We also discussed one method, what-if analysis, that organizations can use to move from demand manipulation to the extended definition of demand shaping. For example, an oil company might want to know how to allocate their capital (that is expected to last years) when the price of oil decreases due to government policy. The scenario would be simulated and compared to a baseline, allowing the oil company to determine how to get the best return for their shareholders.
In part two, we will explore optimizing price and revenue, the second method for achieving demand shaping. We’ll share how this method allows an organization to achieve optimal supply and demand alignment for their business.
Optimizing revenue and price allows organizations to explore alternative and optimal demand options such as pricing, promotions and substitutes to maximize profitability and revenue while accounting for the supply chain constraints. In other words, the demand dynamics are placed into an optimization model while the relevant constraints are applied, allowing an organization to explore the different demand dynamics.
For example, a computer manufacturing organization has a limited amount of raw resources — such as circuit boards — but they want to know the different promotional strategies and pricing options they could use, given their limited amount of raw resources. This allows them to find the most profitable pricing for their current resource allocation.
Since seeing the success that hotel companies and airlines have had with price and revenue optimization, these methods are now being applied in retail, manufacturing, and CPG industries. They are relatively complex and require the development of new algorithms, hence this approach is still being perfected. (Learn more about the up-and-coming area of algorithmic business in this blog post.)
As you may have noticed, the what-if analysis and price/revenue optimization methods are two different approaches to help organizations move beyond demand manipulation. However, both approaches use different models and answer different questions.
What-if analysis allows users to evaluate alternative strategies and policies to maximize their revenue and profit performance while considering risks and supply chain constraints. Typically, the demand options are developed by running an econometric model. Those demand options are then used in an optimization model to determine proper resource allocation.
This means that what-if analysis focuses on the ability of the supply organization to support the presented demand, which is a resource allocation problem. It answers questions such as, “Can we fill this order?”
A price and revenue optimization approach skips the econometric model. As noted above, the demand dynamics are ran through an optimization model instead. This means that a price and revenue approach focuses on the ability of the supply organization to change demand. This method goes one step further than what-if analysis and allows organizations to answer two very important questions: “Can we satisfy this order?” and most important, “Should we accept this order?”
With this knowledge, organizations can give themselves a competitive advantage while maximizing revenue and profit.
The price and revenue optimization method allows organization to achieve production and sales goals while balancing the rapid fluctuation of supply and demand by taking into account both the demand and supply dynamics. There are multiple reasons an organization would want to pursue using this approach to demand shaping.
This concludes our two-part series on demand shaping. In this series, we extended the idea of demand shaping to include all possible supply and demand information. The benefits to an organization that shifts to demand shaping, as opposed to using demand manipulation, are increased profitability, financial optimization and a large competitive advantage.
The two approaches we looked at were a what-if analysis and a optimizing revenue and price. Either of these approaches give an organization a significant competitive weapon.
An organization’s ability to execute this type of demand shaping requires a well-built analytical engine that models the complexity of the supply and demand dynamics in real-time while considering all the goals, constraints and financial variables of the business.