For manufacturers in process industries like chemical and mill products including metals, building materials, paper and packaging, the time lag between issuing a product pricing list, applying customer discounts, and tallying up monthly profits has become an unacceptable eternity measured in reduced profit margins.
Closing the deal at any cost to profit margins is no longer tenable in a market with volatile costs and supply chain disruptions, not to mention competitive threats and heightened competition. Numerous market leaders are adopting dynamic pricing based on the actual cost and value of a product at a precise moment in time.
âDynamic value-based product pricing helps the chemical and mill products industries more effectively adapt to fast-changing market conditions while increasing profit margins,â said Sergey Nozhenko, product expert, process industries at SAP. âBy creating analytics models that incorporate near real-time data, manufacturers can better calculate actual product costs and value to each customer. With these business insights, organizations can rapidly modify pricing strategies for greater profitability.â
Fast pricing flexibility is a competitive advantage
Arriving at prices that boost profit margins for the company and customer value is a delicate balancing act, taking into account not only the costs of raw materials, internal production, and logistics and delivery, but also unfolding regional market trends and customer expectations. Speed that translates to flexible value-based pricing is a major advantage.
âCompanies need to continuously capture, analyze, and allocate relevant product pricing and performance data that impacts profit margins so they can adjust pricing faster,â Nozhenko said. âFor example, using our cloud-based solutions that include SAP CPQ, leaders in process industries are closing the gap between price quotes and actual costs for improved profit margins. Evolving to value-based pricing reflects a business methodology shift to transparent, harmonized, and simplified models.â
Nozhenko said that a leading North American-based wood manufacturer and distributor increased quoting efficiencies by 18% for greater customer wins from data-driven pricing recommendations. After adopting value-based pricing, a global specialty chemical products leader increased prices by 4% compared to the companyâs historical cost-plus pricing models. Another worldwide chemical company achieved 1.8% higher margins after bringing advanced forecasting capabilities into daily price decision tools.
Automation connects pricing to profit margins
Selling hundreds of thousands of products to just as many customers, manufacturers have found automation offers a respite from overwhelming pricing complexities and fierce competition, whether sales involve long-term contracts or spot market transactions.
âItâs not unusual for raw material or transport costs to change 20% to 30% within days, significantly reducing profit margins,â said Dr. Bernd Elser, global chemicals and natural resources lead at Accenture. âCompanies that use price-setting and governance tools gain real-time data visibility, helping them on average increase profit margins by two to 10 percent within nine to 15 months and providing payback.â
Companies can bake algorithms with profit margin relevance into dynamic pricing models that directly boost strategic business plans. Sales representatives can adjust prices based on variables including customer buying patterns, price sensitivity, and order volume. Most important, value-based pricing incents sales representatives to hit profit and not just volume targets.
âDuring the launch phase of a product innovation, the company could adjust pricing to spark initial market uptake momentum among targeted customers,â Dr. Elser said. âWhatâs more, incentivizing salespeople to meet profit goals instead of only volume-based objectives positively changes how field sales builds business growth through profitability.â
AI provides price-sensitive business insights
AI technologies integrated with pricing solutions can deliver actionable insights to guide dynamic pricing â up or down â in response to changeable customer circumstances or market shocks like pricing spikes or other unexpected disruptions. This starts with analytics to improve market forecasts, initially factoring in historical customer buying patterns, followed by external market context over time.
âTraditional AI-based tools can help identify which customers are likelier to walk away if the price is too high, or others that are less price sensitive,â Dr. Elser said. âGenerative AI-based technologies can bring in the latest customer news such as record quarterly profits or impending layoffs plus macro industry and economic trends. Maybe a price list needs an adjustment to stabilize profit margins if raw material costs increase mid-month. In the field, these tools can provide sales teams with the rationale behind pricing decisions, fostering fact-based mutually beneficial negotiations with customers.â
While itâs impossible to predict every future market challenge, value-based pricing helps commodity industries bridge the divide between immediate sales pressures and tomorrowâs profit margin growth.