Artificial Intelligence (AI) – Expand value on Procurement & Supply Chain

PurchTips edition #441

Intelligent Procurement: How can AI expand Value

There is a great number of reports, articles, and studies done on Intelligent Procurement. This is indeed a rapidly evolving science. For context, it is prudent to define the Concept of Value, Value Chains, and Value Streams.

Value has 3 components:

  1. A set of activities that are engaged in transforming inputs and raw materials from on stage to the next
  2. All activities are done right the first time
  3. Customers are willing to pay for the resulting outputs (good and services)

Value Streams are Supply Chain and are:

  1. Systems that source inputs that interact with data points, machines, processes, metrics, conversion mechanisms, logistics functions, and people to develop and deliver useful products and services to customers
  2. A mixture of value-creating activities, non-value creating but essential activities, and wasteful activities. A Typical value Stream consists of 10% Value Creating, 30% non-value creating but essential activities, and 60% wasteful activities. All three activities can be mapped and quantified for time and dollar impact.

The degree of automation in supply chains vary from company to company depending on size, complexity, complexity, and industry. We will examine how Artificial Intelligence can expand value in Business Supply Chain Operation:

  1. AI Models for Supplier Selection. AI and Machine Learning can leverage sophisticated data models to determine the probability of a supplier meeting the business requirements of the buying organization. These advanced, prescriptive, predictive, and autonomous AI Models can virtually eliminate the probability of selecting the wrong suppliers to deliver mission-critical inputs.
  2. AI for ensuring efficient support of Mission-critical Operations. The Procurement function is responsible for ensuring that all mission-critical inputs are procured at the right price point, delivered on time, with the agreed upon AQL (Acceptable Quality Limit). AI can help create a high degree of visibility with the required analytics and decision execution prowess to guarantee that these inputs are consistently delivered in the required parameters.
  3. AI for ensuring robust Benchmarking. AI can be leveraged to pull data and behavioral models from best in class procurement departments and compared to the capabilities of the buying organization. Helpful gap analysis can be performed with a tip on how to improve processes to close performance gaps.
  4. AI for Leveraging Big Data Sets to realize robust Procurement Function Strategy AI systems are becoming better able to interpret business landscape factors such as socio-demographic, political, economic, technological, competitive, ecological trends. These assessments can be formulated into Strategic Response Models (SRMs) that underpin corporate strategic plans with solutions to link supply chain and procurement function to these corporate strategies.AI Models can be pivotal in executing much of the mundane procurement tasks and free time for procurement to focus on more strategic tasks.
  5. AI for ensuring Non-Value Add Waste Reduction. AI systems being leveraged in a manner to error-proof process, reduce duplicate efforts, and eliminate unnecessary transportation, inventory, motion, waiting, and defects in supply chain activities. These systems are improving in the ability to determine optimal patterns for supply chain optimization.

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