Are you part of the New Generation of Pricing Leaders?

- Bringing your pricing performance to a higher level - 

The European Pricing Platform unveiled their cutting-edge pricing accreditation program for the new generation of pricing leaders and specialists this week in Brussels. The Certified Pricing Manager (CPM®) Program offers experienced pricing practitioners the unique opportunity to learn how to achieve full value capturing and profit optimization in their companies.

Becoming a Certified Pricing Manager

“Pricing Power is one of the key value drivers on the stock exchange today. We hear more and more European companies express the need to equip their pricing managers with the latest tools, knowledge and capabilities, to bring their pricing performance to a higher level”, says Pol Vanaerde, Founder and President of the EPP. The CPM® immerses participants in a 3-day and 2-evenings blend of intensive knowledge transfer, interactive discussions, reflection and group work followed by a 6-month in-company profit optimization project, which needs to be successfully completed in order to achieve certification.

Two levels of certification

Two levels of certification, CPM®2 and CPM®3 are offered depending on where an organization finds itself on the path to pricing maturity and on how much experience the pricing practitioner in question has in the field. The modules of the CPM® Program are underpinned by skill cards covering the knowledge and capabilities required by pricing practitioners at each pricing maturity level.  

Higher pricing maturity leads to sustainable value capturing, which in turn results in profit optimization based on fair pricing and value sharing principles. For more information on the program visit

The EPP CPM® program is about meaningful learning and tangible professional development with impact.

The new generation of pricing leaders:

CPM® Level 2 :  Welcome Dinner on 1 July, Training 2-4 July, Brussels 

Pricing leaders on CPM® Level 2 are skilled in Taking Transactional Control.  They have mastered these key requirements needed for successfully completing a 30.000 Euro (minimum) margin improvement project in their companies in order to be certified as CPM2. 

1.  Pricing Maturity Management 
  • Alignment between profit optimization goals and organizational capabilities.    
  • What moving to the next Pricing Maturity level means.
  • Pricing maturity challenges for your organization.
2.  Pricing Analytics, taking control
  • How to gain transactional control.   
  • How to install the right price analytical reports
  • How to set-up a holistic view on profitability.
3.  Defining margin improvement projects

  • Pricing tools which help discover the margin leakages.
  • How to communicate that change is needed.
  • How to ensure that structural improvements are realized.
4.  Price Setting and Discount Structures

  • Different price and discount models.  
  • Price and product differentiation opportunities  to improve margins.
  • How to install floor prices and  price corridors.  
5.  Preparing price increases

  • How to effectively prepare  for and execute price increases.
  • How to monitor the effects of price increase projects.
6.  Pricing organization & Governance

  • The organizational impact of moving towards pricing maturity level 2.
  • The impact on governance, pricing roles, responsibilities  and skills.

CPM® Level 3 :  Welcome Dinner on 15 July, Training 16-18 July, Brussels

Pricing leaders on CPM® Level 3 have moved beyond transactional control and are now focussing on full value capturing.  The have mastered the change management and advanced pricing skills needed to bring their organisation to the next level.  The focus of key topics covered in this programme are:

1.  Pricing Maturity Management
  • How to cross the Pricing Chasm
  • What moving to the next Pricing Maturity level means
  • Pricing maturity challenges for your organization.
2.  Value Based Pricing Techniques
  • Segmentation based on value attributes.
  • Typical issues in setting up demand curves.
  • In-depth view of the research tools (conjoint techniques).
3.  Value Selling and Understanding Situational WTP
  • What it takes to move from selling products to selling on value.
  • What tools to set up to help your Sales Team sell on value.
4.  Calculating TVO
  • How to prove your value in hard economic terms.
  • How to develop and use the right tools for TVO calculations.
5.  Multi Channel Pricing and Discount Policy
  • Challenges of managing channel incentives.
  • Setting up a performance based discount policy, without putting pressure on margins or triggering channel conflicts.
6.  Price Negotiations
  • How to avoid focussing on price during negotiations.
  • How to deal with price issues during negotiations.
  • How to prepare your Sales Team to defend your prices.
7.  Pricing organization & Governance
  • The organizational impact of moving towards pricing maturity level 3.
  • The impact on the governance, pricing roles, responsibilities  and skills.
8.  The Pricing Dashboard
  • Which strategic and operational KPI’s to monitor.
  • How to set them up.


How mature is your pricing organization ?

Many European based organizations have only just begun to realize how significant the effect of pricing on shareholder value creation really is. Until now, the focus was mainly on innovation, sales and marketing – and justly so. But in today’s economic environment, value capturing (effective pricing) is increasingly being discussed at the boardroom table as one of the main shareholder value drivers.

The domain of ‘Pricing’ is in full development and many companies install Pricing teams who almost immediately realize successful margin improvement projects. These are the ‘quick wins’ in the discipline of pricing. But we need to go beyond the low-hanging fruit !

The next step proves to be more difficult : embedding pricing knowledge in the organization, thus moving away from pure project-driven pricing. European pricing professionals have come to recognise that a lasting change and full impact on profit optimization requires a comprehensive approach. Crossing this chasm is not an easy expedition.

As a result, many pricing practitioners, management teams and CEO’s are searching for a structured approach to guide their organizations towards higher pricing maturity, leading to profit optimization.
They asked the EPP : where do we start and what are the priorities? Who should we learn from? Apple? Bose? 3M? Bayer? Audi? Microsoft? Michelin? Hilti? The Rolling Stones? Is there a proven path to superior pricing ?

The answer is Yes ! There is a proven pricing maturity development path.

The maturity model concept, as a tool to enhance organizational capabilities, was popularised by the Carnegie Mellon University in the 90’s. Their first Capability Maturity Model (CMM) was developed for IT management, but in the meantime, nearly every management domain has maturity models to draw upon. A maturity model defines a set of structured levels that describe how well the behaviors, practices and processes of an organization can reliably and sustainably produce required outcomes[i].

At the EPP, we have gathered a treasure of time-tested best practices from the leaders in the field of pricing to come to a practical pricing maturity model to support pricing practitioners in Europe. It’s a hands-on, pragmatic instrument and it is our mission to share it with you.

The emphasis of this white paper is to help you identify where you are today in your pricing journey, which areas you need to prioritize and improve to lead your company to the next level of pricing maturity (and profit optimization) – and perhaps most important : how to cross the ‘Pricing Chasm’.

In addition to this, we are currently building the EPP Pricing Maturity Indicator together with PROS (to be launched in October 2012).  It takes the form of a free, in-depth, on-line survey.  The results of the survey present you with a solid indication of your pricing maturity.  For a customized, company-and-industry-specific assessment, we refer you to one of our expert partnersii.

The Pricing Maturity Approach

In the early stages of their pricing development, organizations often focus first on margin improvement projects. These pricing projects (the low-hanging fruits : see frame) bring the desired visibility at board level, but pricing professionals soon grasp that full value capturing is much more complex and challenging.

Improvements do not come from better price setting alone. You have to develop and align your capabilities in all pricing building blocks.

We visualise this by means of the EPP Pricing Framework. There are five core processes : Price strategy, Price Policy & Setting, Discount Policy, Execution and Monitoring – and two supporting building blocks : Organization & Governance and Tools & Systems.

When you have a pricing audit done, they always reveal weaknesses/improvement opportunities in all building blocks. This results in a long list of capability gaps and organizational challenges. As a result, we see top management often struggle to allocate the right priorities in this list.

How do we set priorities for Pricing ?

The EPP Pricing Maturity Model helps you determine which level you are operating on, how to prioritize your efforts, and how to cross the pricing chasm to realize profit optimization.

We consolidated real-life best practices and advice from Pricing leaders, experienced in pricing maturity development across all industries, into the EPP Pricing Maturity Model.

The model consists of 4 stages described in detail in our whitepaper:

Level 1: Price list maintenance

Level 2: Gaining transactional control
Level 3: Achieving full value capturing
Level 4: Deploying full profit optimization

Under optimal conditions, it will take you at least 3 to 4 years to bring your organization from level 1 to level 3. It is essential that you have the full cooperation and support of your most important stakeholders in realizing the change: top-management, marketing, sales, finance (and IT). Do the right things first and never walk alone; if you keep these two key things in mind, the likelihood of success in your pricing journey increases sevenfold!

 A selection of pricing maturity characteristics to help you determine where you are, and where you need to go :

Download the whitepaper for a full account - click here

1.  Price List Maintenance :

Driven by volume, you sell to (almost) everyone at (almost) any price (Discounts galore!).  Wide price bands likely to lead to pricing conflicts, which sees you spending most of your time managing price lists.  Mainly cost-plus pricing.

2.  Transactional Control :  
You realize that strategic importance of pricing needs to be made clear to the powers-that-be.  A number of successful quick win pricing projects lead you on the way to transactional control.  But the challenge here is to bring management to understand pricing is a continuous process, not just a once off project.  This is the Pricing Chasm that needs to be crossed to get to the next stage of pricing maturity. 

3.  Full Value Capturing :  

You have the full support of top management and they are prepared to make some serious changes.  The chasm is crossed or in the process of being crossed. There is alignment between Sales, Pricing, Marketing and Finance about where and how value is created and which market strategy you follow.  Wherever possible value-based pricing in place.  Pricing software is implemented.

4.  Full Profit Optimization :  

You have tailored value communication per end-user to help them identify optimal solutions.  You no longer sell on features, price or even on value components, you sell solutions ! Think of Michelin who bill their trucking or airline customers according to the nr of kilometers traveled, nr of tonnes transported etc using their well-serviced tires... Your centralized pricing team supports and influences  the whole business model, and reports directly to the CEO.

Take the time to download the full whitepaper here : a couple of seconds now, could result in a lasting impact on your bottom line !

i) For the history and evolution of the Capability Maturity Model by the Carnegie Mellon University, see http://www.sei.cmu.edu/cmmi/ . The description of a maturity model comes from http://en.wikipedia.org/wiki/Capability_Maturity_Model
ii) visit http://www.pricingplatform.eu/partnerzone/pricingexperts/pricingexpertdirectory.html for a list of the EPP expert pricing partners.


Meet the crunch bunch - The effectiveness of data


September 2012

Data can unlock your company's potential - but only if you know how to use it. Here are the people who do
By Stephen Pritchard
Despite being intangible, and often invisible, business data is increasingly referred to as 'the new oil'.
One of the first companies to appreciate its value was Tesco, which has been tracking the shopping habits of more than 15 million British families for almost two decades thanks to its innovative loyalty card scheme. Launched in 1995, the Clubcard helped Tesco catapult past Sainsbury's to become the UK's biggest supermarket chain and the third-largest retailer in the world.
Today there is hardly a businesses sector on the planet that does not mine data in the hope of unlocking new revenues. Facebook's valuation, when it listed, was largely down to the mass of data it collects from its users.
But simply gathering and storing endless information does little to help a business: in fact, it will just add to its IT costs. A US study by business software company Oracle found that managers felt they were being deluged by it. The average data volume they are handling has increased by 86% in just two years.
As well as facing rising costs from managing more data, businesses are also failing to make proper use of it. As Peter Sondergaard, head of research at analysts Gartner, puts it: "Information is the oil of the 21st century; analytics is the combustion engine."
In other words, the real value of business information comes not from collecting or storing it, but from the tools that enable businesses to examine their data and look for trends. They can then use this to come up with new ideas or develop new products.
But only a few companies are doing that today. Gartner, for example, says that 85% of business information is so- called unstructured data, including text, video and audio. Only one company in 10, however, has a formal role in the business for someone to manage that data and put it to work.
This comes with a cost. Again, according to Oracle's survey, private-sector companies believe they are losing 13% of potential revenues by failing to make the most of the information explosion. And this is in part because most things to do with data are still cloaked in geek-speak.
This, says Lora Cecere, CEO of industry researchers Supply Chain Insights, is a hurdle when it comes to turning data into profit. As a respondent to one of her surveys pointed out recently: "Most business people do not understand this, it is still IT-speak for now." But it is not a trend that companies can afford to ignore.
"What is driving change is the availability of a lot of data," says Andy Fano, who leads the data scientist team within the analytics practice at Accenture, the consulting firm. "There are technologies available that make processing those data possible. But what it is about is understanding the signals that are present in the data. And that is not just traditional data, coming from transactions, but information from sensors, from social media, or unstructured information such as text, images, audio and video."
Tesco doesn't just use its Clubcard to see who is buying a particular brand of toothpaste. It has used the data it collects to develop an entirely new raft of businesses, such as financial services.
There are many other examples of data being used to hone businesses. Virgin Atlantic has used data gathered from years of flying passengers to the US to change the timings of some of its less busy flights, making them more convenient for travellers with onward connections. This has transformed some of its less popular routes into some of its best revenue earners.
Other technology is even more advanced. Accenture, for instance, has used cameras in supermarkets to help retailers better understand where to place goods on the shelves. Yet the quest for information is hardly over. "In retail, if you look at transactions over the last 10 years, it feels like you have a lot of data," says Accenture's Fano. But when it comes to predicting what, say, an individual shopper might do, there is no such thing as too much data.
"If a customer visits a department store six times in 10 years, and visits the menswear department, all the information you might have could be that they bought an item at this price. If you're lucky, you would know it was a shirt." That information on its own says little about that customer, or his or her spending patterns or desires. "That is where the volume of data is deceptive," warns Fano.
All told, experts who can crunch the numbers, unlock the secrets of companies' vast databases and explain the data's meaning to senior managers are highly prized.
And helping managers make sense of data is a lucrative business. By no means all the companies mining and analysing data are new: some have done so, out of the limelight, for years. If data is indeed the new oil, here are some of the explorers.

Andres Reiner

New York-listed software company PROS specialises in price optimisation. It started in the airline business more than 30 years ago, but has since moved into areas such as hotels, business-to-business services and retailing: anywhere where goods or services are perishable or have a fixed shelf life. Andres Reiner, its CEO, says businesses often have plenty of data, but struggle to translate that into improved profitability.
"Companies have invested a lot in data and creating ERP (enterprise resource planning) and CRM (customer-relationship management) solutions to leverage that data," he says. "Technology allows them to use transactional data with other external sources to drive their strategy. But a lot of companies have lost their ability to understand how raw-material price changes or currency fluctuations impact their business. They need better tools to guide them on where and when to make changes."
Companies should be looking for patterns in the numbers: changes in the market that might affect pricing. But this means more than just looking at their own sales or reservations systems - they must look at competitor data too. And they need to do more to bring marketing and sales, and purchasing, together. "We're trying to bring them the data they need to make the right decisions," he says.
Sometimes, looking at the data produces startling results. One firm found that the difference between the highest and lowest prices paid for its products was 70%. And sales teams do not always tie pricing to profitability. "How do you ensure a customer who is driving more business for you pays a better price than one who drives less business?" asks Reiner. "When any sales rep can change a price, you may be setting a price that means you are losing money on that business - but you will never know. Businesses must leverage the technology they have to understand how the market is changing and how their costs are changing, so they can make real-time decisions on where you need to price to win business profitably."
Industrial customers, which have traditionally updated price lists once a year, if that, are being hit hard by more volatile raw-material pricing.
They could, Reiner suggests, learn from FMCG retailers or airlines and price more dynamically. "The consumer markets are much more advanced when it comes to using this data, because they've needed to be. Business-to-business companies may not always have seen the volatility we've seen over the last few years." Regular, small price increases might be better for both a business and its customers, as it is easier to absorb the costs. "Understanding how your profitability changes over time is very important," says Reiner. "And businesses need to be more surgical: you are not changing all of your price lists, but changing them where it matters."

Jim Goodnight

SAS Institute
Dr Jim Goodnight co-founded data analytics firm SAS Institute in 1976.
Still privately held, the company ranks governments, global banks and big-name retailers among its customers.
For three decades, analytics remained a largely specialist branch of IT, used in areas such as banking or intelligence analysis. But that has changed. "Execs realise that analytics can be a key factor in improving their bottom line," says Goodnight.
"A bank needs to make decisions on who to lend money to. By building predictive models, we can compute the probability that someone will repay their loan. With that information, the bank can decide whether it is worth taking the risk or not. We score credit card usage, so when you use a credit card we are at the other end working out whether the card is being used fraudulently.
"We've been in the high-end analytical space for 35 years. But more and more companies are using analytics, and we are helping to create new solutions for companies that maybe don't have the analytical talent themselves - we will host the data and do the work." HSBC is one such customer: SAS Institute develops algorithms for the bank to use in its analytics.
The current trend for businesses to use 'big data' is not, though, a guarantee of improved profits. "Often the problem is not so much the analytics but getting it all together and getting the data cleaned up," he says. "There are always bugs in data: someone has put down an address incorrectly or misspelled a name. But with high-performance analytics, once the data is cleaned up, we can compute models in a matter of minutes and address huge problems we would not have been able to dream of solving just a few years ago."
Demands such as credit card processing have prompted SAS Institute to focus on performance: the smartest algorithms are of no use if a shop customer has to wait several minutes for approval. Those lessons, Goodnight says, are now being applied to other businesses.
"We have been successful at uncovering really fast ways to do things," he adds, explaining that this in turn allows the software to run on more modest equipment. As a result, a wider range of companies can use the service.
"Retail is one of the last spaces to turn to analytics in a big way," he says. "We are working with [US department-store chain] Macy's to forecast the shelf life of each item in their stores - if it looks like it will be on the shelf for more than a season, we will suggest markdowns. We do that for 270 million items each Monday morning."

Gordon Rugg

Search Visualizer
Academic Dr Gordon Rugg - a psychologist and computer-science lecturer at the UK's Keele University, set up Search Visualizer to help researchers and businesses make sense of large amounts of information. This might be results from a search engine, where the problem is sifting through thousands of hits, or looking for specific terms within a document. In layman's terms, it is helping to look for needles in a haystack of data.
"Most people tackle big data with one of two approaches. One is to make software replicate how humans operate - the 'semantic web' approach. The other is to do what humans are bad at: statistical cluster analysis," says Rugg.
"The problem with the semantic approach is that the hardware isn't yet up to it. Nor is the software. What we are doing is representing data in a way that plays to the strength of the human mind's ability to process it: making sense of huge amounts of natural language text but also quantitative information."
The technology works by turning data into a pattern of coloured dots. The company says it can search through an entire Shakespeare play, and put the results for just a single word on one page. But there is a more business-focused application.
"The companies we are talking to are drowning in data. They want to make sense of it. One customer is looking at patent searches, and searching for patents in languages they don't speak. The current technology is too slow. But we can identify which records are likely to be relevant and draw up a shortlist of documents to be translated."
Another application is monitoring social media for comments. "Say you want to know what's being said about a company. You don't need a lot of training to do that, and you can scroll through hundreds of records in a few minutes to get a general feeling for whether sentiment is positive or negative. Then you can drill down into what people are saying - the words that they are using - whilst you are at your desk. You just reframe the question with a greater degree of precision.
"When we show it to people their eyes widen. Within minutes they can be up and running and using it at a 'power user' level. There is a lot you can do with this that you can't do with conventional search technology: you can see a large amount of information at a glance. We see this being used by medium to large, nimble companies, that are small enough to react quickly and flexible enough to adopt new ideas."

Neil Thomson

Dr Neil Thomson carried out academic research on memory and reasoning at Cambridge before moving into information technology.
He founded his own company, developing business-rules software, which he sold to Microgen. There, he built the firm's Aptitude technology, which deals with large volumes of business data.
Businesses cannot derive insights from data if they cannot process it in a joined-up manner, he says. "In classical statistics, you are not just looking randomly for patterns. It is always going to be difficult to look through large amounts of data without an a-priori hypothesis."
The challenge is to design a system that is efficient, and fast enough to cope with huge volumes of data, but which is simple enough to be configured by business users, not IT people or specialist analysts.
"I can write something that goes fast in a low-level language, but that doesn't correspond to any business language," says Thomson. "We try to create something people can use that isn't opaque code."
The Aptitude software aims to help companies make more of their data by being as intuitive as possible but still powerful. The idea is that by making data analytics more accessible, companies can run more searches and queries, and make better use of the information they hold. After all, data, Thomson concedes, is worth little on its own.
"More data doesn't necessarily lead to better decisions," he says. "Ideas come from creativity; data lets you check those ideas. If you look at most standard business processes, 'big data' is simply more data." And ever-larger databases aren't the answer. "The issue is not having the data, it's having the questions. Business users need to be able to ask the right questions."