Why do pharma companies need to tweak data integration?

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Why do pharma companies need to tweak data integration?
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Do you remember the times when the world was not a global village? Some of you probably still do, but the thing is that these are times long past. Companies now compete in many markets all over the world and are on constant standby seeking new opportunities to strengthen their position. We are all now watching them turn towards the digital transformation as a path that, through deep changes in the interior of the company, opens new possibilities.

Building competitiveness by optimizing processes, increasing efficiency, and making decisions based on data obviously makes sense, and is a global trend. But let’s not forget about the good old price competition, and with it — tool sets necessary to carry out pricing policies effectively in globally competitive markets.
I have 15 years of experience of cooperating with big pharma players (I probably shouldn’t give their names here, but I’m sure you would recognize the brands) and building IT systems to support their operations.
Complicated beasts they are, conservative and demanding. And they have mastered the art of designing pricing policies that build strong relations with their clients (pharmaceutical wholesalers, hospitals or pharmacies). But there’s a problem that they have to solve: lack of flexible and well supported tools that let them carry out the policies effectively.

Growing sales = new challenges

Sales is primarily relationships and as such, this area deserves careful care. With high sales volumes and large numbers of customers, traditional solutions for keeping tabs on everything are just not enough. The more you sell, the more complicated it gets. And pharma businesses sell a lot, as you can imagine.
Drug manufacturers sell their products to pharmaceutical wholesalers or directly to pharmacies and hospitals. Animal Health corporations sell to producers, farms, or straight to small animal clinics round the corner in your neighborhood. Just to show you the scale: one of our clients (Animal Health industry) offers hundreds of products to over 10k indirect customers through distributors. Their rebate calculation is based on sales data: upwards of 10k customers, over 2 million Euro payments monthly, with the need to take into account the growing importance of purchasing groups.

Companies use complex rebate policies to gain and retain their customers. In this world pricing REALLY IS like rocket science, as prices usually depend not only on quantities of products sold, but on turnover, contract settlements and billings frequency, order structure and purchase seasonality as well.
Pricing policy has to be flexible and creative to meet client needs, deal with seasonal variations and react quickly to competitors’ activity. And so have to be the tools to implement it.
But my experience is that in the pharma industry (and in animal pharma even more) traditionally, multi-level and complex algorithms for rebate calculation are managed in Excel spreadsheets. Is this really such a good idea, when you are selling hundreds of SKUs, process thousands of thousands of orders to process and generate billions of EUR/USD of revenue?

Everyone is doing it

Yes, CRMs, CLMs, pricing systems. In the Digital Economy and Society Index Report 2019 by the European Commission, “Customer Relationship Management” holds fourth position among processes digitalized by European businesses. MarketsandMarkets forecasts the loyalty management market to grow from USD 6.8 billion in 2019 to USD 10.9 billion by 2024, at CAGR of 10.1% during the forecast period.

It’s data, stupid

Using Excel spreadsheets as the basis of companies’ rebate policy, loyalty programs and sales monitoring may be OK on a small scale. With large-scale of operations and dispersed sales data sources, the integrity and quality of data may cause serious concerns. Payout errors caused by data irregularities, as well as the lack of efficient fraud detection can jeopardize the revenue. Without full control over the flow of money and settlements with contractors, companies cannot assess the amount of revenue lost. What’s more, sometimes they don’t even realize that these losses take place until they discover them during audit.


No matter how smart, insightful and awesome your pricing policy is. No matter how cool, innovative and technologically advanced your CLM or CRM system is. It’s always SISO.

Data integration should be the first step to feed your systems and let them work for you. The FMCG industry has done this homework. They often use SaaS-based platforms with data integration functionalities.
But pharma is still a little behind. Problems with effectively analyzing sales made by pharmaceutical wholesalers give room for errors, rebate policy abuse and outright fraud. In fact, it’s pharma clients I’ve worked with who asked me if there’s a way to verify the data provided by wholesalers and detect errors — both intentional and resulting from human error (of course there is a way, let’s get in touch if you want to know more).

Data integration is crucial. Feed your systems with top quality data — you will get top quality results. The tools to do that are there on the market, within your reach. The technologies behind are not revolutionary, but they are available in the SaaS model, require no IT intervention, and will provide your company with quick, automated and reliable way of maintaining tight control over the most important asset nowadays: data.

"No matter how smart, insightful and awesome your pricing policy is. No matter how cool, innovative and technologically advanced your CLM or CRM system is. It’s always SISO. Companies use complex rebate policies to gain and retain their customers. In this world pricing REALLY IS like rocket science, as prices usually depend not only on quantities of products sold, but on turnover, contract settlements and billings frequency, order structure and purchase seasonality as well. "

Michał Osuch Head of Data Management
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