SignalDemand: Dealing with Supply- and Demand-side Pricing Matters - Part 2

Part 1 of this blog series described the conundrum that commodity-based manufacturers encounter when it comes to determining the best price, production mix, and volumes. It also introduced SignalDemand, Inc., which applies math and science to the problem of price and margin optimization software for large-scale manufacturers.

SignalDemand stands alone as the only provider of price management and optimization software that takes into account the key supply and production constraints impacting manufacturers. In other words, its application is using pricing as a demand and supply matching mechanism for manufacturers of consumer goods.

Namely, on the supply (upstream) side, commodity-focused hedge funds have long leveraged supply optimization software, while on the demand (downstream) side, wholesale distributors and retailers have for some time leveraged demand management and optimization software. Conversely, manufacturers have for too long been left in the middle shooting in the dark when it comes to concurrent pricing and demand management.

Pricing Science of Matching Supply and Demand

Other price optimization solutions really only consider the demand side of the pricing equation, and these results are insufficient for manufacturers to make decisions when they need information on capacity and production constraints as well.  SignalDemand's hand-picked team of scientists and mathematicians from prestigious universities have built a pricing science based on eight pending patents.

This sophisticated science drives the recommendations provided by the software application. When making decisions on margins, the idea here is to account for all major profit drivers, such as to

  • align strategic business objectives with pricing decisions;

  • understand demand drivers to forecast future sales;

  • account for fluctuating costs;

  • on the supply side, account for asset utilization, available capacity, and inventory situation; and

  • determine the most profitable product mix for a given demand.

Accounting for all the above factors helps with much more complete, consistent, and actionable information to better anticipate future costs, forecast demand, identify poorly performing products or customers, and explore projections in the context of historical sales.

How SignalDemand Works

At a high level, the process to determine the best mix of products and price points to drive up margins goes through the following four steps:

  1. Leverage historical data to model products’ demand elasticity (or price sensitivity) in each market segment;

  2. Evaluate fabrication (production) operations alternatives, cost drivers (both projected and current ones), supply forecasts, and capacity constraints;

  3. Evaluate all production and pricing options (performance projections) to maximize margins (and revenues); and

  4. Recommend optimal (“demand shaping”) trade, net, or list prices, based on established corporate objectives and business rules.

SignalDemand software performs pricing scenarios to help maximize suppliers’ margins by delivering optimal products’ prices to balance demand, supply, and external competitive factors. Contrary to manual or spreadsheet-based methods, SignalDemand was built to handle today’s astronomically huge data feeds and speeds.

The product is able to evaluate billions of pricing scenarios based on thousands of variables. Some of these factors can be: market data, order history, channel demand forecast, commodity price history, commodity futures, customer hierarchy, cost of goods, overhead cost, activity costs, inventory positions, bills of materials (BOMs), plant hours calendars, plants, production lines, resources, product hierarchy, materials options, plant utilization data, corporate goals, supplier availability, intuitive (empirical) input, etc.

This holistic supply chain network-based pricing is the only way to take advantage of pricing applications to improve overall profitability, in light of both supply and demand opportunities and constraints. Recommendations for product price and mix can be projected for spot market, weekly, monthly, or long-term contract purchases.

This capability gives supplying manufacturers much more confidence in fact-based price quotes (in front of mighty retailer customers) and mitigates their risk using better projected information. Namely, with SignalDemand, vast transactional data in terms of observed quantity vs. observed price can identify elasticity and other pricing trends, and account for any outliers.

The Very First Customer Speaks Out

SignalDemand’s very first customer was the second largest North American beef and pork processor Cargill Meat Solutions. The company uses SignalDemand for daily optimization support for 150,000 pricing, production volume, and mix decisions every week. The meat processor has been able to translate commodity fluctuations into pricing decisions for every product and time horizon (from spot market sales to long-term contracts) and to determine how to best process the meat to maximize margins (in terms of recommended changes in mix and supply).

Last but not least, Cargill has reportedly improved its often arm-twisting customer relations with retailers via fact-based pricing approach. Namely, it operated with increased confidence when it shared its pricing models by tracking individual stock-keeping units (SKUs) over time with one of its large buyers (a near-bullying retailer).

This transparency resulted in Cargill being awarded a long-term contract to supply every SKU for the product category for all the retailer’s stores. This contractual commitment has allowed the meat supplier to stand tall and bring significant value to the table for the retailer and consumers, rather than provide product price and availability alone.

Along similar lines were the experiences of Hormel Foods, a leading processor of branded, convenience meat products, and Seaboard Foods a leading pork producer and top exporter, for whom SignalDemand has helped balance supply, demand, and costs in the face of ever-shifting global market conditions.

I should also emphasize that SignalDemand is the only on-demand price optimization software for manufacturers (since DemandTec and Revionics focus on retailers).  The software as a service (SaaS) model allows the vendor to deliver science-based results to its customers 24 hours a day, seven days a week.

SignalDemand’s team works to continually improve the science powering the solution, so that customers have access to the best science-based recommendations at all times. This contrasts with the more rigid, traditional on-premise and perpetual software licensing models where new updates require onsite visits and extensive implementations.

Challenges and Opportunities (More Of)

On the down side, SignalDemand is still a fledgling company, whose worldwide headquarters are located in San Francisco, California, United States (US) and its European headquarters are located in London, United Kingdom (UK). The application is currently available only in English, but the company has plans to localize the solution to meet the requirements for other markets. The company is currently also in discussions with a number of technology, reseller, and consulting partners.

In the long-term, SignalDemand will have to more aggressively expand its presence beyond the established stronghold in the food processors segment. Other potential verticals, especially those that leverage reverse BOMs would be chemicals, oil and gas, high-tech, metal centers, and industrial manufacturing.

But although the ability to use pricing applications to profitably match supply to demand (while taking costs, on-hand inventory, and capacity into consideration) is a critical need across all those verticals, penetrating a new vertical is not an easy task. It requires a deep domain expertise to develop viable proofs of concept for first customers, an intimate knowledge of industry-oriented pricing and activity-based costing (ABC) models, experienced consultants, and so on.

Nonetheless, the recently raised round of funding might indicate that SignalDemand has a good value proposition in the eyes of its financial backers, especially with manufacturing companies whose operations revolve around sourcing commodities. Particularly these days have we indeed been witnessing volatility of some commodities like corn or oil. In fact, without intending to become too fancy, besides managing downstream demand and optimizing manufacturers’ profit margins, the vendor might want to start using its science to provide upstream supply recommendations.

In other words, besides currently using upstream supply data as inputs to recommending downstream pricing (that the customer will accept while the manufacturer will be profitable), how about supplying useful information in the other direction too? The process could be turned around to recommend, say, what supply levels might be optimal to meet demand based on price projections (of both commodities and finished products).

Since the lead times for many commodities can be quite long (i.e., putting more arable fields into production for a growing season or raising more livestock to bring to market take some serious doing), suppliers can use this information to decide whether to invest in more production or search for alternate sources of supply (also in light of the specific quality or regulatory requirements). By mastering this bidirectional supply-demand information highway, SignalDemand would certainly set a much higher bar for many other pricing vendors to reach.

Therefore, dear readers, what are your views, comments, opinions, etc. about SignalDemand’s value proposition and about the pricing optimization software market in general? We would also be interested in your experiences with this nascent software category (if you are an existing user) or with your current (possibly ineffective) practices, and your general interest to evaluate pricing solutions as prospective customers.
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