Grab your Popcorn…Things are about to get really weird

9 12 2010

There are things you hope never happen to your business, some you even discuss and prepare against. And then it happens just like you planned: a rogue employee for the US government slips a little known website confidential material and suddenly, all heck breaks loose.

This example seems like a Hollywood sci-fi show, yet the effects and impact are played out in reality and cost innocent bystanders money.  What started with Julian Assange posting a few things have spiraled towards a digital Armageddon.  First was a smear campaign against Assange; true or not, things were leaked to damage his reputation. Then, those hosting WikiLeaks were pressured. It worked, and like a good fighter, he took the punch, regrouped, and counter-punched.  We know the story, it has been the same through time. All of a sudden he is seen as an underdog, and the following starts. He becomes the flag-bearer for those oppressed and in the shadows, who then rise up to support their black knight. And all of a sudden, businesses involved in some way are attacked.

So buy your “Go WikiLeaks Go!” tshirt (you knew someone had to make a t-shirt), grab your popcorn, and get ready for the show – this one is just starting up.  And I have a strange feeling Assange might be saving his best for last.

For those of you playing the home version…click here for a link to the Google news thread on WikiLeaks.

While you are at it, you might have a discussion about what would happen if your website is attacked.





Visualization Methods

14 10 2010

I thought this was worth sharing….Periodic Table of Visualization Methods.  This is a nice visualization of the different types of visualization.  It shows some good examples, and some not so good examples of visualization. Make sure you mouse over the different elements.

Rules of visualization designed to create action:

  1. Keep it simple, clear, and concise – with the emphasis on simple.  Don’t use complex charts to explain simple ideas.
  2. Know your audience.  Don’t present glorious details of each step in the analytical process to executives – trust me, they don’t care.
  3. Find a chart style that works well with the data.  Line charts show historical trending, bars charts do a better job of showing relativity.
  4. Don’t use 10 charts when 1 could suffice.
  5. Label well.  Take the time to make sure all of the information is explained.  The last thing you want to happen is for someone to look at it and say “what does it mean?”
  6. Understand there is a difference in analysis and presentation.  If you are trying to convince someone to act, then make sure the data (and you) tell the story.
  7. Start with the big picture, then explain (if necessary) how you got there.  People learn by seeing the picture first, then seeing how the parts go together.
  8. Document your assumptions.
  9. Explain your conclusions, don’t expect your audience to jump to the same answer.
  10. Highlight the relevant points within the data that augment your argument – use a color scheme that calls out the item if you can (red bars vs gray).  Do not be afraid to use the power of a printed report and some hand written notes with arrows to the corresponding areas.
  11. Understand where and why the data does not support your conclusions.  Be prepared to defend against those points, because your audience will likely be looking for ways to contest your conclusions.
  12. Practice what you want to say.  The more proficient you sound the more convincing you will be.




Flakes…not just for breakfast anymore

5 10 2010

Carbon Flakes (aka graphene) just earned a pair of University of Manchester students $1.4 million, oh and the Nobel prize.  Think nanometer material that is unbelievably strong (Wikipedia).

While we might be a few years off, there is certainly some potential to see new paradigm shifts in certain markets:

  • What could a light weight, strong coating do to the car market where weight and MPG are inversely related?
  • What could it mean to the military in terms of personnel and vehicle armor?
  • What could it do to clothing?
  • How about kitchen materials?
  • How about computer components?
  • Plastics?

If you believe this could impact your products, your market, what would you do?  When would you need to start thinking about it?  How do you discuss items that might change your space?





The end of Blockbusters…

23 09 2010

OK, well it is potentially the end of Blockbuster Inc.  This morning Blockbuster filed for chapter 11 protection.  It is a great example of the Risk of being the market leader.  They owned the market, they were on top of the world.  I am sure during their heyday money was being thrown all over the place.

I would love to hear these questions answered:

The trap of leadership is that you often have to wait and see the result.  You are often not allowed to change your business model until it is too late.  If you change it when you probably need to and a loss occurs, then everyone loses their jobs.  The analysts would quickly call out leadership saying that they lost market share because of the business model shift.  Even it is was a great move that would ultimately save the company, our short term focus is entirely too great.

It is also difficult to understand the nature of the perceived threat.  I am sure there were a couple of times when Management said “what do we do about NetFlix and the changes in the market?”  I would guess that 10% market share did not scare anyone, nor 20%.  Yet, at this point there was too much momentum.

As leaders, when do we act?

If we react too soon, we risk looking prone to panic.  We can always explain it easier after the fact.  Our egos, politics in general, and concern about saving face probably drive more decisions than anyone would ever want to admit.

All to often we push harder on marketing and sales to cover shortfalls in market share.  I would be willing to bet that the company spent more time creating sales spiffs and getting creative in terms of finances, than investing in new business models.  What this leads to is a further entrenchment into the business model, a “we can weather this storm” mentality.

I wonder what would have happened if they would have set hard targets in terms of driving action.  What if they would have said “once our market share slips by 10%, I want a meeting where we come up with 5 new business models”.  We are just not trained to think about creating very specific action.

We ponder and delay (then get out and let someone else handle the mess).





Advanced Analytics

22 03 2010

A major item organizations grapple with is the concept of advanced analytics.  They want it, but have little idea how to use the various tools to make it happen.  Unfortunately too much information often blurs the lines.

For example, I watched a sales presentation on Predictive Analytics where the key outcome showed how to build databases with the tool yet almost completely missed the fact that the real benefit should have been something like “we were able identify two segments to target a marketing program for more effectiveness.  Instead of spending $500k on a generic campaign we were able to identify key attributes that drove increased customer interaction and focus the campaign to only $200k on those segments.”

Why is this? The primary reason is we do not truly understand the tools and how best to use them.  A Swiss army knife is not good for home repair, but is the perfect tool to throw in a hockey bag, or car trunk for occasional use as a widget to get you out of a jam – a screw needs to be tightened, a shoelace needs to be cut, or an apple peeled.  We need to understand which tool to use in the most appropriate situation instead of thinking of various tools as universal.

Business Intelligence, Planning, What-If Scenario Tools, Optimization, Dashboarding, Scorecarding, Cubes, Cluster Analysis, Predictive Analytics are all different tools for vastly separate purposes yet have similar uses.

Advanced Analytical Tools

Here are the core elements of Advanced Analytical tools:

  • Business Intelligence – great for creating an enterprise-wide, data visualization platform.   If you do this right, you should create a single version of the truth for various terms within an organization.  It should enable better reporting consistency standards for the organization.  In the end, it reports what the data says.
    • Scorecard & Dashboards – These are primarily BI tools that have a more organized or structured methodology for presenting ideally the Key Performance Indicators.  These are great tools, but to be most effective, they need a specific purpose that is highly integrated into a management process.
  • Enterprise Scenario Planning – Most enterprise planning exercises are giant what-if scenarios that try to plan out financial outcomes based on a series of drivers (employees, widgets, sales reps, etc.).  We build out plans based on a number of assumptions, like the average sales rep drives $2mil in business, or benefit costs for the year are going to be #of employees * average salary * 2.  We do this primarily to lay out a game plan for the year and we do it as part of an annual or rolling cycle.
  • Tactical or Ad-Hoc What-if Scenario Analysis – Besides the full scale project we do to plan out the company’s cash outlays, we also do a significant amount of smaller, typically tactical “what-if” scenario tests.  This is traditionally done in Microsoft Excel.  We dump a bit of data into excel, make a number of assumptions and try to build out likely scenarios.  For example, “if we were to create a customer loyalty program, what would be the cost and a likely reward.”  We are doing this to test ideas, so yes it might be ideal to bolt those into the Enterprise planning tool, but it typically takes too much overhead.  It is easier to just get something done quickly, then make a go/no go decision.
    • Data Visualization can also be a great help with this – to bolt on a couple of reports to see the data and how different scenarios impact the various facts and dimensions.  This can help us with our conclusions and recommendations.
  • Predictive Analytics – This tool is best used when we have historical data, or representative data set and we want to make a conclusion based on mathematics.   The key is math.  This is not guessing, it is improving the chances of being right with math, or a structured approach to remove risk from decision making.  With a planning tool, we primarily use assumptions to create plans.  We cannot use predictive analytics for all decisions, but for a few specific types of decisions:
    • What transaction details and customer insight can we use to determine credit card fraud?
    • What customer attributes create our buying segments?
    • Which customers are most likely to abandon our offering?
    • What products are most often purchased together?
    • Which taxpayers most likely need to be audited?
  • Optimization Analytics – This is perhaps the most specific advanced analytics tool when looking to solve the specific business question: “With the given parameters of these trade-offs, which mix of resources creates the most effective (or efficient) use of those resources?” This helps make decisions around production locations and product investment.  Like predicative analytics, it is mathematically based (though you may need to make a couple of assumptions as well) in how it determines the answer.

Advanced Analysts

Another reason we lack understanding is analysts.  Our analysts are commonly from the IT team, trained in data structures, or from the finance team, trained in accounting.  Neither is wrong, they just have a default mindset that falls back on using the tool they best know.  This lacks the business/statistical trained person who can both layout the hypothesis and, more importantly, explain the results.

We do not want correlation explained in R-squared values, “63% of the variation of the data is explained by our independent variables.”  While this may make sense to other statisticians and mathematicians, it is lost on the business.   One key value of using a math-based concept is that the explanation should sound more like, “We have found a way to decrease fraud by 3.2%, which should result in a $576K return to the business every quarter” or “We have tested our marketing campaigns and have found three segments that are 25% more likely to purchase based on the campaign, which should result in a payback period of 3 months.”

The right tool with the right skill set is imperative to successfully using advanced analytics.  We also need the discipline to have the right people using the right tools for the right information to drive action.  If you have an algorithm that predicts customer defection, you need to use it and test the results.  It is never going to be perfect, but in most cases, you can bet it will be better than not using it at all.





Meeting Expectations

18 01 2010

In a recent MyMidwest (Midwest Airlines) inflight magazine there is a story by Kimberly Douglas of FireFly Facilitation on Meeting Management.  If we look at a couple of the numbers from Douglas’ research we can begin to quantify the impact of meetings.

38,000 msft employees say that their 5.6 hours per week spent in meetings are unproductive.  That’s over 11 million hours of meetings.  Now if we say the average msft employee makes 100k per year (including benefits), that translates to ~ $50/hr.  If we do the math, that’s ~ $550 million a year in meeting costs.

Microsoft’s 2009 annual income was $58.4 billion which makes just their meeting costs roughly 1% of their annual income.  Let’s make a couple more assumptions: that half of that value is waste (more people than needed, run longer than necessary, etc) and we could reduce that by 10% which should be easy.  The result is ~ $22.5 million.  I am guessing here, but it should be worthwhile to at least try and improve upon meeting management and find some other way to leverage that $22 million.

  • What % of time do you spend in meetings?
  • Would your employees feel that meeting management and effectiveness could be improved upon?
  • What would you do with an additional 1% of your annual income?
  • In what ways could you improve meeting management?




Can we learn from Mite Hockey?

30 12 2009

In youth hockey, the youngest  group (6-8 year olds) is called mites.  Watching a mite hockey game, especially with the players in their first games, is a unique experience.  Watching a kid on a breakaway is everything, an amalgam of excitement, anticipation, worry, dread.  You feel like you can chew off all your fingernails from the time the play starts to when the play ends.

Why? Purely the speed in which the play happens.  It takes too long.

Think about the speed of change within an organization.  If it takes too long, it probably doesn’t happen.  We talk about burning platforms, or Machiavellian-like beheadings.  Employees don’t like change, but what they really don’t like is the not knowing what the other side will look like.  So why do we draw this stage out?

  • Why do we take forever to move some projects?
  • Why do we announce reorganizations, and then take months to make it happen?
  • How much artificial time do we add to a number of the things we do, and what is the value of that time?
  • What is the impact if act twice as quickly as the day before?

If you need to get something done, get the right minds on it, have a discussion and be done with it.