Supply Chain Analytics: Opportunities in Data Analysis and Business Intelligence

  • keeping up with rapidly changing customer demand,
  • dealing with delays and disruptions,
  • inefficient planning,
  • lack of automation,
  • rising costs (of transportation, labor, etc.),
  • diversity of sales channels, and
  • complex structure resulting in siloed data and lack of visibility.

Supply chain management process

Supply chain management process
  • Planning mostly concerns demand forecasting and resource planning.
  • Procurement is a set of operations related to choosing vendors, negotiating the terms of cooperation, and buying supplies needed for your business.
  • Manufacturing deals with production and capacity management.
  • Inventory management is focused on keeping the optimal stock balance, sales, and warehousing operations.
  • Logistics management covers order fulfillment and all delivery activities.
Optimization opportunities offered by analytics

Analytics in planning and demand forecasting

Comparison between traditional and machine learning approaches to demand forecasting

Analytics in procurement and contract management

Example of the procurement dashboard interface

Analytics in manufacturing

  • machine/cell performance,
  • shift performance,
  • throughput,
  • quality and scrap rates, etc.
Production performance dashboard example

Analytics in inventory management and sales

Inventory management dashboard example

Analytics in logistics and transportation

Fleet management analytics dashboard

How to implement analytics and integrate it into the supply chain management process

Identify your business problem

  • reducing inventory to release cash,
  • finding more reliable suppliers,
  • preventing equipment breakdown,
  • increasing product quality, etc.

Establish KPIs

Define data sources

  • an enterprise resource planning (ERP) system,
  • a customer relationship management system,
  • a logistics management system,
  • a transportation management system,
  • a warehouse management system,
  • accounting software,
  • IoT devices,
  • eCommerce platforms,
  • customer support,
  • non-digital information like phone calls or printed documents, and so on.
  • B2B integration platforms,
  • social media,
  • partners’/competitors’ performance information,
  • outside research,
  • customer feedback, etc.

Assemble the data team

Work on the culture

Start with existing analytics capabilities

Develop business-specific analytics platform

A few more tips to consider

  • Conducting real-time analytics besides just creating reports is crucial to ensure timely reacting to possible changes. Also, setting up customized alerts and notifications helps quickly obtain targeted information about disruptions. Collecting historical data and generating reports is also important, i.e., for observing trends or monitoring performance, but using real-time data would let you immediately know about malfunctions, accidents, or any sudden changes so that you can take rapid action and avoid losses.
  • Implementing self-service BI would enable sharing data across the organization and provide access to multiple users outside the CEO-suite. That, in turn, would drive business agility and accelerate decision-making on all levels.
  • Deriving from the previous one, it’s important to ensure that dashboards and reports are tailored to different user roles. That means setting different access preferences for users of different levels and also ensuring a user-friendly interface for non-technical employees.
  • Mobility, or the ability to use BI tools and see data analysis results on mobile devices, is another factor that expedites the decision-making processes.
  • Seamless integrations are key to smooth data sharing across departments and software modules. Having all the company data in one system is the only way to conduct accurate analysis. So, you have to ensure that all the data sources such as business management systems, web store platforms, IoT devices, 3PL or carrier systems, etc., are connected and synchronized with your BI software. Sometimes, BI platforms offer some of these integrations out of the box, but it’s worth considering partnering with an integration provider to set up a perfect customized integration architecture.
  • Deployment type is another significant decision to make. Typically, on-premise software is thought of as more secure, reliable, and customizable, while cloud-based is cheaper and more scalable. But now online solutions have developed to such an extent that they can easily compete with traditional on-premise platforms.
  • Sometimes, the final cost of a software is not obvious and, besides a subscription and/or monthly fee, can include hidden expenses such as additional customization, after-purchase support, hardware costs, implementation and training costs, etc. Be sure to take everything into account.

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AltexSoft Inc

AltexSoft Inc

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Being a Technology & Solution Consulting company, AltexSoft co-builds technology products to help companies accelerate growth.