We use cookies and other similar technologies (Cookies) to enhance your experience and to provide you with relevant content and ads. By using our website, you are agreeing to the use of Cookies. You can change your settings at any time. Cookie Policy.

The Benefits of Commercial Analytics for Pharma: A Q&A with Peter Harbin of IMS Health

Originally published May 14, 2012

BeyeNETWORK Spotlights focus on news, events and products in the business intelligence ecosystem that are poised to have a significant impact on the industry as a whole; on the enterprises that rely on business intelligence, analytics, performance management, data warehousing and/or data governance products to understand and act on the vital information that can be gleaned from their data; or on the providers of these mission-critical products.

Presented as Q&A-style articles, these interviews conducted by the BeyeNETWORK present the behind-the-scene view that you wonít read in press releases.

This BeyeNETWORK spotlight features Ron Powell's interview with Peter Harbin, senior principal at IMS Health. Peter and Ron discuss how pharma companies benefit from commercial analytics.

Peter, letís start this interview by having you give us a brief overview of IMS Health.

Peter Harbin: IMS is one of the largest information, services and technology providers in the life sciences industry. We began over 56 years ago by collecting pharmaceutical data Ė market level data, prescription information Ė† that is used by all pharma companies to drive their sales operations and their commercial operations processes. We have built a very significant business, with 7,800 employees globally. We also have a large consulting arm Ė approximately 1,600 consultants Ė and a healthy consulting practice to the† life sciences industry.

IMS is going through its own transformation. As an employee, itís a very exciting time to be part of IMS. We have been known as a data company, but are increasingly focused on being a healthcare solutions provider. What that really means is that data is our asset and itís our core, but our customers are also looking for a full solution with domain expertise and technology enablement. Our number one goal is to help customers obtain better insights, which is directed toward helping them make better decisions so that their strategy, planning, and execution can be improved. We're focused, like I said, very heavily on the commercial operations space, so a lot of the offerings we have are geared toward helping customers with their analytics and business intelligence programs.

Can you tell me why it's so important for pharmaceutical companies to leverage their data effectively?

Peter Harbin: When I think about the pharmaceutical industry, I don't think itís any more important than other industries, but it is different. The landscape is changing. A lot of the change has to do with legislation and some of the new ways that pharma is being governed. But overall, the profile of the customer has also evolved. In pharma, as we all know, blockbuster products are becoming fewer and fewer. A lot of genericization is taking place. Therapeutic areas that had blockbusters in the past now have five or six competitors because of the age of the therapeutic classes.

In the past, pharma companies organized a lot of their efforts around their biggest customers Ė the general practitioners and specialists who service patients and diagnose their conditions. Therefore, pharma was a big educator to physicians and ultimately helped them select the right prescriptions for their patients.

Today there are larger patient populations who have chronic diseases or mature disease states. A shift has taken place, and now itís not only the prescriber that can dictate what the prescription should be, but also a very intricate network of non-prescribers Ė formularies, managed care groups and long-term care practices. This isnít a new situation. Some pharma companies have traditionally focused on these groups; but for the majority of pharma companies, the influence network has grown.

It is critical for the commercial model of pharma companies that they be able to map out this relatively new influence network Ė what we call the healthcare management network. We call it the new commercial model, and we see a lot of companies that have had systems and data assets that were very specific to prescribers who are now looking to acquire new data assets, new information and then combine it so that they get a full picture of the network instead of just fragmented pieces. The idea is to get the† 360-degree view of the customer, which, in this case, is the patient.

Peter, because these pharmaceutical companies can access all of your data and combine it with theirs, they now can assess the impact of any of their prescription drugs. That's really the benefit, right?

Peter Harbin: Yes, exactly. And when we look at third-party information combined with the data that pharma companies are collecting, that's really where the magic occurs. In the past, everybody talked about data, and then it moved from data to information. Now what is key and what everybody is looking for is the insight. The insight is the combination of the information that people look at, scenario-based discussions and different types of analyses. Pharma companies can look at not just what happened yesterday but also be a little more leading and predictive about what could happen tomorrow.

Compounding the challenge, pharma companies are facing the reality that there are a lot of new parts to the commercial model. In the past, it was really sales focused. Today, the commercial model includes marketing, and marketing has gone through a massive transformation because of social media, social networking and multichannel Ė looking at the web and how patients interact with websites. Pharma companies have discovered the value of social media, and it's bringing them a ton of useful information.

Can you explain commercial analytics and how an organization can achieve value with this type of analytics?

Peter Harbin: Data and information are key to commercial analytics, but we're really looking for the recipe where that comes together into insight. The value is being able to look at multiple, maybe even 50 or 60, datasets and pieces of information to bring the story together. The real magic and value Ė from a commercial analytics perspective Ė is getting insight in the quickest time possible. That becomes a competitive differentiator. A lot of companies have focused on sales operations to manage the relationship from strategy, planning, and execution, primarily targeting GPs and specialists.

At IMS, we start to look into the marketing groups, into the managed care organizations and actually into everyone who has a customer touchpoint. From an outbound perspective, that can be looking at what types of promotions and campaigns are run, and how feedback can be collected so the company can determine where the biggest value is occurring and where they should be investing their time.

In terms of effectiveness and efficiency, a lot of pharma companies are being tasked with doing more with less, and they can't only focus on the sales ops perspective. They need to look at the whole commercial model. The† commercial model is where we bring in analytics from many different places that werenít previously coordinated.

From an analysis perspective, the challenges pharma companies are facing today aren't much different from the ones they've faced in the past. But today they're being forced to sit down at the table to determine the business strategy that they want their people to be addressing. They need to shift the conversation in the boardroom from just looking at what happened yesterday in one channel to looking at what types of insights they need to manage the business. Itís really focusing on the integration of the sales and marketing touchpoints as well as all other necessary information that is associated with that.

The whole goal at the end of the day, outside of getting insights faster, is to create what we call actionable intelligence. Itís not just enough to say, "O.K., this happened or didn't happen," or determine how far off they were, versus what they projected. The goal is to get the users of these analytics systems to be able to say. "This is off, I know why itís off, and here's what I need to do about it." And that's really the holy grail that people are trying to find. This evolution has been a little bit slower than I think it needed to be, and pharma companies are really looking today to companies like IMS and other partners in the industry to help them get to actionable intelligence.

The other part to that is not just actions for a salesperson or a marketer, but to really deliver it in the context of the role and how those roles need to work together. Itís the familiar adage of the right information at the right time to help drive the right action. That's really what we see a lot of and what our customers are coming to us to help them achieve.

Peter, what would you say are the core steps for deriving the most value from a commercial model or commercial analytics?

Peter Harbin: There are three or four key steps that we've seen through hundreds of implementations. We help customers get to commercial analytics with the limited amount of pain and money. We always come back to the point that now that the model has changed and the landscape is different, what are you actually trying to achieve and understand? I think a lot of mistakes have been made in the past where companies have taken whatever is in their data warehouse and made it available to everybody. Thatís not driving insight. Itís just providing information in a different way.

We help our customers understand what business benefit a particular insight is going to help them achieve. This comes down to some very simple questions that a lot of people have not considered such as: If we could look at some of the customer data thatís coming from our websites and combine that with some other datasets, what could we learn?

We help our customers look at the exceptions, the outliers, to create the scenario-based analysis that can be used to identify options and understand the likely outcome for each option. To be reactive is one thing but looking to be proactive with outcomes that can be measured Ė in days rather than in months Ė and have a high degree of confidence that the steps you take will actually drive what you're trying to achieve, is another.

Once you know what youíre looking for and what you think will help drive your business to help deliver better patient outcomes, you can begin understanding data acquisition to see if you're acquiring the right data and information Ė and that leads to insight. Today, pharma companiess have a lot of structured data, but as they begin to include unstructured data Ė such as social media data and website results Ė deriving insights from that unstructured data becomes more complicated.

And then, of course, steps three and four involve how the data is collected and organized properly so it can be disseminated in the most effective way.

We really look at the combination of the assets, trying to raise the bar on the domain expertise so that companies can look at standard reporting as well as ad hoc reporting. We also help them take advantage of the delivery mechanisms Ė in this case, technology Ė to push alerts and exceptions in real time. For example, if there was a formulary win that impacts their business in either a positive or negative way, we help them determine how to plan around that and start communicating within minutes of the occurrence, instead of weeks or months.

From a data perspective, what are all the sources of the data used for commercial analytics?

Peter Harbin:
We have worked with some companies that have 1,000 websites, and those websites all become sources of information. We look at it from six key source levels.

The first one is market environment, the second is applying the organizationís business objectives and the third is looking at the customer's customer. In this case, pharma doesnít go directly to the customer unless they have an over-the-counter product, but rather they look at the actual patients who are the customer's customers to understand what's happening with them. The fourth is looking at the competitive landscape, the fifth is looking at market feedback that happens through the thousands of different points of contact from their websites or specific primary/secondary research. And the sixth is really all the five that I mentioned in context with how this information can be brought to the right person.

If you think about having 5,000 people who have a customer touchpoint, and all the different combinations and permutations with millions of customers, getting the right information to the right people at the right time becomes a very complex problem. We look at standard reporting, ad hoc reporting, predictive analysis and then how we integrate it so thereís relevance when someone in marketing looks at a dashboard. It is really those five areas and then everything in context.

Can you give us some specific examples of the benefits that these pharmaceutical companies are gaining from commercial analytics?

Peter Harbin: There are a lot of examples, and Iím going to group them into a couple of categories. One of the biggest challenges with analytics and insights is really ensuring that your company can use it, understand it and then be responsible to act on it. There's a big learning curve for any end user. That really identifies the first step. We have spent a lot of time making sure our systems and our customersí systems (that we either help them build or build for them) take the user experience into consideration. These analytics platforms need to be intuitive. Most pharma companies don't want their field force to be analysts. They want their analytics platforms to be very user-friendly and ergonomic Ė meaning its available on a laptop and it's available on their iPad or or other mobile device so that they can be informed when something happens and they need to make a change in direction. This also needs to be very point-and-click, so performance is another big key.

For example, when we have a formulary change in pharma, there's a big impact and the impact can be measured in days, hours, or seconds. If you are a pharma company experiencing an event that has a negative impact Ė for example, your product is no longer covered or itís covered less than it was before Ė then specific messaging needs to be given to the physicians so that they can: A) understand the change, B) understand how it impacts their prescribing behavior, and then C)† be able to defend any negative messaging they may hear from their patients. Conversely, in the example Iím referring to, if the formulary change is a benefit to you, a lot of competing companies will be defending against it. Itís important for your sales representatives to know what messages to present and how to position it because it can also impact your line in a very positive way.

Today, with how commercial analytics has evolved, the available technology, and the insights that people have been able to predefine, those changes can now be measured in minutes and hours instead of weeks and months. Not every company is there yet, but they're slowly getting there.

Another example would be the healthcare management network. There's been a big paradigm shift in terms of just focusing on physicians and the prescriber. Now commercial analytics and being able to bring in other non-prescriber groups that have a lot of influence can really help a pharma company understand what's happening in the healthcare network and be able to formulate/readjust plans to make the biggest impact.

Through the power of these analytical tools and structuring the data warehouse correctly, we can help them weed through that rapidly. We've seen amazing transformation in most of the big pharma companies that are looking very horizontally, but also have the power to go vertically as well. Before it was more of a fractured view, but today they have a complete view. The net result of that, of course, is better information, better decisions, and better patient outcomes, which drives better shareholder value and profitability for the organization.

And it really speeds up these pharmaceutical companies. It increases their profits but at the same time reduces their expenses because of the data that is now available.

Peter Harbin: Absolutely. And that's a big driver today because a lot of pharma companies must comply with the Sunshine Act and are being closely scrutinized over spending. Theyíre in a situation where they have to be better at this type of activity than they have been before. Itís not an environment where the more promotion you do, the better you get. They're limited to the types of promotions they can do so it's about really finding the right person or group of buyers, and finding them faster and cheaper than before.

Peter, thank you so much for taking the time today to discuss the benefits and providing examples of how commercial analytics is benefiting the pharma industry.

  • Ron PowellRon Powell
    Ron is an independent analyst, consultant and editorial expert with extensive knowledge and experience in business intelligence, big data, analytics and data warehousing. Currently president of Powell Interactive Media, which specializes in consulting and podcast services, he is also Executive Producer of The World Transformed Fast Forward series. In 2004, Ron founded the BeyeNETWORK, which was acquired by Tech Target in 2010.† Prior to the founding of the BeyeNETWORK, Ron was cofounder, publisher and editorial director of DM Review (now Information Management). He maintains an expert channel and blog on the BeyeNETWORK and may be contacted by email at†rpowell@powellinteractivemedia.com.

    More articles and Ron's blog can be found in his BeyeNETWORK expert channel.

Recent articles by Ron Powell



Want to post a comment? Login or become a member today!

Be the first to comment!