partnership between project44 and SAS combines the largest global real-time transportation data repository with the most intelligent supply chain planning tools available, enabling accuracy and visibility in E2E global supply chains.
• In November 2022, IBM (introduced IBM Business Analytics Enterprise to assist businesses in rapidly making data-driven choices and dealing with unanticipated disruptions.
• In October 2022, Oracle announced a partnership with WellSpan Health to streamline operations and increase business visibility.
• In May 2021, by allowing the deployment of its TrendMiner analytics software on SAP's S/4HANA Cloud, Software AG expanded its partnership with SAP into the field of digital supply chains.
• In February 2021, to enhance product quality, Software AG and SAP have partnered to better surface supply chain management data.

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