Pharma

1. How Pfizer Uses
Tablet PCs and Click-
Stream Data to Track
Its Strategy
AUGUST 2011
REPRINT NUMBER 53118
Interview with David Kreutter (Pfizer)

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“We’retakinganalyticsfromaplanningperspectivetoaplanning,exe-
cutionandevolutionperspective,”saysDavidKreutter,VP,US
CommercialOperationsatPfizerInc.Asaresult,analyticshasbecome
“muchmoreoperationalthanit’sbeeninthepast.”
DAVID KREUTTER (PFIZER), INTERVIEWED BY DAVID KIRONAND REBECCA SHOCKLEY
HowPfizerUses
TabletPCsand
Click-StreamData
toTrackItsStrategy
T
he ways that Pfizer Inc., the global pharmaceutical company, uses analytics is
changing, in no small thanks to the pressure on physicians to prescribe generic
rather than brandname drugs.
David Kreutter, VP, US Commercial Operations, is accountable for Pfizer’s U.S.
commercial operations, including business analytics. He says that “in terms of cus-
tomer analytics and commercial operating analytics, Pfizer U.S. has a strong legacy
of management science in operations research support.” With a team of 40-50
economists, statisticians, operations research colleagues and scientists, Kreutter says the group historically
has focused on promotional tactics: understanding the effectiveness of strategies used in the field, in conver-
sations with physicians and other players who influence whether a Pfizer drug is prescribed or not.
Today, that’s a little different. Today, Kreutter says his team closely tracks how sales representatives present
material and how presentations are received. It’s information, he says, that’s critical.
Kreutter spoke with David Kiron, executive editor at MIT Sloan Management Review, and Rebecca Shockley,
the business analytics and optimization global lead for the IBM Institute for Business Value, about how the
company is generating daily data reports, why precision is overvalued and what the coming generic version
of the company’s popular Lipitor drug has meant in terms of attention to analytics.
KIRON: How has the strategic role of analytics changed at Pfizer in recent years?
It has changed significantly. Part of that change is in response to the cost constraints that we’re all facing, “all”
meaning pharmaceutical companies.

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There’s no great surprise here — a number of very,
very successful drugs in the marketplace are disap-
pearing this year and over the next couple of years,
which is just astounding in terms of the number of
dollars. From a healthcare perspective, it’s abso-
lutely great for patients to have a generic version
available of Lipitor [a Pfizer cholesterol medication
that reduces the risk of heart attack]. From a busi-
ness challenge perspective, though, taking billions
of dollars out of a corporation in one fell swoop is a
little bit daunting.
Part of our response is how do we reduce our oper-
ating expenses so that we can maintain our
operating margins? The question of capital alloca-
tion becomes even more critical than it normally is
in an environment of constrained resources. You
don’t have the same operating buffer, if you will,
that you had before.
What I’m seeing, from an organization perspective,
is more of a focus on understanding what the data
are telling us in order to use resources in the most
efficient and effective way possible. Historically, I
would describe our use of analytics at Pfizer as a
kind of intellectual journey. People would have hy-
potheses or strategies that they would want to
pursue through numbers. They would quantita-
tively analyze them, but for the most part, unless
there was a glaring difference between the hypoth-
esis and the analytics, people would pursue their
strategies as long as they were compliant with our
legal and regulatory requirements. That’s pretty
much going away. Because we’re at a point where we
can’t ignore any data telling us about the effective-
ness of our business strategies. The stakes are just
too high, and the resources to allocate aren’t the
same as they were before.
KIRON: How have you seen that change play
out?
There’s certainly an uptick in focus and utilization.
There have seen some clear demonstrations of how
we can use analytics to link the goals of teams to ac-
tual execution at a field force level. For instance, we
are able to understand the “why” of things a little
better. When something is not working, is it the
strategy that’s not working? Is it the execution?
Both? We’re taking analytics from a planning per-
spective to a planning, execution and evolution
perspective, so it becomes much more operational
than it’s been in the past. I think that’s the key part.
SHOCKLEY:Tell us some more, if you can,
about how you’re using analytics to under-
stand your customers.
Well, we have data on almost every physician in the
U.S. who prescribes Pfizer medications, and that
data comes from IMS. What’s really changed over
the past year or so is the amount of data we collect
directly from our customers — meaning either the
healthcare providers who do the prescribing them-
selves or the people in their offices who would
either influence them or execute on their behalf,
like nurse-practitioners and physician’s assistants.
As we’ve evolved from a paper-based interaction
model to a digital-interaction model and a multi-
channel model, we’re getting a huge amount of
information from our interactions with our cus-
tomers.
A lot of it is activity-based. When physicians visit
our website, we know what they’re clicking on, we
know what they’re clicking through to. We don’t
have any greater data on how those clicks translate
into prescription writing, but we’ve got more data
from which to try to discern patterns, which we can
use in a predictive way. That’s really what we’re try-
ing to focus on now: can we detect patterns
early-on, or at least much earlier than prescription
writing, that will allow us to adapt more quickly to
our customers’ needs as well as to the competitive
environment?
KIRON: Lots of data, a lot more quickly.
Yeah. Here’s an example. We segment our custom-
ers much like any other industry would segment
customers. Lipitor is Lipitor, so we don’t change the

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legal and regulatory approved messaging around
that product, but we will change the presentation
based on how physicians approach the care of their
patients and how they absorb information. We tai-
lor the presentation to be aligned with that
customer segment’s needs and preferences.
When we were a paper-based organization, we had
no way of knowing whether a sales representative
actually showed the recommended content to the
recommended segment. There was just no way of
understanding that.
Now that we’re in a digital operating model, we
have an opportunity to ensure greater compliance
controls and detailing effectiveness. For example,
we can ensure that representatives are using the ap-
proved and up-to-date materials and are interacting
only with healthcare providers that belong to ap-
proved specialties for our products. We can also
actually track, literally in real-time, the utilization
of content and then the behavior. We can see if rep-
resentatives are delivering the recommended
content to the recommended segment. If our strat-
egy is to deliver certain messages in a certain order,
we can see if the message was delivered that way.
For example, if we know that a certain segment of
doctors in South Florida have a heavy proportion of
elderly patients, they will often want to hear about
drug-drug interactions first (since their patients are
on many medications). We can track if we executed
against that strategy, and we can track if that strat-
egy had the impact, the literal prescribing behavior,
that we anticipated. It’s a huge level of insight into
the basic operating model, and really helps us to
figure out, if we don’t have the impact we hoped for,
if our strategy was right but the execution was
flawed, or if the strategy fundamentally needs to be
rethought.
KIRON: How do you get that information in
real-time?
By real-time, I mean daily. I don’t mean literally as
the representative is talking to a physician. Let me
give you a little bit of context. When we get IMS
data at a prescriber level, there’s about a 6-8 week
lag between what literally happened, the physician
writing the prescription, and us getting the data.
Two months.
When representatives talk to physicians in person,
those representatives are now using tablet PCs. As
they click the screens with their styluses to illustrate
points, those clicks are recorded. That’s how we’re
able to see things like the order of presentations, the
messages within a presentation that were presented,
if the physician found it engaging. Representatives
synchronize their tablets on a daily basis, and we
get a data stream back to our data warehouse. Our
customer data master now has all of that click-
streamdataforeachrepresentativeandeachdoctor.
Just to put that in scale, in Pfizer’s Primary Care
Business Unit, we have about 4,000 representatives.
Each of them sees about seven or eight physicians a
day, and details about two to three products in each
of those calls. And they’re out there five days a
week. We’re collecting a lot of data on a daily basis
now.
SHOCKLEY: It’s interesting that presenta-
tions are now made on tablet PCs in the
field. Do you feel like the needs of your cus-
tomers have changed?
Yeah, they certainly have, and on a couple of levels.
At one level, there’s the simple fact that pharma, as
an industry, is no longer the sole source of informa-
tion about our products. Physicians don’t need a
sales representative to deliver a package insert for a
product: they can go on the internet and get it
themselves.
As well, their autonomy in determining their own
medical practice has changed significantly. The de-
mands of payers around generic utilization and cost
containment have really started to reduce the de-
greesoffreedomthatourcustomers,thephysicians,
have.
But those payers are our customers, too. Whether

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you’re on the formulary for CVS Caremark or Wal-
green’s or whomever very much influences the
utilization of medication. And of course the pa-
tients themselves are very influential. They’ve got
access to much of the same information that physi-
cians have, and that dynamic, the patient-physician
dynamic, has changed dramatically. Patients have
become more empowered and more accountable
for their own healthcare. The whole industry, the
whole healthcare ecosystem, is in flux.
SHOCKLEY:What’s been the most difficult
thing in getting to where you are today?
From a capabilities’ perspective, the hardest part
has been the talent pool. Hiring the right people.
The pharma industry in general isn’t state-of-the-
art in the use of analytics, so when I think about
talent and capabilities, I don’t look at what is Merck
doing and how do I access that talent, I look at con-
sumer packaged goods, financial services, telecom,
and ask, how are they advancing their business? We
haven’t even caught up to where they were five years
ago. What are companies in those industries doing
now? What talents have they accessed to drive that?
How do I access that talent?
The challenge is contextual knowledge. Pharma is
not telecom. It’s a different operating model. So
how do we round out our staff people so they can
apply their brain power and capability set in a busi-
ness-contextual manner? We want to make sure
that the value they’re bringing can be realized — we
don’t want to wind up with theoretical answers that
aren’t executable in our environment.
The challenge also is that I want to keep them en-
gaged. If their primary motivation is to do
cutting-edge research and analytics, and to interact
with like-minded individuals, how do I make sure
that I’m meeting their needs so that we can retain
them and keep them productive?
SHOCKLEY:Are there particular skills that
you think are critical to have within your an-
alytics group that you have particular
difficulty finding?
That’s a hard question for me to answer, because
based on how we currently use analytics to drive in-
sights, I think we have the capabilities we need. But
that’s kind of self-limiting. What I don’t know is,
how do we take it to the next level? How do we pro-
vide the next level of insights? I’m not talking about
a marginal improvement. I’m talking about a frame
shift. How do we provide next-generation insights
to the organization?
SHOCKLEY: So talent is a challenge.What
about cultural issues?What’s been hard cul-
turally in getting to where you are today?
What’s been difficult is the temptation — and
maybe it’s an appropriate temptation — to ask, in a
cost-constrained environment, if we can really af-
ford to spend this much time and money on data
and analytics.
I actually think that the spending question is mis-
placed. The question isn’t how much money do we
spend on data and analytics. It’s how much value are
we getting from data and analytics. If the literal
amount of value that you get exceeds the cost, then
finance theory would say, “Yep. Do it. Keep doing
it.” If it’s not, it’s not necessarily a question of do we
cut it. It’s a question of what can we do to get more
value out of it. But the reality is that there’s a pretty
intense focus at the moment on cost.
The other challenge is how do you literally ascribe
value to analytics. Invariably, someone will say, “I
would have done that strategy anyway. Whether
you analyze it or not, I would have done it.” And
yeah. I don’t know: maybe yes, maybe no.
Demonstrating the value of analytics on an on-go-
ing basis is part of building the organizational
support. I do think there are two schools of thought
around this. One is the top-down and the other is
bottom-up. I think they’re both valid, but I just
think they require different approaches.
SHOCKLEY: Has Pfizer taken one approach
or the other?A combination of both?

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Well, I think the focus on analytics has really been
one on sophistication and precision. I want to pick
up on the precision part because I think there’s a
fundamental belief — and I think it’s something
that’s untrue — that a precise answer gives you a
better decision.
We obviously can analyze things much more pre-
cisely than we can execute them because it requires
humans to execute these strategies, and each
human applies some personal judgment. The beau-
tifully precise answer gets diluted as the strategy
gets executed. As I mentioned before, we can now at
least track that that process.
But I also think that some of that focus on precision
is misguided. Because by definition, we’re trying to
analyze the future, not the past. As I mentioned at
the beginning of our conversation, analytics is not a
descriptive exercise; it’s a predictive exercise.
Therefore, by definition, there’s uncertainty: We
don’t know everything about the future. Maybe
some of our focus should be on helping the organi-
zation understand the bounds of uncertainty and
the actions we can take within those bounds of un-
certainty.
David Kiron is executive editor of MIT Sloan Man-
agement Review. Rebecca Shockley is the business
analytics and optimization global lead for the IBM In-
stitute for BusinessValue.
Reprint 53118.
Copyright © Massachusetts Institute of Technology, 2011.
All rights reserved.
I would say it’s a combination of both. The reality is
that all these strategies are executed bottom-up, be-
cause demonstrating value at the brand-team level
is absolutely critical. I don’t think top-down would
be possible because I fundamentally believe that if
you mandate analytics or you mandate anything, at
least in our organization, it’s the kiss of death.
KIRON: I understand, though, that the ana-
lytics operation at Pfizer is in the process of
becoming an integrated service for the com-
pany. Can you talk about what that means
and how that will work?
Currently, the analytics department is a shared ser-
vice across the U.S. business. From an
organizational perspective, analytics sits within
Commercial Operations. It’s not a pay-by-the-
drink system, but based on utilization patterns on
an annual basis, our services are charged out to the
four U.S. business units.
Now, all of that is about to change. The overall di-
rection going forward is that analytics will be
integrated, meaning that secondary market re-
search, market analytics and management science
will be integrated into a single analytical function.
And it will be integrated on a global basis.
This gets really tricky because while I have an inte-
grated analytical function in the U.S., it doesn’t
really exist like that in some of our other markets.
There, people who do this do it as part of a broader
job. This will be a way to leverage the sophisticated
capabilities that we have in the U.S. through a con-
solidated delivery center to the less well-endowed
organizations around the globe. Can we deliver bet-
ter insights more cheaply than we’re currently
delivering them? That was the rationale for the con-
solidation of analytics, but analytics was only one of
a number of shared services that were consolidated
on a global basis.
SHOCKLEY:You’ve been in analytics for a
long time.Are there any other observations
you’d like to share?

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