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Price Optimisation: How Big Data Can Help You Get Your ‘Pricing Mojo’

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Pricing is one of the biggest challenges that sales and marketing professionals have to face. It’s more than the Recommended Retail Price that you see on a label – companies can have hundreds to thousands of SKUs (stock keeping units) to manage across multiple markets. The complexity that exists around pricing makes it a difficult subject to broach.

Yet it is one of the most powerful tools that businesses can use to improve their growth. According to Christopher Fletcher, research analyst at Gartner, a successful price optimisation and management (PO&M) implementation can increase margins by 50 basis points or more, and increase a company’s revenues by 2% to 4%.

The 2013 Gartner MarketScope for this sector points out that “price optimisation has shown steady growth during the past two to three years and has found its way onto the CXO’s agenda, aligning closely with executive priorities of revenue generation, customer acquisition and profit/margin improvement.”

Getting started with Big Data

Bringing data and analytics into the sales process is a topic for the CEO, according to Sebastian Mamro of Big Data software company PROS: “Ask any CEO and their number one priority will be growth. Ask them how they will achieve this, and then it becomes much more complicated. Many of the CEOs I speak with have found they can’t cut costs any further as it will have a potential impact on their ability to compete, so they are hungry to look at alternatives. Pricing and sales effectiveness is a topic that gets their interest when they hear about the potential revenue improvements, but they also recognise that this is not a short-term effort. Data plays a critical role here.”

So how can companies start rethinking their data strategies? Peter Ostrow, analyst at Aberdeen Research puts it this way: “Our Big Data research shows an increasing number of technology and line-of-business professionals acknowledging the need to address the virtual fire hose of incoming customer data. Most of them, though, are still in search of the best tools to get their arms around the vast opportunities.”

For companies that are taking their first steps in Big Data, looking at sales performance can be a good starting point as it focuses on answering particular questions. Ostrow continues: “With an enhanced ability to know which deals are likely to close and at what gross and net price points represent the ideal spot between the needs of buyer and seller, companies now have the opportunity to create opportunities, up-sell, and cross-sell more efficiently than ever before.”

Mamro seconds this view point, but also points to how sales, marketing and finance professionals will all be involved in setting out how new pricing strategies are put into practice: “Pricing and sales effectiveness is a cross-business challenge – it can be everybody’s responsibility and no-one’s. In these situations, it’s best to go back to the data that you have already to help support decision-making. This helps get everyone on the same page, and it also makes it easier for everyone to agree on next steps. Big data can provide great ammunition for the CEO around the strategy for the future, but it should also filter down to the sales professionals who are in front of customers every day.”

What does this look like in practice?

U.S.-based medical manufacturer DePuy Spine is an example of how to look at sales, pricing and Big Data. Prior to the financial crash in 2008, DePuy would see annual 5% or 6% price increases for its products as standard. This was similar to the rest of the medical manufacturing sector.

While the changes in the world financial markets did not stop demand for DePuy products, they did have a big impact on how willing those customers were to buy. According to an interview conducted by Ostrow, DePuy worldwide director of pricing David Mok commented, “Since we traditionally sold to the physicians and clinicians, we were not as well prepared as we would like, when faced with the more confrontational approaches used by supply chain and materials management departments.” This led to significant erosion in the company’s revenue and profit because pricing was never a core focus until 2011, when he was the first pricing professional to join DePuy Spine.

Working with the company’s finance director, Mok led the roll out of a data analytics strategy at the company. This included tackling the challenges of pricing discipline and re-educating the sales team on how to sell in the new market environment.

Mok explained this further: “In terms of our pricing approach, we addressed it holistically. We started by defining what our pricing priorities were, and then created a strategy with supporting rules and policies. Finally, we gained alignment with all the key stakeholders. This gave us the ‘pricing mojo’ needed to enable proper control of price management, including the confidence to make the right calls — be it an approval, counter, or flat-out denying a price request.”

The company is now using its data analytics as part of all its customer engagements, including using market data to protect pricing and maintain margin, even in competitive situations.

Making the first step

Sales and pricing strategies are long-term decisions. So what are the future steps that a company can take around applying data analytics to these areas?

From a deployment point of view, Mok notes that this is not something that can be achieved solely with technology. From his experience, a blend is required: “The best strategy in the world without the right tool won’t go as far as it can, and neither will the best tool in the world without the right strategy. They compliment each other.”

Mamro follows up on this: “Big Data has the potential to be transformational for a business. Look at a small project where the results can be delivered, and then extend the approach to other product lines or business units. Companies already hold most of the information they need to get started; it is mainly a question of desire to get there.”

DePuy Spine shared its pricing success story at OUTPERFORM 2013. Learn how companies including Arrow, Celanese, Gates, HP are able to turn their pricing and sales challenges into success stories at OUTPERFORM 2014. Click here for more details about the event, and register to join a best-in-class group of thought leaders, seasoned practitioners and industry experts to learn how to outperform your competition using big data.

A version of this article was originally published on MyCustomer.com. Click here to view.

Post written by Ed Farquhar


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