Learn how industrial manufacturers can tackle both internal and external pricing challenges with intelligence and speed by leveraging the power of a price optimization solution.
Industrial Manufacturing is Facing Both External and Internal Challenges
The industrial manufacturing industry is currently facing challenges from all angles. First, today’s inflationary pressures, supply chain issues, and labor shortages are negatively impacting margins for many manufacturers, which is leading to an increase in costs which must be passed through, via pricing for products and services. Unfortunately, there is no relief in sight when it comes to input cost pressure.
Making matters more complicated, industrial manufacturers face common challenges brought on by their own industry dynamics. This includes pricing for configured or custom products that might be only made one time, avoiding knee-jerk cost-plus pricing for discrete products and determining the best approach to engineer and price products to ensure a revenue stream from the aftermarket parts business. Essentially, pricing structures and their inherent challenges vary depending on the type of products manufactured. Before getting into solutions, let’s take a closer look at each of these challenges.
Pricing Challenges for Industrial Manufacturing
In this mode of production, costing can be simpler since you know what components you need from the Bill-of-Materials and can plan accordingly. However, this also means that cost-plus pricing tends to become the go-to strategy. While it’s easy to markup costs across the board to target a certain margin goal, overly broad cost-plus approaches don’t allow for any consideration of price elasticity. Customers are unique, so selling to them in a uniform way leaves profit on the table.
Separating customers and products into price segments and measuring price elasticity for each segment is critical. When the pricing team is equipped with this information, prices can be raised where feasible, or lowered where needed, maintaining volume and share. Additionally, precise segmentation allows pricing teams to drop customers into a profitable matrix system. These matrix prices can be used effectively in eCommerce systems, especially for products a customer may not have previously purchased. When it comes to negotiations, pricing can be delivered to sales reps in a CPQ tool as a Start/Target/Floor deal envelope that is highly relevant for each selling circumstance. In customer-specific pricing scenarios, manufacturers should consider a deal management solution to actively maintain the health of customer price agreements and efficiently manage approvals. Systematically maintaining customer-specific prices can enable manufacturers to tailor and personalize prices for customers in digital channels as well.
Many of the custom-engineered parts, products or equipment produced are only made once, meaning each pricing decision is unique. There are two complications that manufacturers encounter: (1) how do you price something that you’ve never made, let alone sold, before?; and (2) you’re not dealing with a single SKU, but rather parts and pieces that get configured into a final product. Therefore, it must be designed and costed out before even considering the price.
The next step is to determine how much pricing power you have (i.e., how differentiated you are) versus your competitors and drive a price accordingly. Most will gather all the built-upon costs and add a markup. But how rigorous is the decision-making for said markup? Is it a guessing game based totally on gutfeel or what you consider a rule-of-thumb fair margin? For those that haven’t transformed their pricing, the answer is usually yes. This means there’s almost certainly money left on the table and in some cases overpricing, which results in lost sales and customer dissatisfaction.
It is much more effective to arrive at a markup using a scientific approach. You can (1) build up to a cost and apply price optimization to determine the optimal markup based on the product configuration and selling circumstance; or (2) build up to a cost, apply a markup to a list price and then optimize for discount guidance. Both tactics leverage real transaction data and customer/product price elasticity into the decision, delivering sizable growth to the bottom line.
Manufacturers need to determine how best to engineer and price products upfront to ensure they get the downstream aftermarket business. The original product price serves as a guideline for the aftermarket price of its component parts.
Pricing it too high upfront could be problematic and combining that with the highly variable nature of who you’re selling to in the aftermarket creates a classic price optimization scenario. How do you produce a competitive list price with so many buying personas to account for? How do you purposefully assign customers to a matrix that produces market-aligned prices? What kind of discount guardrails can you provide to sales reps to help them negotiate customer-specific agreements or spot transactions? If selling online, how do you enable automated negotiation functionality? The solution lies in the power of price optimization.
Market Volatility & Inflationary Pressures
Cost fluctuation represents an ever-moving target that hinders profitable pricing. Market volatility combined with stubborn price inflation and creating and selling products in very different ways with different costs to wildly different customer segments can have a negative impact on a manufacturer’s bottom line. The fact is that it’s a near impossibility to consistently arrive at the best price using outmoded tools and processes. Solving these internal and external challenges requires data science, advanced price management, and deeper customer/product segmentation capabilities.
An Intelligent and Scientific Pricing Transformation is Critical to Success
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