Within the first article of the series, we discussed how important the information is that you collect and how to best begin using it (See Article One of "How to ensure You're Obtaining the Very Most Out of your Prescription data)

In part two we likely to drill to your data and see what we will find....

How do you identify the most effective targets?

Script history can also help your organization identify targets. Often, smaller pharmas will contract with 3rd party sources to get this done. Generally, these sources will request just one cut of IMS data to help identify targets, and they will massage the information to generate a target list and perhaps territory alignments. Why don't you put this single cut to make use of?

Particularly with startups, this cut could be a baseline to compare against, perhaps Six months or a year later, to find out bonuses for the reps. This data can also be used to tweak territory alignments and targets long afterwards the 3rd party is finished using their work.

During target identification, it's important to know who the "early adopters" are when bringing out a brand new drug, especially for an inferior pharma company. This data, particularly with 2 years of history, allows for analysis to see which doctors are "quick to switch" to new drugs because they come out, or which of them keep to the "tried and true". You don't need to heavily target the "tried and true" until later inside your campaign rolling out a brand new drug.

Using the appropriate analysis tools in place, pharmas be capable of quickly change territory alignments, product market definition and campaigns. To remain competitive in this ever changing market it is imperative to eventually have the ability to reload fresh data monthly so you're able to identify trends quickly.

How do you determine the effectiveness of sampling and call frequency?

Another reason to combine and analyze information is to find out effectiveness of sampling and call frequency. Carefully crafted queries can show certain doctors receive way too many samples for the scripts they write. The same kinds of queries can correlate that particular doctors respond very well to frequent calls while others just don't need the attention they are driving their script writing.

How best to investigate all this data?

The key to successful analysis is building the proper data repository where any kind of prescription data mining associated with sales and marketing can be performed. In very large operations, often these power tools are built internally and managed by an interior Information Technology (IT) department. In this section, we'll go through a few ways to provide the analysis, whether done in-house or outsourced. Next, we'll take a look at why strong consideration should be given to outsourcing this data repository to a 3rd party.

For any tool to be successful, it has to deliver enough detail which means that your sales organization has enough information on each doctor they ask, but must also have the ability to roll up this information to the highest level. So, for targeting and actual calls, information must be easily available to the sales reps letting them know key information that can help them on their call, for example script background and some
automated trend analysis. But, for compensation, doctor detail might be an excessive amount of and instead a territory level detail report (a consolidation of doctor detail) is needed. In larger organizations, with several sales layers, additional "rollups" may be needed for districts, regions, and areas.

Finally, for every level, graphical "dashboards" are extremely useful to point out trends. Legitimate effectiveness, these graphs can then be "drilled upon", letting you see details, either graphical or tabular, that make up a high level graph.

Pharmas

This data must be "fresh", with monthly extractions from IMS or Verispan quickly integrated into the information repository. This is critical as the market is quickly changing, especially if you also analyze group plan track data.

Let's look at an example of how drill downs can easily lead to information. Suppose the national sales director looks at a drug's two year trend and sees moderate growth. By "drilling down", the manager sees that the drug's growth curve vary dramatically by district. By drilling down further, the manager could see that particular territories may be outperforming others. By focusing on many places and looking at plan data, a manager often see that perhaps a certain group of plans is
lagging behind others. The audience Plan Manager could then become involved and perhaps new incentives to groups that specialize in certain territories could help repair the problem.

But there are many different ways to help analyze the data to determine trends. One is the ability for the tool to "group" doctors in small customized entities and analyze the trends.

Supplements

For instance, if your company support speaker's bureaus, then it may be good to determine how effective they are. Patient registry participation may be integrated with the oral appliance analysis/focus be share with those doctors within the registry. As guidelines tighten as far as what pharma's can do with doctors (and the current political weather conditions are for additional stringent and possibly government oversight), analysis of data that relates to adjunct activity becomes a lot more important.

Finally, a proper analysis tool helps bring together data which may be disparate and controlled by various people within the organization. For example, in a single organization we serve, one person controls the spreadsheets which contain data concerning the sales roster. Someone else (or 3rd party) controls the data relating to territory alignments (usually by zip code).

Perhaps even another looks at targeting and call frequency data. It is easy to observe that all this data correlates but could easily get free from sync if a centralized system for management is not used. We find that organizations that consolidate these details (so far as data) cash more accuracy in most data involved.

Adding even more complication to some quickly changing environment, turnover becomes a problem when key sales ops staff move from one drug company to another. If the effective system is in place business rules are loaded and also the tribal knowledge issue is minimized.