How to Make Sure You're Getting the Most Out of Your Critical Prescription Data In the first article of the series, we discussed how important the information is that you collect and the way to best start using it (See Article Among "How to ensure You're Obtaining the Most From Your Prescription data)
In part two we likely to drill to your data and find out what we can find....
How can you identify the very best targets?
Script history can also help your business identify targets. Often, smaller pharmas will contract with third party sources to get this done. Generally, these sources will request a single cut of IMS data to assist identify targets, and they'll massage the information to generate a target list and perhaps territory alignments. Why not put this single cut to use?
Particularly with startups, this cut can be a baseline to compare against, perhaps Six months or perhaps a year later, to find out bonuses for the reps. This data may also be used to tweak territory alignments and targets long after the third party is completed with their work.
During target identification, it's vital that you know who the "early adopters" are when bringing out a brand new drug, specifically for an inferior pharma company. This data, especially with 2 many years of history, allows for analysis to see which doctors are "quick to switch" to new drugs because they emerge, or which ones stick to the "tried and true". No need to heavily concentrate on the "tried and true" until later in your campaign rolling out a new drug.
Using the appropriate analysis tools in place, pharmas be capable of quickly change territory alignments, product market definition and campaigns. To stay competitive within this ever changing sell it off is important to eventually be capable of reload fresh data monthly so you can identify trends quickly.
How can you determine the effectiveness of sampling and call frequency?
Another reason to mix and analyze information is to find out effectiveness of sampling and call frequency. Carefully crafted queries can show certain doctors receive too many samples for the scripts they write. The same types of queries can correlate that particular doctors respond perfectly to frequent calls while others just don't need the attention they are driving their script writing.
Just how to investigate all this data?
The important thing to successful analysis is building the proper data repository where any kind of prescription data mining associated with sales and marketing can be carried out. In large operations, often these power tools are made internally and managed by an interior Information Technology (IT) department. Within this section, we'll discuss a few methods to provide the analysis, whether done in-house or outsourced. Next, we'll check out why strong consideration ought to be provided to outsourcing this data repository to some third party.
For any tool to achieve success, it must deliver enough detail so that your sales organization has enough info on each doctor they call on, but must also have the ability to roll up these details to the highest level. So, for targeting and actual calls, information should be easily available towards the sales reps allowing them to know key information that can help them on their own call, for example script history and some
automated trend analysis. But, for compensation, doctor detail might be too much 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 each level, graphical "dashboards" are extremely useful to point out trends. For real effectiveness, these graphs can then be "drilled upon", letting you see details, either graphical or tabular, that comprise a high level graph.
PharmasThis data needs to be "fresh", with monthly extractions from IMS or Verispan quickly integrated into the data repository. This is critical because the market is quickly changing, especially if you also analyze group plan track data.
Let's consider a good example of how drill downs can easily lead to information. Imagine that the national sales director looks at a drug's 2 year trend and sees moderate growth. By "drilling down", the manager understands that the drug's growth curve vary dramatically by district. By drilling down further, the manager often see that particular territories may be outperforming others. By focusing on certain areas and searching at plan data, a manager could see that perhaps a certain number of plans is
lagging behind others. The Group Plan Manager could then get involved and maybe new incentives to groups that specialize in certain territories could help fix the problem.
But there are many different ways to assist analyze the data to see trends. The first is the power for that tool to "group" doctors in small customized entities and analyze the trends.
SupplementsFor instance, in case your company support speaker's bureaus, it may be good to see how effective they are. Patient registry participation may be integrated with the tool and analysis/focus be share with those doctors in the registry. As guidelines tighten so far as what pharma's can perform with doctors (and also the current political weather conditions are for additional stringent and possibly government oversight), analysis of information that pertains to adjunct activity becomes a lot more important.
Finally, an effective analysis tool helps gather data that may be disparate and controlled by various people inside the organization. For example, in one organization we serve, one individual controls the spreadsheets which contain data relating to the sales roster. Another person (or third party) controls the data relating to territory alignments (usually by zip code).
Perhaps even another examines targeting and call frequency data. It is easy to observe that all this data correlates but could easily get out of 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 all data involved.
Adding even more complication to a quickly changing environment, turnover becomes a problem when key sales ops staff move from one drug company to another. If an effective product is in place business rules are loaded and the tribal knowledge issue is minimized.