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15 10, 2014

Forget risk management; long live resilience management

By |2017-05-23T15:42:01-08:00October 15th, 2014|Blog|0 Comments

We are surrounded by evidence of resilience: Our immune systems fight off thousands of potential invaders every day and constantly hone their defenses in response to the threats they experience. Ecosystems evolve to use the forces that might otherwise threaten them, such as the sequoia forests of the Sierra Nevada, which don’t just survive forest fires, but use fire as a tool to foster new seedlings. Nature is full of complex systems that use threats to make themselves stronger.

But what about the companies to which we devote so much of our time and resources? They are complex systems, but are they resilient? What can we do to build resilience into their DNA?

A recent article in the magazine Nature* offers a framework for creating resilience that has much to recommend it. Although the article is focused on the threats created by climate change, the basic concept is widely applicable. In the approach it describes, risks to a system (say, your company or R&D portfolio) are characterized as threats that have some chance of occurring (based on the extent of the vulnerability) and will result in some consequence. The consequence inhibits your companies’ ability to perform, profit, and grow. As a resilient business, an inherent adaptability in your systems and processes allow you to adjust your operations, accommodate and minimize the consequences of the occurrence, and move forward. A resilient company will, over time, recover, and perhaps even exceed its performance prior to the event.

You are probably already thinking that scenario analysis and risk management—activities in which a management team ponders the bad things that might happen, and hedges its bets— are an important part of building resilience. I agree, but I think there’s more to resilience management than scenario thinking.


16 10, 2013

Portfolio Management Can Be a Six Year Journey, Here’s Why

By |2017-05-23T15:42:02-08:00October 16th, 2013|Blog|0 Comments

rtm_coverThe September-October 2013 issue of Research Technology Management Journal includes a case study on portfolio management written by our own Dan Smith and yours truly: “From Budget-Based to Strategy-Based Portfolio Management: A Six-Year Case Study”. In it, we describe the journey of a life sciences company as it transitioned from a conservative, somewhat disordered investment process to one that was in better alignment with the long-term growth aspirations of the firm.

You might be saying “Six years to a better process? That seems an awfully long road.” The plain truth is that effective portfolio management doesn’t happen overnight, especially in mature companies. Portfolio management involves a diverse set of stakeholders across the firm, and therefore everyone involved in R&D spending must be engaged in the process overhaul, from project champions to the head of R&D and the CFO. Bringing transparency to the discussions of each project’s value will threaten project teams unaccustomed to justifying their funding to management. At the same time, management may be unaccustomed to basing, and explaining the rationale for, funding decisions in the context of information gathered through the portfolio process. So, the barriers to overnight success in portfolio management are largely organizational, rather than technological or scientific.

The good news is that benefits of implementing even a few portfolio management best-practices accrue almost immediately. The key to long-term success is to build stakeholder consensus around a clear but cautious road map for improving your portfolio management process. Each step should bring more rigor to the process, while conferring tangible benefits to both management and product teams. Be careful not to add too much sophistication to valuation or portfolio analyses in any one portfolio cycle. One team we worked with never showed more than two novel analyses to management in a portfolio review. This slow-but-steady process improvement mindset helped all involved stay focused on the funding decisions rather than drowning in methodologies or fancy visualizations. It also ensured that management had sufficient time to learn about and assess the value of new analyses brought to each review.

21 01, 2013

Learning From Our Forecasting Foibles

By |2017-05-23T15:42:02-08:00January 21st, 2013|Blog|0 Comments

The prevalent tendency to underweight, or ignore, distributional information is perhaps the major source of error of intuitive prediction…The analyst should therefore make every effort to frame the forecasting problem so as to facilitate utilizing all the distributional information that is available to the expert.

—Daniel Kahneman and Amos Tversky

Most people involved in risky enterprises forecast costs or benefits as a single estimate in each time period, rather than a range that reflects the unknowable nature of the future. That’s why we can readily compile the following examples. Below you’ll find a few instances of deterministic (expressed as a point or line estimate rather than a range) forecasts that missed the mark. In some cases we have the benefit of hindsight over many years of forecasts, or across many independent experts, so that we can easily see just how difficult forecasting can be.

20 09, 2012

Storytelling and Pharmaceutical Portfolio Management

By |2017-05-23T15:42:03-08:00September 20th, 2012|Blog|0 Comments

campfireHumans have always been and will always be storytellers. From the fireside tales of bygone millennia to today’s TV dramas and movies, the power of the narrative holds us in rapt attention as it both entertains and makes sense of the world around us.

How does this relate to pharmaceutical portfolio management? Essentially, portfolio management is about affecting change in an organization. But real, honest to goodness change is hard to bring about; what people will do to avoid change is the basis of many a sitcom. To initiate change, you need to make a compelling case against the status quo—you need to tell a great story. Your tale might unfold like this:

    Act I:    Set-up, or “How We Got to Where We Are”
    Act II:   Complication, or “We’re On the Road to Ruin (or at least mediocrity)”
    Act III:  Resolution, “The Happy Ending—if we do portfolio activities A, B & C”

It isn’t always safe or easy, but whether you are an analyst convincing your manager or an executive persuading the board, telling a story will help you make your case, and do so in an effective and entertaining way.

9 09, 2012

The “Good Enough” Business Model

By |2017-05-23T15:42:03-08:00September 9th, 2012|Blog|0 Comments

A product manager and an analyst are discussing the revenue forecast for a product in development. Poring over the financials, the manager asks:
     “Have you considered how SUPR-3 will impact sales of our other SUPR products?”
     The analyst replies confidently: “Yes! Right here you can see we are estimating SUPR-3 to take a 20% cannibalization of the existing SUPR product line.”
     “But a dollar of revenue from our earlier SUPR products is much less valuable, since we have fatter margins on the new product. Has that been factored in?” asks the manager.
     “Oh no, I didn’t think of that,” replies the analyst, taken off guard. “I’m on it.”  So away goes the analyst with a job to do: Add another input and another algorithm to The Model.
     Two days later the analyst meets with the manager once again: “You were right about the difference in profit margins–it reduced the impact of cannibalization by 20% and increased the net present value by 4%.”
“I thought so,” says a satisfied manager.” We are getting closer with this business case.”


Another factor to roll up with the model

They were “getting closer,” but the model still wasn’t “good enough.” Variations on this theme play out every few days for the next month, until there are a dozen more business factors explicitly considered in the forecast. Over a quarter or a year, they might add hundreds of factors as they think of questions, but never remove them as they find answers. Taking out a business factor goes against instinct, as if they were removing value, or intelligence, from the model.


6 08, 2012

Tornado Diagrams 101

By |2017-05-23T15:42:04-08:00August 6th, 2012|Blog|0 Comments

As we have said before, every forecast you’ll ever build is wrong. The truth may be out there, but due to a lack of perfect information about the future, you won’t be able to reveal it before your project review meeting.

There is a paradox here: The more you insist on the truth, the more likely you are to deny the uncertainties obscuring it. Alas, denying the existence of those uncertainties distances you still further from the truth. So, take a deep breath, and let go of your desire to know the truth. Now you are ready to manage (dare I say embrace?) the uncertainty standing between you and the truth. Managing this uncertainty is the key to good forecasting. By effectively managing uncertainty, you’ll be able to honestly assess the value of your forecast and, in turn, make an honest statement about the value of your project.

A tornado diagram can help you find your project's pot of gold.

A tornado diagram can help you find your project’s pot of gold.

As a forecaster, the key question you need to answer is: “Is my forecast precise enough to make a confident decision?” If it is, hooray! You are ready to make an investment decision. If the answer is no, then you need to gather more information. One of the most useful and easiest-to-understand methods we have to assess our confidence in a forecast is the tornado diagram. Using a tornado diagram, we can assess how much our forecast might change if things go better or worse than anticipated. We can also assess which uncertainties have the greatest impact on our forecast—those are the very inputs we should research further if we want to tighten up forecast precision.


22 07, 2012

Pigs, Chickens, and Discount Rates: Improving Project Valuations for R&D Portfolio Management

By |2017-05-23T15:42:04-08:00July 22nd, 2012|Blog|2 Comments

Finance and R&D can get along

Finance and R&D can get along

You’ve just finished briefing the executive committee on the methods for project valuation that you have worked so hard to establish in your R&D group. The team has finally acknowledged that risk needs to be managed in all its potential forms. You’ve reached consensus on the following set of risks that will be characterized as ranges, using probability distributions in your business models:

  • Market share
  • Willingness to pay
  • Product yield
  • Product cost
  • Technology feasibility/R&D cost and schedule


15 07, 2012

In R&D Portoflio Management, Failure is an Option

By |2017-05-23T15:42:04-08:00July 15th, 2012|Blog|0 Comments

Innovation is inherently risky. By definition, you’re doing something that you haven’t done before so there are no guarantees it will work. The mindset in many organizations is to “minimize” risk as if it were a disease, but it isn’t that simple. The best companies face risk head-on and manage it both systematically and transparently.


10 06, 2012

All the NPVs are wrong. Can we talk about the portfolio now?

By |2017-05-23T15:42:04-08:00June 10th, 2012|Blog|0 Comments

A review of Itanium server sales forecasts made over seven years reveals the same bias year after year after year.

A review of Itanium server sales forecasts made over seven years reveals the same bias year after year after year.

When the economist Kenneth Arrow was working as an air force weather forecaster during the Second World War, he and his colleagues found that their long-range weather predictions were no better than random. They informed the boss but were told, “The commanding general is well aware that the forecasts are no good. However, he needs them for planning purposes.”
David Orrell, The Science of Prediction, 2006

The first step in R&D portfolio management is to generate the list of projects that are under consideration and value them. Unfortunately, this is where many companies spend 99% of their effort, and too often this leads to countless wasted hours and benign neglect of the portfolio as a whole.


6 10, 2010

R&D Portfolio Management and the Black Swan

By |2017-05-23T15:42:09-08:00October 6th, 2010|Blog|0 Comments

blackswanI recently read The Black Swan by Nassim Nicholas Taleb and found the book’s central tenets relevant to R&D portfolio management. I recommend you pick up a copy yourself, but until you do, I hope the following thoughts hit the mark for you as they did for me.

What is a “Black Swan?”

According to Taleb, a Black Swan is an event with three characteristics: 1) It has a low probability of occurrence; 2) It has remarkable (positive or negative) consequences; and 3) It creates an irresistible urge to retrospectively concoct a story explaining why the event happened and how it could easily have been predicted. The problem with Black Swans, says Taleb, is that they are far more common than those in the prediction business will admit, and that they have profound implications for the value of forecasting and sound decision making in a wide variety of disciplines.

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