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September 9, 2021 | 15:09

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Data analytics has already transformed several spheres, and logistics is not an exception. The industry constantly overcomes challenges of numerous data sources and weak customer satisfaction. Data analytics methods are handy for managing and processing information accurately. What’s more, the technology leads to greater industry consolidation.

In 2021, Gartner researchers identified only 9% of supply chain executives without plans to invest in advanced analytics. The demand is high, but the supply doesn’t catch up. The key problem is to find the right tool and a reliable technology provider. For your convenience, we’ve created this overview of supply chain analytics to help you understand this software type and pick a great tech partner.

“96% of respondents use predictive analytics, 85% use prescriptive analytics and 64% use AI”

Gartner Research

4 Main Analytics Types for Supply Management Process

Depending on the exact supply management tasks, you can rely on one among these 4 types of supply chain analytics:

  • Descriptive analytics. This is the instrument to process historical data. Normally, the sources for information include both internal supply chain software and external systems. Within this data set, the tool draws predictions on possible changes
  • Predictive analytics. With this type of analytics, supply chain companies can work with possible business scenarios, predicting disruptions and complex problems. Check this detailed overview on predictive analytics in supply chain execution in our blog
  • Prescription analytics. This tool has both descriptive and predictive analytical capabilities. In particular, it uses historical data for suggesting business-relevant actions
  • Cognitive analytics. Being AI-enhanced, this analytics type completes operations similar to human behavior and thinking. This tool is useful for solving complicated context-dependent issues
  • Check below how you can apply these supply chain analytics types in your daily business operations.

    IBM Planning Analytics with Watson

    Analytics in Planning and Demand Forecasting

    A hero illustration explaining synthetics testing best practices

    The power of descriptive analytics applies to improving organizing and controlling processes. Historical data shows the best-working strategies already applied in this dimension and forecasts what your customers will order.

    Here are the opportunities of supply chain analytics you can capture:

  • Predictions on sales
  • Forecasting demand and picking the right tools
  • Adjusting forecast accuracy
  • Sales and operations planning
  • For example, Bravida, a Nordic systems installation and servicing company uses IBM planning analytics for long-term planning. The software assists in budget management and has established an easy-to-use system for business users. After release, the software has reduced budgeting cycles by 90%.

    Traditional Statistical Methods

    The software adopts mathematical formulas, models, and techniques for describing trends and forecasting their presence. That’s the basic prediction approach that relies on general stability only, without considering changing environmental factors. Nevertheless, traditional statistical methods are useful for understanding the stable tendencies in your company.

    Machine Learning Techniques

    This technology deals with Big Data. Thus, it’s capable of determining implicit trends and connections between factors that affect corporate performance. This advanced method can provide reliable predictions for the dynamic environment, thanks to the huge data set analyzed non-stop.

    Solutions to help your business from Planergy

    Analytics in Procurement and Contract Management

    Supply chain analytics opportunities help manage resources and strategic partnerships in your company. Here, the tool analyzes the existing data records and provides recommendations on the best vendors and suppliers in the given case. Moreover, supply chain analytics can advise on the terms of cooperation.

    In terms of supply chain design, the analytical software assists in:

  • Entire supply chain network modeling
  • Redesigning distribution
  • Assessing strategic partnerships
  • An example of this analytics application is Planergy software in University Orthopedics Center (UOC). In the organization, the technology processes real data and lets the executives make more cost-effective purchasing decisions. Besides, the centralized system warns about possible overcharges for products in advance.

    Supplier Evaluation

    Supply chain analytics gathers information on your suppliers to provide you with valid suggestions for each purchasing case. The software scans order histories and applies KPIs to check reliability and trustworthiness. You will see the prices, experience, and other relevant factors in the system.

    Supplier Performance Review

    This tool is useful for preparing negotiations with suppliers. In supply chain analytics, you’ll see different metrics that describe the overall supplier profile. For example, you can compare defect rates, the presence of extra charges, and the processing time needed to make an informed choice and clarify the details and terms needed.

    Katana Manufacturing ERP software

    Analytics in Inventory Management and Sales

    Application of supply chain and data analytics empowers manufacturing and purchasing goods with greater stock optimization. By having access to accurate inventory information updated in real-time, you’ll see the actual quantity of your goods whenever needed. With the forecasts on future demand, you’ll increase the accuracy of your selling practices.

    In this dimension, supply chain analytics is helpful in:

  • Inventory categorization
  • SKU rationalization
  • Enhanced inventory planning
  • Real-time visibility of goods
  • Inventory synchronization
  • Order management tracking
  • Arranging warehouse processes
  • For example, Essence One uses software from Katana to increase visibility over inventory and improve production capabilities. With enhanced analytics, the company managed to bring in the pricing predictability in the circumstances of seasonality. What’s more, the supply chain analytics improved delivery by providing greater control over distribution channels.

    Stock Management

    Better demand management in combination with predictive analytics brings good to your company in several ways. You get more control over the left inventory, can rely on historical data to make demand predictions, check the gaps in real-time, and update them timely. Besides, you can clearly see best- and worst-performing positions and make informed decisions on changing the composition of your inventory.

    Optimizing Warehousing Operations

    Inventory analytics deals with the flow of your goods, not only their state. The tool will recommend proper allocation and provide optimized routes for delivery. This way, you can control what’s happening with your inventory while it’s in transit between point A to point B.

    Evaluating Channel Performance

    You get everything needed for informed channel assessment with historical data on vendor performance, goods’ conditions, and already spent resources. In addition to analytics for the supply chain, BI tools are useful here. In the dashboard, you’ll get access to reports on each channel and can timely make decisions needed to rearrange loading between the channels.

    Shelf Planning

    Supply chain analytics deals with seasonality-related problems. In this case, the technology uses information on historical trends and balances it against current customer behavior. As a result, you get handy recommendations on the relevant amount and place of your goods. This way, you’ll improve your current inventory optimization practices significantly.

    Pricing Optimization

    Analytical tools can adjust not only the number of goods but also their prices. If you apply enhanced software (like an ML-empowered program), your supply chain analytics will collect Big Data from internal and external sources and provide the most accurate pricing. The technology can consider customer categorization, the current and predicted behavior of your competitors, and the general market condition.

    Reducing Shrinkage

    Once a supply chain analytics tool is implemented in your company, it will possess all the data necessary for loss prevention. For this aim, it needs enough data about your previous thefts and mistakes. The technology will draw conclusions, relying on multi-factor analysis.

    Azure IoT development solution

    Analytics in Logistics and Transportation

    Supply chain management analytics is a powerful tool for tracking, optimizing, and improving the cost-effectiveness of your routes. In general, it introduces greater visibility of processes and the overall effectiveness of operational processing.

    In the logistics and transportation dimension, supply chain analytics does the following:

  • Fleet routing
  • Route optimization
  • Reporting system automation
  • Increasing fuel consumption efficiency
  • FoodserviceCo, a UK-based multinational online food service, uses an Azure-based IoT solution to get rid of the manual reporting system and introduce more effectiveness in the processes. The mobile software established a transparent supply chain system with real-time updates. Among its improvements, the software prevents the possibility of lawsuits, threats to customer satisfaction, and loss of revenue.

    Fuel Management

    Fuel control has a direct impact on increasing the cost-effectiveness of your business. With the handy reports on driver behavior, fuel expenditure, and payments, you’ll get evidence to optimize fuel spending in your company.

    Route Optimization

    Analytics supports your delivery strategies. This instrument tracks delivery operations, detects routes of maximum cost-effectiveness, and minimizes time spending. If you’re interested in getting real-time dynamic route optimization for your delivery business, check this guide first.

    Shipment Tracking and Vehicle Maintenance

    The condition and movements of your vehicles are among the most influential indirect factors on your budget spending. With sensors and other IoT devices, you can track these parameters in real-time. Analytical tools will predict the repair calendars and show the best- and worst-case movement scenarios.

    Reducing Delays

    Normally, you deal with the delay first and get the reason then. With supply chain analytics, you can predict these situations and eliminate them in advance. Moreover, while choosing, you can evaluate the performance of your carriers by the delivery time criteria right in the system.

    Choosing Carriers

    The software lets you decide on carriers for future cooperation. For this, contact management supply chain analytics matches your profile with the most suitable partners according to your criteria. This way, it lets you work on the best cooperation conditions.

    Intermodal Transport Optimization

    If your delivery requires changing several transport modes, the management and optimization become harder. But with supply chain analytics, you’ll get a handy system where all the information from different channels will be present in an easy-to-use dashboard. And the functionality of predictive analytics will let you rely on data-driven predictions for route optimization.

    Managing Returns

    The software provides you control over problem situations at your workplace. There’s no need to clarify each time what’s the reason for return. Supply chain analytics will automatically gather all the relevant information and forecast all possible conditions for returns to happen again.

    How to Implement Analytics and Integrate It into the Supply Chain Management Process

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    Since supply chain analytics solutions have different types and applications, it’s hard to get a one-and-only ready-made program that will fit your business needs perfectly. Going for custom software development is a much better choice.

    For your understanding of how an integrated custom supply chain system works, check the example of a logistics platform with ERP, TMS, and CRM modules we’ve created for InnLogist. Its admin panel works with numerous sources of information simultaneously and provides real-time updates relevant for order management. The reporting module provides documents and an overall picture of the company’s balance sheet. 

    It may seem simple, but building such custom software takes time and several stages of negotiations. Otherwise, it won’t serve your business needs accordingly. This section will share the working model for cooperation with a tech vendor while making custom supply chain analytics software.

    Identify Your Business Problem

    Any custom software development should start by considering your business needs. At this stage, aim at clarifying all the nuances behind each expectation articulated and concern raised. The more detailed roadmap you develop together, the easier it will be to manage the process. As a client, you’ll get a better result, and your development team will understand what’s needed from the very beginning to fit all your needs.

    Establish KPIs

    Actionable KPIs will validate the goals and expectations revealed before. For example, if you want to increase cost-effectiveness, you should give your development team an exact number. In return, they’ll develop an action plan and indicate the set of technologies needed, a project timeframe, and total development cost. Together, you agree on the exact number and introduce measurable criteria for future cooperation.

    Define Data Sources

    For effective working, supply chain analytics should collect data from different sources. That’s why arranging and providing access to all the internal and external information portals is the next essential step in your cooperation. The data sources definition stage may need the transition of papers to digital formats and getting access to third-party databases to migrate the information.

    Here’s the list of possible data sources you may use:

  • ERP
  • CRM
  • TMS
  • IoT devices
  • Printed documents
  • Social media
  • Partners’ information
  • Customer support
  •  Assemble the Data Team

    Once you decide on the software difficulty level, your tech provider will gather a development team.

    The possible team roles may involve:

  • Software engineer
  • Business analyst
  • Data scientist
  • Data engineer
  • Work on the Culture

    For your software solution to work, a supporting data-driven culture is needed. In this dimension, it’s the task of top executives to reveal the importance of information sharing. Employees should understand how to use software for making routine decisions and completing mundane tasks faster and easier. Otherwise, the digital transformation will be just a formal event, not a core business change.

    Start with Existing Analytics Capabilities

    Typically, current corporate computing systems already possess some analytical features. After describing the need for data-driven culture, it’s effective to get acquainted with this approach in an already existing environment. This way, the new software introduction will pass smoothly and easily.

    Develop Business-Specific Analytics Platform

    While you’re paving the way for the supply chain analytics implementation, your tech partner should complete the work on customized data architecture. Even if you go for an easier-to-implement business intelligence supply chain solution, data analytics still requires the involvement of a data engineer to set up the appropriate flow of information. 

    Once you get the digital solution, check if all its functions work appropriately and your employees find it easy to use. Otherwise, it should be sent back to the development team for elaboration.

    Let AmconSoft Be Your Supply Chain Analytics Software Development Partner!

    AmconSoft offers custom software development services for a supply chain analytics solution. We work with a wide set of technologies to address all your business needs. Once needed, we can enhance the analytical modules in your existing CRM and ERP systems. Alternatively, we can build a separate analytical software that will join your existing computing environment.

    If you decide to build supply chain analytics from scratch from us, here are your benefits:

  • Working solutions to your business problems. We always start with discussing your case in detail and elaborating mockups and prototypes we both agree on. Through the development process, your expectations are our top priority
  • Tech expertise. Our developers possess more than 7 years of experience and can combine complex processes and technologies in easy-to-use solutions
  • Dedicated team. We take responsibility for each project we take. You can reach us anytime during and after the development process and get our tech specialists’ needed consultation, support, and clarification
  • While referring to AmconSoft, you’ll get a workable solution that perfectly suits your business needs. We work with industry-specific demands of any scope and complexity, including special supply chain management needs. We’re ready to develop a business-specific analytics platform for your business. Contact us, and let’s get it started!

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    Written by:

    Artem Ramazanov

    Through the 10 years in marketing, I’m establishing partnerships with the reps of various fields in business and managing the aspects of business administration to achieve more success with my company

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