This is the end February 2015 update to let you know what we are doing, what we are thinking and seeking some help in setting priorities, especially in Big Data.

We need your help on making making two decisions. Please continue reading to help us vote.

For 2015, we set an extremely ambitious agenda for new consulting studies, new TCO-type shows and significant changes to the website. The good news is that we are on track so far with just 17% of the year completed.

Where do we stand:

Executive program studies x 4:

  1. LAB Market Entry Strategy Study On schedule
  2. Power Sector Corporate Strategy & Transformation Study On schedule
  3. Technology Merger Implementation Study On schedule
  4. Purpose of this update!

TCO-type shows x 3: On schedule

Website changes x 2: Ahead of schedule

As it stands, of the 9 major initiatives we have planned, we can clearly see at least 7 of them finishing on time while the other two are still possible but we need to make some changes to complete them all.

Decision 1: Do you want to learn how we inspire / motivate / mentor / build confidence in executives?

Fatigue among our executive clients is a big problem. Read one classic example that made it into the press. Horta-Osorio is actually a very capable executive and this did not derail him. Others are not so lucky.

At Firmsconsulting we have a dedicated partner working on leadership/confidence/motivational issues for the executives at the companies where we run our consulting studies. This is a big part of the behind-the-scenes work you never see about our studies. We discuss how we apply this work during the Power Sector Corporate Strategy Study Podcasts where the leadership team is playing a major role in working with the client.

This work is crucial. Most of our executive clients are under extreme pressure to perform. These are the tough conditions of the power sector study, for example.

The company is constantly in the press under a barrage of blinding criticism. The executive team is always in emergency meetings dealing with funding issues, operational problems and discussions with regulators. A typical day for an executive starts at 6am and runs until 11pm.

None of the meetings are pleasant and few care about the executive’s views or well being. Executives are routinely seen as highly paid and therefore should be able to handle the criticism.

The executive team is routinely insulted in the press and there is a real threat of termination. At the same time, while all of this is happening, our corporate strategy team is charting a new course for the company and this adds additional pressure on the leadership team.

They need to put out fires constantly while thinking ahead and planning for the future. That is exhausting to do.

Our leadership partner helps executives deal with the following issues.

  1. What is a “leader” in their unique situation?
  2. How does one lead?
  3. How does the executive succeed at his/her job?
  4. How can they wake up every day and remain motivated?
  5. How does an executive plan, prioritize and make decisions with so many conflicting decisions?
  6. How do they motivate their own staff despite all the uncertainty?
  7. What does an executive do on 8am morning of each day?
  8. How would an executive use the crisis to relaunch his/her career?
  9. How can the stress be managed?
  10. How does the executive mentor staff in these situations?
  11. How can an executive map out and achieve a 2, 3 or 5 year career plan within this turmoil?

The objective is simple.

Even if the study is a success, we would not want the leadership team to become burned out or marginalized through the process. They need to achieve personal career success just as much as the company achieves corporate success.

If you would like to know more about this work we do, please let us know in the comments section.

Decision 2: Do you want an Operations, BTO or Disease Management study?

On our header and footer, we list all the studies we have scheduled for 2015 and 2016. Each time you subscribe for a study we count that as a vote for the study. In other word, how popular is the study. The exception is the Big Data Disease Management study for which we do not, yet, have a page to vote.

Right now, operations is the most popular study and is scheduled to be the 4th and final study of the year.

As it stands, this is the top 4 studies based on your votes:

  1. Market entry strategy study
  2. Power Sector strategy study
  3. Operations study
  4. CPG pricing, marketing and strategy study.

We have to decide if the operations study is the 4th study we will do this year. To us, the options are not clear cut. We think BTO and Big Data Disease Management can teach more. We will explain each one below and let you decide.


Operations strategy begins by first determining if the corporate strategy is about competing on lower costs OR product differentiation. It cannot be both. Once you know that, as the operations executive, your job is figuring how to tweak the operations to meet that goal while increasing total factor productivity. The key thing is to know the goal. In fact, there are five key steps to follow. Every single operations technique/tool/approach you could possibly follow at any company anywhere in the world fits into this framework.

Screen Shot 2015-03-07 at 4.42.19 PM

Any operations executive can increase productivity by lowering input costs while keeping output value constant. However, a luxury brand like Hermes, for example, will have such a high cost base to produce quality products that it must focus on increasing output value at a faster rate than rising input costs. Therefore, simply lowering the input costs raises Hermes’s productivity in the short term, but will decimate the company in the long-term. An operations executive who does not understand Hermes’s corporate strategy could conceivably make this mistake.

This applies to any luxury brand, even a luxury auto company. There are many ways to raise productivity, yet they must always support the primary corporate strategy. In the example below, the executive has multiple paths to raise productivity but may need to give up some productivity gains in the short term to keep the output value consistently high over the long term. In other words, how you achieve the productivity increase is just as important as the increase you achieve.

Screen Shot 2015-03-07 at 4.43.16 PM

On the other hand, commodity producers like oil and coal companies must always be lowering costs since they are at the mercy of the lowest cost producer and the market, since low volume producers cannot set the commodity price. Unlike Hermes, a commodity producer must be trying to hack away at costs without lowering volume throughput. This is especially important during bull markets when rising markets will cause prices to rise and productivity to spike even when the costs are rising to unhealthy levels. High prices routinely mask poor operating practices in commodities.

Screen Shot 2015-03-07 at 4.43.35 PM

Finally, if you are not the operations executive, but someone working in the operations department, you must understand how your individual work is linked to the effort to either lower costs or raise value, and which lever needs to be pulled to what extent based on the corporate strategy.

In fact, if you are an operations analyst, you can make a clear case for the value you bring by ensuring your work is always helping the operations team enable the corporate strategy.

Screen Shot 2015-03-07 at 4.43.54 PM


IT strategy is generally poorly done. IT strategy is like corporate finance or organizational design. The corporate finance plan and organizational design must enable/support the corporate strategy. The same for the IT strategy. We will not publish any of the slides on BTO but there is a far more elegant and analytic way to develop IT strategy than the current approach.

Rather than re-writing an overview of IT strategy, it is best to read this detailed article we published earlier.

Big Data Disease Management

This the potential study that I am personally most excited about.We have the opportunity to do something very cutting-edge.

A few weeks back we published a very popular video demonstrating advances in corporate finance now that Big Data can be applied to measure risk and return in far more sophisticated ways.

Healthcare, not finance, is one field where this concept has enormous value. To learn more about this field, read this recent article in the New York Times and the excellent work of David Matheson. Matheson is the now retired BCG senior partner who pioneered a more data intensive way to manage healthcare programs and he basically invented the field of disease management in the 1980s and 1990s.

We think more can be done today, by taking Matheson’s work further. Much, much further.

The link here is that Matheson’s work can be refined and improved by borrowing quite a few concepts from financial analysis, which we just could not do 3 or even 5 years ago due to a lack of computational power.

When I was at the firm I was asked to also lead a group of about 20 PhD’s in physics and mathematics who where trying to solve a particularly important problem in measuring returns. We where successful to some degree but did not have the software now cheaply available to test all our ideas. I will explain the problem in a simple way and then explain the study where we want to apply this technique.

So the proposed study below is the culmination of several years of work and thinking.

Explaining the problem: Let’s assume there is a football team, Liverpool FC. The football team has a defender who by every conventional metric for a defender is pretty lousy. He is not great at stopping the other team from scoring, his tackles are weak and he basically is just hanging onto his role. Now, the manager benches him. The expectation is that the team will perform better if a new defender comes in who has better metrics. However, while the new defender does better, the overall team does worse.

The net effect is that the team loses the game 3 – 2.

Perplexed, the manager brings back the “weaker” defender after 3 straight losses.

Surprisingly, the team plays much better even though that “weak” defender is back and his metrics have not changed. Here you have a situation where the defender is terrible at his role, but the effect he has on the team means that the entire team performs much better when he is around.

If you selected defenders based just on defense metrics, you would cut this defender. However, if the manager selected a defender based on the defender’s ability to “somehow” make the team win, he would keep this defender.

The “somehow” part his key. Maybe the defender raises morale. Maybe the team is more relaxed around him. The correlation is clear but understanding causality is hard. It is close to impossible.

In finance we call this a portfolio selection problem. Rather than looking at each player individually, we need to see the impact he has on the portfolio of players – the team. In a team with 11 players being watched all the time by a coach and thousands of camera’s and screaming fans, this is hard to do. It is hard to determine the impact a player has on the team, and even if you could see the impact, it is very hard to determine the sequence of events that causes that impact. It is therefore, all but impossible to predict what will happen with certainty.

Now, lets make the problem more complicated.

Imagine if you had a team with 350 million players and 100,000 more rules. How could you possibly understand the causality?

This is essentially the problem in healthcare.

You have thousands of treatment options, medical options, payments options, specialist provider options etc., all impacting the level of care provided. Given the complexity of the healthcare system and the inability to determine how one drug/treatment/doctor/insurer impacts the overall end result, the healthcare sector creates metrics to measure how a drug performs as a drug, versus its impact on the overall treatment end goal.

This is the very same problem as in football.

In other words, using the current approach in healthcare you could conceivably cut a treatment since it fails on the metrics for that treatment protocol alone. However, doing so could hurt the entire health outcome if the treatment has an overall positive effect on the net system, even if it scores abysmally in its own category. That is tough to determine but it can be done today with the tools we have for analysis.

It is a completely different way to analyze healthcare options versus the current approach.

We have an opportunity to develop the national disease management strategy for one particularly costly and burdensome disease. The disease has been singled out as the most pressing problem for this economy and is directly impacting productivity and foreign direct investment in one of the most important sectors.

We want to tackle this problem by avoiding the per treatment least cost analyses approach that was pioneering in the 1980’s but now outdated. Yet, still used today.

Most times, consulting assignments zoom in on cost spikes in the chain of treatment and try to lower them. That is the early work of Matheson at BCG. At the time it was pioneering but now that his approach has been implemented widely, doing more of the same generates little incremental improvement. Yet, it is still the gold standard.

In recent times, economists have used health exchanges to pass the burden of costs to consumers so they are incentivized to help lower the costs. The tool is new but the goal is still the same: lowering costs.

The problem is that when consumers are dis-incentivized to spend money on treatment, the consumer may pick a needed treatment/pill to avoid. So healthcare costs go down initially, hopefully, but the overall health of the patient and patient pool is no better off. In fact, relapses from avoiding a needed treatment could cause costs to rise in the long-term.

Doctors attack this problem from a different way. They try to analyze the pathways of a disease to figure out which treatments work best and which can be discarded. They then recommend a treatment path and insurers have to figure out how to pay for it.

So there is this big disconnect. The insurer refuses to pay for treatment x, like physiotherapy, since the benefit is not clear to the system and there is no direct benefit when measuring the impact of the treatment alone. However, the physiotherapy may be necessary for the hip-replacement to work which makes the overall operation a success. Those linkages are hard to understand. They should be understood.

To prove the concept, we built a simple but radically different way to model this problem using Big Data. Rather than being obsessed with the costs spiking, we wanted to see if the return attached to that cost outweighed the costs. The key thing is that the return is not directly linked to the one treatment point. The return for treatment x may be spread all over the system and we need to hunt it down and add it up. The hunting down part cannot be a group of consultants poring over spreadsheets. Even if they could find all the data, the consultants could not understand all the linkages.

I can say that we arrived at this very elegant, and beautiful way to understand the costs, risks, returns and business case around a disease by moving beyond simple 2-dimensional correlations – in English that means plotting data on a x-y graph – to modelling the relationships that existed in a 3rd or 4th dimension.

Our governing hypothesis is that the wrong treatment decisions are being made since we do not correctly understand the risk, cost, return and benefit of each treatment step for the disease and the overall treatment protocol. The client’s eye’s popped out a little when we showed them the example of what we had in mind and the very different recommendations we could develop.

We think you will like this study too.

It is a way to analyze diseases and extract new insights and recommendations that you have never ever seen before. That, we can guarantee.

Please vote here for the study you want to see

Operations study: vote here

BTO study: vote here

Big Data Disease Management: vote by posting a comment below

We will make a decision based on the number of votes and points raised in the comments below. As it stands the operations study has >400 votes, BTO ~ 100 and Big Data Disease Management is at zero since we have just announced it.

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73 responses to Vote: Operations vs BTO vs Big Data Disease Management?

  1. Hi Sundeep,

    We will begin releasing parts of the study guide late this year, but the full study will only come out later next year.


  2. I’ve been eagerly waiting for this Healthcare study to come out since its stated “April ’16”. Any update on when it will actually be released?

  3. Hi Femi,

    This is the central principle of economics applied to operations. Any major economics textbook will explain how being productive leads to wealth and to be productive one needs to be competitive. I do not recall any other publication explaining this the way we have, since we build it off a strong economics and strategy base.

    I thought about this more and the first MGI report explains this well and any of the major pieces of work by Robert Solow, the Nobel Laureate.


  4. Hi Michael:

    Thanks for laying the land with regards a reliable approach to operations strategy. One quick question though: do you have a link to an academic article, or series of articles, that fleshes out this approach in detail? This could be articles that you published or articles that someone else published on this approach. I want to suggest this approach to someone and I want to provide the necessary citation to lend credence to my suggestion. I really like the “productivity ratio” hook. However, if the FC weblink is the appropriate citation, I am happy to do that.

    I look forward to reading your reply.


  5. Hi Cheung,

    Thanks for writing. We will publish both studies but we have prioritized the Big Data piece. That said, it has a heavy operations component as well.


  6. I am a new member of this website and I am so happy to learn hot topics and new cases! Big data seems very interesting and I would vote for that. But I think these topics are both important so maybe it is just a matter of time to cover all of them? Anyway I look forward to anything you are going to have!

  7. There are no such things as traitors on this site. The good news is this is the very last vote for studies in 2015.

    The even better news is all will be done.

    Thanks AB.

  8. Hi Michael,

    The problem I have here is that every new proposal sounds more attractive than the previous one. Months ago as a result of another post I voted for the operations study. It’s a tough call and I feel a bit like a traitor now but well… please remove my vote for operations and add it to big data.


  9. Thanks for the vote Robin!

  10. Hi Michael,
    I would love to see FC’s work on Big Data! Thank you for doing this.

  11. Thanks Henry. It is noted. Michael

  12. Hi Michael;

    Big data it is.


  13. Thanks for voting Gautam.

  14. Thanks Davison – noted!

  15. Michael,

    Decision 1: Absolutely.
    Decision 2: Ordered preference is Operations, BTO, Big Data.


  16. Michael,
    Big Data study +1. It sounds interesting !

  17. Thanks Manmohan – both votes are noted.

  18. Decision 1 definitely.
    I will vote for operations

  19. Thanks Alessandro.

  20. Thanks Ben – that vote was entirely expected!


  21. Michael,
    What else but Big Data Healthcare for me?

  22. Thanks for the vote GK.

  23. +1 on disease management.

  24. Thanks Femi. Your vote is appreciated.

  25. Hi Michael,

    I like the soccer skill complementarity example; perfectly explains the subject. I vote for the Big Data Disease Management Study.



  26. Thanks Nauruz. Your vote is counted.

  27. Big data +1.

  28. Thanks Kevin. All are noted.

  29. Hi gentlemen,

    Decision 1 : yes, I am definitely interested in.

    Decision 2 : all are of my interests, but in order:
    1. Disease amangement
    2. Operations
    3. BTO

    Otherwise, keep up the good work.


  30. Hi AB,

    There are no excuses. We took too long to bring the LAB study out and we know that. We plan to release the LAB study on 10th April 2015 if all goes well.

    The reason we took so long is because the LAB study was for a real client and we were learning how to go through all the checks and balances to ensure the client was comfortable with the material we would eventually release. That process was something new for us and it was a steep learning curve. This approach had never been done before and we had to invent the approach as we went along.

    Each client needs to sign-off on the study. We now have a better process and team to manage that. We have brought in new partners to ensure we do not fall behind.

    We have made substantial changes within Firmsconsulting since November 2014 and we are better prepared for the challenges of running the studies, cleaning them, formatting them for release, preparing the videos and, finally, preparing the detailed study maps. It will not take us about 9 months to a year to bring out a new study again.

    Even so, the LAB study ended in September and it is now March. That is just 6 months and even though we think it is a long delay, taking 6 months to format, record and prepare all the files is very fast. We think we can and should be faster though. That is our goal for 2015.

    Finally, on the point of continuity, there are going to be some delays because clients may start the studies late and approve them late. That is why we are looking to start more than one study at once. In this situation, if one study is delayed by a client, another can be pushed ahead in the production schedule.


  31. Hi Michael,
    Irrespective of what comes at the end of the year, I’d love to see some more continuity on the projects. The LAB study has not been published yet although the blog closed many months ago. It’s like being allowed to smell delicious food and then having the plate taken away. You’re so eager to get a bite you’re salivating but your salivary glands eventually dry up :-). Similar for the technology merger study. I appreciate FC is launching a lot of very interesting initiatives and time is in short supply but I, as a subscriber that really enjoyed those two studies, have been quite disappointed it is taking so long to bring them to completion. They are said to be on schedule. Would you care to share what that schedule is? I truly look forward to seeing them online.


  32. Thanks and noted Phillip.

  33. Thanks Marco!

  34. I vote for Big Data Disease Management. I would love to see the behind the scenes leadership work.

  35. Disease mgmt Study

  36. Thanks for voting Avni.

  37. Disease Management Study +1

  38. Thanks Jamie!

  39. Thanks Jorge. Noted.

  40. I vote for the Big Data, healthcare study. A lot to be learned there.

  41. Hi Michael, I vote for the Big Data Disease Management Study

  42. Thanks for voting Hassan.

  43. Big Data Disease Managemen

  44. Thanks Vladan.

    Yes, this will be the final vote for 2015. Later in the year we will release the schedule for 2016 and you can vote for that year.


  45. My vote goes to Big Data study. As Xiaofei mentioned, transferability of analysis is what makes it so attractive. In addition, I haven’t found many resources of how big data analysis is used in consulting project (compared to Operations and BTO), so looking forward to seeing it in this format.

    Michael, is this the final voting to establish the order for all the studies proposed?

  46. Thanks Xiaofei – your vote is noted.

  47. Thank you for the clarification, Michael.

    What goes through the minds of top executives, especially at a turbulent time, would be a rare and valuable insight. Please definitely share with us that part of the study!

  48. Hi Xiaofei,

    Great to hear from you again. Your vote is counted!

    The Ops, BTO and Big Data studies are all competing to be the 4th study for 2015. Of the two studies not selected for 2015, both will be moved to 2016. So we will do them all eventually.

    The leadership program/study is a straight vote. It is not competing with anything. Since we are already doing the leadership work on our current studies we are simply deciding if we should share it. Voting for the leadership work does not knock out any of the other studies!

    So Ops, BTO and Big Data are competing for one spot this year.

    Hope that helps.


  49. All of these studies sound very interesting!

    I will add one vote for the big data study. The comments below by Jen, Michael and Brian have explained how it would be very beneficial to the healthcare industry. And I will add to that: “big data” as a means to analyze correlation between components is transferable to many other fields, such as forensics, marketing, even terrorism. It’s fascinating. It would be great to see its power in an actual study.

    Also have a question for Michael – are the 3 studies (Operations, BTO, big data) competing for one spot, and the other spot is for the leadership study? Or are you considering possibly picking 2 studies out of Operations, BTO, big data?

  50. Great points Brian.

    Big Data looks at correlations and never looks at causality, as you point out. We hope to merge both.

    I will add that we will do all the studies. These votes are simply about prioritizing when we will do them, though we will get to them all eventually.


  51. Jen and Michael,
    It is interesting that you mention that people think that what goes on in healthcare is not relevant to them. I would flip that on its head. Most people in the healthcare industry (pharma, biotech, med device, providers, reference labs, insurers) seem to think that the industry is so unique that any ideas from outside the industry can’t work. That is not true, but that has been my experience.
    As for the comparison between health care systems in Canada and the US, the NEBR paper is interesting though I do not know if I would put much stock in regression models that explain anywhere from 4%-to 20% of the variation in the data.
    The problems with the US health care system are structural and are due in part to companies profiting from the inefficiencies in the system(Health Insurers for one). Also, there are legislative restraints which allow pharma companies to charge the prices they do in the US for medicines. That is a problem in and of itself.
    Can the use of statistical methods(At the end of the day, “big data” is just applying computational brute force and statistical methods to large data sets) help with determining outcomes? Yes, it would and it definitely should be pursued. Will it help make the approval process faster? I do not know. It will help the folks at CDER(FDA) make better decisions and it will help companies streamline the drug development process by pursuing more favorable targets. That is for sure.

    Michael, I would certainly like to see both an operations project and the health care study done. From the standpoint of educating myself on how consulting projects are performed and learning the methods, both are important. If the health care project ends up “winning” and performed this year rather than the operations study, I would not be disappointed. It is a win-win situation.

  52. Hi Michael, a vote for the big data study, eager to see how big data can revolutionize disease management!

  53. Thanks Jen,

    You hit it on the head. All the legislation exists to support treatment which works. The point if this study is that we really do not know which treatments work and which do not since we have never properly analyzed the outcomes.

    That ability to analyze the outcomes is relevant everywhere, irrespective of the payment model used.


  54. Brian, if I may offer a follow-up explanation to Michael’s regarding universal applicability.
    You rightfully pointed out the difference between single payer, publicly-funded healthcare systems in the UK and Canada and multipayer systems with a large private component in the US. Thing is, the jury is still out on which of these two systems provide better health outcomes:

    Yet, payers are just one stakeholder in healthcare. Let’s look at disease management from the perspective of another important stakeholder – pharmaceutical companies. The US dominates the global drug market with ~35% market share. Every pharma company in the world assumes the cost, risk, and time investment of drug development with the goal of marketing their products in the US where they can command prices that are unattainable in any other country. Yes, companies might start out seeking EU or Japanese approval, but the US FDA is end game. As described in my earlier comment, the FDA is unnecessarily complicated because we are not leveraging technology to make data-driven assessments of health outcomes beyond the rudimentary criteria of safety and efficacy. Big data will enable a holistic and objective definition of health outcomes, which will in turn ensure that patients across the world receive the treatment they need at the right time and cost.

    The UK’s NICE pioneered cost-effectiveness which compares potential treatments head to head with existing standards of care. But how do we know that the metrics upon which the existing standard was evaluated still holds, 10 years from its approval? Patients who have taken the standard for the last 10 years are scattered around the world, but our existing technologies do not allow us to follow the multifactorial “patient experience”, to develop a true outcome measure for existing treatments, and a benchmark for potential ones.

    The US isn’t getting it right, and since companies go where the money goes, a patient in the UK or Canada, or the developing world for that matter, would not get a dire treatment for their condition if pharma companies judge that condition to be commercially unviable in the US due to regulatory hurdles, market access constraints, etc. So without knowing where this disease management study is based, I know for sure that it would be relevant to the US, and by extension, the rest of the world.


  55. Hi Brian,

    Not disappointed but I think the healthcare study can teach more practical skills. So I think many readers see the word “healthcare” and they think it is not relevant to them, though the skills are directly relevant to everyone.

    The work would still be relevant to nationalized systems since those systems all have payment caps based on the usefulness of a treatment and we are basically trying to determine the usefulness of a treatment. Although, this is such early days for that study, this objective may change.

    Even if the study was not beneficial to the nationalized healthcare systems, only about 700MM of the world belongs to some form of a national system so the relevance to the rest of the world is massive.


  56. Thanks Utkarsh.

  57. Hi Michael,
    I would love to see a detailed study on healthcare, this I think is an relatively less explored area and detailed study will surely help everyone understand the structure well.


  58. Hi Michael,
    You seem disappointed that people are picking the operations study. Why?
    With the healthcare study, how would the results of the study benefit more nationalized systems such as the UK or in Canada?

  59. Healthcare study, please :).

  60. Thanks Brian. And yet another vote for the operations study.

  61. Hi Michael,
    I would like to see how you handle leadership issues. At the end of the day, it is people that make businesses go. I would also like to see how you handle an operations study and make that the last study of the year.
    The healthcare study would be a great way to kick off 2016. It is an important issue, and we get to see if, and how well, sophisticated analytic methods can be integrated with how tier 1 consultants solve problems.

  62. The vote is noted Van.

    The healthcare study is still way behind the Ops and BTO studies.

    We need more enthusiasm for this study if we are to see it through. Where are all the healthcare PhD’s and doctors?


  63. I would vote for the Big Data Disease Management study.

  64. Absolutely, Michael!

    Also happy to see that we don’t have to choose between it and the leadership development study. I’d still pick healthcare but it’s nice to have our cake and eat it 🙂

  65. Thanks Jen. Does that mean you are voting for the study? I was not entirely sure…


  66. Finally, a study on healthcare!

    The high and rising costs of healthcare has been well documented. The 3 P’s – Payers, Providers, and Patients are in dire need of an alternative. However they can’t agree on a viable alternative as each cost-cutting option is essentially a zero-sum game. A breast cancer patient needs that $300K/year monoclonal antibody really badly. No insurer wants to pay for it because it improves progression-free survival but not overall survival. Her physician can’t determine for certain that a $2000 generic drug that worked in ovarian cancer will work for her. But his gut feeling, her biomarkers, and her genetic traits suggest it would. The FDA doesn’t have enough retrospective trials showing it will work, or that it’s safe in breast cancer patients. They need a prospective trial to be convinced.. The pharma company says it will skip Phases 1 and 2, and run a giant Phase 3 which will cost $100M. To justify that investment, the repurposed generic will develop a magical patent that would justify a $90K/year price. Insurers balk. The media says Big Pharma is evil. The patient dies. Everyone loses. Rinse and Repeat. This is essentially US healthcare today – we lack interconnectivity among the respective stakeholders who are fighting to protect their individual interests. This made possible by you guessed it – lack of data. Which is made possible by dinosaur-era technologies across the healthcare ecosystem. End result is different stakeholders pulling data out of thin air to justify anything.

    At 17% of the 2014 US GDP, these astronomical healthcare costs are unsustainable. Big Data is here. The Internet of Things is here. We don’t need that much of a “disruption”. Just a good ole application of existing tools anda healthy dose of common sense to this slow-moving, age-defying mamoth of an industry.

    Thanks, Michael!

  67. Hi Van,

    Thanks for the comments.

    You can pick the leadership training + one study. We have the capacity to do both. So let me know which study you want to wait with the leadership study.


  68. Although I find the Disease Management Study very interesting, I think the leadership study should be the priority. It would give an insight into what it really means to be an executive. Furthermore, since leadership in consulting is defined from the perspective of an executive, it would give aspiring consultants or industry professionals a structure to guide their own leadership development/skills.

  69. Thanks Martin. Good point.

  70. Thanks Mat.

    Great criteria.

    I think the one thing to keep in mind is that we would keep the disease management study very practical if we did it. We would do it in such a way that you could follow each step and understand the analyses engine we built. We would want you to replicate what we did.

    On the 3rd criteria, there is no question the disease management study is far more complex. It has not been done yet.

    We will ensure we do not take on too much if we chose to go ahead.


  71. Michael,
    thanks for this update. I’m glad to hear things are going according to schedules!

    As for the last study, I think the Big Data Disease Study deserves the last spot for 2015.

    Why is that? I’d say there are several key criteria here. First, which of these studies is of a greatest importance to your customers: aspiring consultants and consultants – i.e. all of our FC community? The chance is, that both Disease Study and IT Strategy will be having the most educational value to subscribers. The first one, by applying concepts previously not used in Healthcare, the latter by being more likely an assignment one can be doing – thus having a lot of practical value.

    Second criteria is, how current a study theme is. Both studies go hand in hand here, one touching upon technology, another on big data.

    The deciding point then, is the third criterion: the importance of the issue to solve. And here the Disease Study wins, as helping to solve a healthcare problem is more likely to have a significant impact on people’s lives. It is also better aligned with FC values, and its ambition to solve toughest problems, as in Power Study example.

    For the behind the scenes leadership work, it would be very interesting to see it. But FC has already a stretching plan for 2015, so I worry having another initiative can divert focus and energy from the ones that it has already committed to.


  72. Michael –
    Learning more about career management is definitely an area of interest for me. My plan is to do 3-4 years in consulting before transitioning back into industry; I imagine that my life priorities will change by then (e.g., more focus on family, work-life balance, etc.), but can better career management extend my consulting tenure? Perhaps.


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