How to Create Budget Allocations that Allow You to Compete Effectively

Different companies, and countries, use various approaches for budget allocation.

These range from the ‘very basic’ (i.e. crossing fingers and hoping/making a judgment call/response tracking), to ‘interesting but not that useful in dynamic environments like Pharma’ (i.e. response curve analysis and econometrics), to ‘the most sophisticated with proven results in Pharma’ that take the current market into account and run complex algorithms on their data to determine financial results based on the market and all brands strengths and vulnerabilities (i.e. Eularis’ Growth Accelerator Program market data-based analytics).


Budget Allocation

Interestingly, we have noticed in China and a few other markets that, until we get involved, many companies are in the ‘very basic’ category of budget allocation. In fact, in China, what was most shocking to me was that most companies went even further and did not even know where or how their money was being spent as they simply give money to the hospitals and allow them to spend it as they see fit.

The companies themselves have no way of knowing or tracking what their money was spent on at all, nor what results were gained! For companies relying on growing their sales and profit, simply adding rigor and analytics to the process will result in significantly improved results for the company.

The good news is that in the last two decades, we have had a revolution in measurement, allowing companies to understand in much more detail what their customers perceive and believe as well as what their sales / marketing activities are doing, and what their company strategies are achieving. That improvement in measurement is creating new opportunities to manage things differently. Finally we are seeing a shift from using intuition and gut feel toward using data and analytics in making decisions. This shift has gone side by side with measurable improvement in productivity and other results measures.

Using Data

A study conducted in 2011 demonstrated that by simply increasing use of data and analytics by a small amount, a significant improvement in productivity and an even larger increase in profitability were obtained. The implication for Pharmaceutical executives is that by changing the way they make decisions, they’re far better equipped to be able to outperform their previous results, and their competitors’ results.

What is required to do this, of course, is both the ability to measure and the ability to take those measurements and turn them into something meaningful that will impact results…and also basically to get the team to use the results. Sometimes, if we have a client who is doing very well (e.g. they have a top performing brand), they tend to use the data to support and back up what they are doing, when really what they should be doing is taking the few things that the data is showing them they should change and making the changes.

There needs to be a cultural change in some companies so that the thinking is “Here is our problem, let’s use analytics to solve it.” The data being measured needs to consist of both non-financial and financial aspects. The financial side is the result of what you are doing in the non-financial side and all sides must be measured.

It can sometimes be frustrating when you come across managers who say, “I have the experience and I manage from the gut”, and do not wish to examine the opportunity for improved results big data can provide; instead they should be leaving their egos at the door and have the confidence to let the data speak.

One client CEO pushed this attitude to his reluctant sales and marketing managers and fought hard for the changes, which was not easy for him. However, the results were worth it. All brands grew dramatically and even the marketing managers, who were against it in the beginning, became raving fans after the first results were seen. But it is not always an easy process.

So, What is the Process?
    1.    Define the objectives for your analytics, and specify the end financial results required
    2.    Determine what data is needed to solve this
    3.    Collect the data
    4.    Analyze the data and model everything, including optimal budget allocations, to achieve your target revenue and profit
    5.    Review the results and decide on key actions and timelines
    6.    Assign responsibility

Eularis’ Growth Accelerator Program Analytics budget allocation model takes all the data into account as well as strategic importance, stage of lifecycle, whether brands are supporting other brands or are follow on brands, competitor brands, and much more. The factors any competent manager would consider are now all neatly incorporated into the budget allocation algorithms to ensure maximum real world results.