Response planning enables businesses to accommodate changes in demand through making production adjustments. The COVID-19 crisis caused unanticipated shocks to the supply chain, triggering the need for stronger methods of response planning.  

The use of traditional models, such as spreadsheets, has proven to be ineffective when adapting to the current needs of response planning. These models are unable to react to fast-moving data, causing lag in forecasting. Forecasting is used to improve decision making quality – therefore inaccuracies in forecasts lead to substandard decisions. Through the use of artificial intelligence, creating improvement in problem areas of response planning leads to better accuracy, effective use of limited resources, and more collaborative decisions.

According to Gartner, three areas of improvement in response planning through digital supply chain forecasting are:

  1. Variability and Bias – Using digital technology to avoid variability and reduce human bias
  2. Data – Using digital technology to eliminate missing, wrong, or out-dated information
  3. Model – Using digital technology to improve accuracy or scope of the current model being used 

In order for businesses to improve operations and response planning as a whole, the implementation of AI is imperative to keep up with trends in today’s society.’s artificial intelligence business assistant, Athena, turns data into proactive insights to optimize the supply chain and give real-time visibility that ultimately creates more efficient routes to gathering critical information needed to make accurate and informed decisions.

Athena addresses the critical areas in supply chain response planning through her ability to: 

  1. Flag inconsistencies in inventory which reduces variability and eliminates unnecessary costs
  2. Provide real-time reporting to reduce the usage of stale data
  3. Create recommendations based on the tracking of trends in the supply chain 

As businesses implement artificial intelligence in their response planning methods, there will be a continuation of better accuracy, stronger decision-making, and smoother reaction times, which will ultimately reduce costs and drastically improve the function of the supply chain. 

See how can provide actionable insights to improve response planning in your supply chain:

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