Supply Chain Analytics Market, By Component (Solution and Services), By Deployment Mode (Cloud and On-premises), By End user Industry (Retail and Consumer Packaged Goods (CPG), Healthcare and Life Sciences, Manufacturing, High Tech and Electronics, Automotive, and Aerospace and Defense), and By Region (North America, Europe, Asia Pacific, Latin America, Middle East, And Africa) - Global Industry Insights, Trends, Outlook, and Opportunity Analysis, 2018-2026

  • To Be Published : Jul 2018 |
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Supply chain analytics is an algorithm that consists of mathematics, statistics, predictive modeling and machine-learning techniques. It helps convert business data including order, shipment, and transactional data of several industries such as, manufacturing, retail & consumer, healthcare, and transportation into meaningful insights.

Supply chain analytics analyses data to provide accurate forecasting that is in tune with current and future market trends. Moreover, supply chain analytics solution is involved in providing real time analysis for huge data set. Rampant growth of unstructured data set through the data or record management of forecasting, transportation logistics, retail and manufacturing, data or transaction of banks and finance, and business tax are expected to boost the growth of overall supply chain analytics market globally, owing to the requirement of analysis and management of huge unstructured data set in shorter time span, which is labor intensive. For instance, machine learning algorithms are used in warehouses to demonstrate an intelligent stock management system for the prediction of resupply requirement in future. In Finance sector, supply chain analytics are used to predict capital costs or the probability of working capital, which helps to target the best suppliers and also provides prompt warning of budget overruns. In transportation, supply chain analytics software can forecast the impact of weather on shipments.

However, data security concern is the factor, which may restraint the growth of global supply chain analytics market.

Supply Chain Analytics Market Taxonomy

On the basis of component, the global supply chain analytics market is segmented into:

  • Services
  • Solutions

On the basis of deployment mode, the global supply chain analytics market is segmented into:

  • Cloud 
  • On-Premises

On the basis of end user industry, the global supply chain analytics market is segmented into:

  • Retail and Consumer Packaged Goods (CPG)
  • Healthcare and Life Sciences
  • Manufacturing
  • High Tech and Electronics
  • Automotive
  • Aerospace and Defense

Supply chain analytics market is expected to witness rampant growth due to growing healthcare sector in the near future.

On the basis of regions, the global supply chain analytics market is segmented into North America, Europe, Asia Pacific, Latin America, Middle East, and Africa. North America region accounted for largest market share of global supply chain analytics market in 2016 due to wide application of supply chain in healthcare sector. Accuracy is one of the major concerns in the healthcare sector. Machine learning have the capabilities to provide more accurate diagnosis and healthcare services, which in turn has augmented demand for supply chain analytics in healthcare sector. For instance, diagnosis of diabetic eye disease requires frequent examination of pictures at the back of an eye by the specialist. The features in the image helps to identify sensitivity of disease, which indicates fluid leakage and bleeding. In 2016, Google has developed a deep learning algorithm, which analyze images and provides training to the system by using a data set of 128,000 images. Thus, the system diagnose the disease with a level of accuracy similar to human ophthalmologists. Google healthcare sector is focused on developing a deep learning algorithm for early diagnosis of skin cancer and breast cancer. 

Major players operating in the global supply chain analytics market are IBM Corporation, Microstrategy, Oracle Corporation, SAP SE, SAS Institute, INC., Capgemini Inc., Genpact, Kinaxis INC., Tableau Software, and Birst, Inc.

Research Methodology

Coherent Market Insights followsa comprehensive research methodology focused on providing the most precise market analysis. The company leverages a data triangulation model which helps company to gauge the market dynamics and provide accurate estimates. Key components of the research methodologies followed for all our market reports include:

  • Primary Research (Trade Surveys and Experts Interviews)
  • Desk Research
  • Proprietor Data Analytics Model

In addition to this, Coherent Market Insights has access to a wide range of the regional and global reputed paid data bases, which helps the company to figure out the regional and global market trends and dynamics. The company analyses the industry from the 360 Degree Perspective i.e. from the Supply Side and Demand Side which enables us to provide granular details of the entire ecosystem for each study. Finally, a Top-Down approach and Bottom-Up approach is followed to arrive at ultimate research findings.


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Coherent Market Insights desk research is based on a principle set of research techniques:

  • National level desk research: It Includes research analysis of regional players, regional regulatory bodies, regional trade associations, and regional organization.
  • Multinational level desk research: The research team keeps a track of multinational players, global regulatory bodies, global trade associations, and global organization.

Coherent Market Insights has a large amount of in-house repository of industry database. This is leveraged as a burner for initiating a new research study. Key secondary sources include:

  • Governmental bodies, National and international social welfare institutions, and organizations creating economic policies among others.
  • Trade association, National and international media and trade press.
  • Company Annual reports, SEC filings, Corporate Presentations, press release, news, and specification sheet of manufacturers, system integrators, brick and mortar - distributors and retailers, and third party online commerce players.
  • Scientific journals, and other technical magazines and whitepapers.
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Preliminary Data Mining

The raw data is obtained through the secondary findings, in house repositories, and trade surveys. It is then filtered to ensure that the relevant information including industry dynamics, trends, and outlook is retained for further research process.

Data Standardization:

Holistic approach is used to ensure that the granular and uncommon parameters are taken into consideration to ensure accurate results. The information from the paid databases are further combined to the raw data in order to standardize it.

Coherent Statistical model

We arrive at our final research findings through simulation models. Coherent Data Analytics Model is a statistical tool that helps company to forecast market estimates. Few of the parameters considered as a part of the statistical model include:

  • Micro-economic indicators
  • Macro-economic indicators
  • Environmental indicators
  • Socio-political indicators
  • Technology indicators

Data Processing

Once the findings are derived from the statistical model, large volume of data is process to confirm accurate research results. Data analytics and processing tools are adopted to process large chunk of collected informative data. In case, a client customizes the study during the process, the research finding till then are benchmarked, and the process for new research requirement is initiated again.

Data Validation

This is the most crucial stage of the research process. Primary Interviews are conducted to validate the data and analysis. This helps in achieving the following purposes:

  • It provides first-hand information on the market dynamics, outlook, and growth parameters.
  • Industry experts validates the estimates which helps the company to cement the on-going research study.
  • Primary research includes online surveys, face-to face interviews, and telephonic interviews.

The primary research is conducted with the ecosystem players including, but not limited to:

  • Raw Material Suppliers
  • Manufacturers
  • System Integrators
  • Distributors
  • End-users

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