MDM Classics: Managing Pricing Algorithms - Modern Distribution Management

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MDM Classics: Managing Pricing Algorithms

Three factors for distributors to consider when evaluating risks in automatic pricing.

Technological advances are providing distributors the opportunity to help mine increasingly larger datasets. However, if algorithms are not managed appropriately, too much of a good thing can backfire. This was the message of a Wall Street Journal report by Deloitte, On the Board’s Agenda: Board Oversight of Algorithmic Risk.

In Managing Pricing Algorithms, from February 2018, Lee Nyari, managing partner of The Innovative Pricing Group, discussed how Deloitte’s views on algorithmic risk management generally apply in distribution pricing. Below, we review three of Nyari’s key factors to consider.

Learn more about pricing algorithms this spring at MDM’s Pricing & Profitability Summit.

1) Pricing is a useful and powerful business lever in distribution

A key question Deloitte asked in its report was, “What are the potential impacts if the algorithms go wrong?" Pricing is a high-stakes game, according to Nyari. A successful pricing project can have a favorable impact on a distributor’s business performance. Ineffective pricing practices can also create a lot of pain. They can cause strategic damage, such as weakened strategic customer relationships, marketshare losses, low morale and more.

Weak pricing practices are more frequently being exposed due in large part to the growing popularity of e-commerce, and the resulting increase in pricing transparency for the distribution industry. Combine pricing’s importance in driving performance, the industry trends toward price transparency and the emphasis often put on the mathematical sophistication of toolsets to analyze large and complex distributor pricing datasets, and you can quickly see why algorithms, and their risks, represent a major consideration in distribution pricing.

2) Excessive price complaints may signal algorithmic risk

Deloitte advised looking for signs that algorithms may not be functioning effectively, such as “complaints about them from constituencies such as customers, suppliers, employees.” Deloitte suggested that when signs of trouble are spotted, the business should conduct an independent review of the relevant algorithms.

In Nyari’s assessment, distributors vary in how they respond to price complaints from sales reps and customers. Some simply allow for habitual manual overrides of the outputs of their pricing algorithms. These distributors might have “given up” trying to fix their pricing algorithms, or their management may believe that the ongoing flow of price complaints is somehow normal.

Seasoned executives understand, he said, “some push-back on pricing is healthy – otherwise you are not pricing to resistance, and you are leaving money on the table.” It is true that some noise around pricing is to be expected. Still, if pricing is a constant source of headaches in certain parts of the business, then this may be a sign that the relevant pricing algorithms could be misfiring.

Several other types of corrective actions are also frequently prioritized before reviews of pricing algorithms. They include stepping up controls to force the use of the pricing recommendations produced by the algorithms, and/or investing in pricing-related training programs for sales reps. While some of these types of corrective actions can be helpful, No. 3 below explores some situations where reviewing the pricing algorithms themselves might be a more effective response.

3) Pricing algorithms may be insufficiently market-informed

As any distribution sales rep will tell you, effective pricing is about more than just mathematics. It requires, among other things, an understanding of markets and customers, as well as the particulars of the offerings themselves. This cuts to the way pricing algorithms are developed. Pricing algorithms do not replace industry expertise and they are most effective when they are deeply informed by industry experts’ judgment.

Algorithmic risk increases when knowledgeable market experts do not provide extensive, direct input into model design decisions. Too often, however, their input in pricing initiatives is limited to providing data, being interviewed and validating results. When it comes to pricing algorithms, the devil is often in details (assumptions, weights, etc.). Ideally, these experts should have direct input on these important details. If there are frequent price complaints in specific business areas, algorithmic risk may be reduced by following Deloitte’s advice: Conduct a review of the relevant pricing algorithms, including the minutiae about weights, assumptions, etc., and do this in a meaningful way, with the involvement of relevant market experts.

Unfortunately, the pricing algorithms are kept in a “black box” in some popular pricing software packages. This can make it impossible for distributors to independently review these algorithms.

When distributors raise potential issues with their algorithms, some pricing software vendors reportedly push back on change requests – particularly if the type of change would go beyond simpler tweaks or adjustment. These kinds of issues have led several large distributors to discontinue pricing software contracts with “black box vendors,” at times before prices ever hit the market.

These solutions are potentially quite powerful. However, Nyari warns, distributors should not view them as “bulletproof” price optimization tools, and their use does not mean that algorithmic risk is minimized in the businesses.

Read the rest of Nyari’s breakdown of algorithmic risk management here. And learn more about pricing algorithms this April at MDM’s Pricing & Profitability Summit.

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