The global pandemic, COVID-19 has shifted all business priorities. The impact and shifting patterns due to the virus are evident in the supply chain and logistics business globally. After a stagnant period of closed borders, organizations may be able to identify the impact of their business.

The global nature of the economy requires all companies to comprehend their supply chains, and furthermore the natural risks that they might be presented to supplier and client levels. Monitoring these risks will help with detailing corporate procedures and business strategies.

Companies expected business to tank but instead, it peaked in the short term which is that the volumes were expected to be reduced however they increased based on the current global scenario. The data available within the organization combined with the market analysis, companies can use data to turn this to an opportunity especially with ‘price’. Using price agility as a technique it will help companies steer and adapt prices based on market conditions.

Organizations can build agility into their pricing with the following:

  1. Data-driven Dynamic Pricing Engine

‘Dynamic- Integrated Pricing’ which means that every time a customer asks for a quote to ship a product on a particular trade lane – they get a price that has the highest probability of winning the deal since it is market adjusted, capturing the customer willingness to pay while also maximizing revenues. The computation of this ‘perfect price’ is done by a Dynamic Price algorithm that looks at a whole range of different variables and computes a price intended to strike an optimum. The data and variables that go into price determination are historical transactional data, vendor costs, market demand and supply, customer negotiation and purchase history, customer price sensitivity, macroeconomic indicators.

  1. Price-steering

Strategy for done at a higher-level reducing customer churn and improving acquisition performance, with the least amount of penalty on margin, some advanced simulation, scenario analysis, and model steering techniques built upon the existing dynamic pricing algorithm. Simulation Algorithms can be used to find the margin-conversion tradeoff from historical data on past performance. Pricing managers then ran scenarios analyses to assess the business impact of different points of the tradeoff curve. Once the desired setting was chosen, the strategy (higher conversion by sacrificing minimum possible margin) can be passed on to the algorithm as a new objective function. Parameters/Features of the algorithm then automatically are adjusted to revise the price recommendations and guidance that sales are receiving, to help meet the new business strategic objectives.

  1. Price Rules

Directly influencing the account manager by giving guidelines or by setting target prices based on the current global situation that helps your company to not be solely dependent on your quarterly list prices. These guidelines are created with the help of a ‘rules engine’ that helps you immediately act on a certain event by using new prices based on your target in your CRM. In the same place you can see your quotation and new price points on certain levels.

Businesses and the economy are in another phase at the moment, getting themselves increasingly powerless against the risks of globalization and supply chain interruption. As needs are, utilizing the right data and determining methodologies and tools will be essential to organizations as they explore the present market condition and keep on settling on strategic choices.