Survival of Innovation

31 08 2009

In 1988 Pinnacle Brands broke into the baseball card market.  The market had long been dominated by a couple of players (Topps,  Donruss, and Fleer) and the market was doing fairly well.  It catapulted onto the scene by throwing in new features to the market, more colorful cards, full edge bleeds, more information, etc with their Score brand.  Over time they added in brand variations that were targeted at very specific markets:

  • Score:  Lower price point, more kid friendly
  • Select:  Mid price point, geared for the beginning collector
  • Pinnacle:  Higher price point for the more serious collector

If you followed the baseball card market at that time you will remember it as a rather unique time.  It was perfect example for economists.  The value of each card, pack, box was independently valued by third parties.  Card shops popped up in nearly every neighborhood to trade cards, and serious collectors were following the distribution trucks buying entire cases at a time before they even hit the shelves.  The catch was that you could not make all the cards you wanted.  The more you made the less you sold, and vice versa.

One of the main things that happened was the wrong sales mentality.  What made them successful, new  innovation, also hurt them.  They tried to stack the cards to the ceiling and create a consumer good mentality, not realizing the principal that the card would really only sell if they kept product very limited.

Hindsight being perfect (still a good lesson none the less) they should have kept production runs low, elevating the brand and looked for other ways to extend the brand.  As a last change, they started to get into other types of cards.  I think in the beginning they had the brains to come up with demand creation card games like today’s Pokeman genre.

Upper Deck came along in the same year and appears to be the leader in the field today.  Usually someone is going to survive, are you doing everything you can to make sure it is you?





Design for Information

4 08 2009

All to often reports are designed to provide data, not information.  There are charts and tables with little intrepretation, or description.  While I am not great fan of PowerPoint, it can often make up for Enterprise BI limitations.  We can call out certain areas within the charts and graphs, as well as add the commentary to help us communicate our point.

A safe assumption is that the person reading the report will not have the same understanding of the material as the report designer, or analyst.  It is then our job to make sure that the report communicates the point clearly.  The last thing you want is to hear “what are you trying to show me?”

Below is a good example of presenting data, while not telling us much.  Here we see that he/she has a few fans that are frequent contributors, and that tweet volume picks up around the lunch hour.  There is not much variation for the days of the week, with a little drop off for the weekend.  August is also the most popular month.

twitter2008-1

What would be helpful to know is why this data is important to us.  What perhaps would be the most important is to know the subject material, so we could do things like tweet just before lunch as that seems to be the most popular time to inspire reaction.  Or that August tweets were up due to an embarassing grammatical error.

As we are designing reports, make sure that the information has a purpose.  Most specifically, know the audience and know the potential actions the information is going to inspire.





Supply Chain Profits

7 07 2009

In terms of delivering goods or services to the consumer, the supply chain is not created equally.  More often than not, one part in the chain controls the bulk of the profits.  How did they get there?  They most likely earned it (though there are some interesting examples of other methods).  They have the power in chain to manipulate and control the negotiations.  They are the perceived value provider.

  • Where do you stand in terms of delivering value to the consumer?
  • What do the other parts in the supply chain offer in terms of value?
  • Can this chain be altered either from someone in the chain, or perhaps a whole new value chain?
  • What are your relations with the people in control, or with the entire chain?

Depending upon your business model, this could be a potential opportunity or threat.  We need to understand our position in the supply (or value) chain and if the position is changing.  We may not need to do it constantly, but we need to make sure someone owns the process and it is built into an ongoing management discussion.  At the very least it should be part of the strategy development plan.





Key Risk Indicator (KRI): Customer Abandonment

1 07 2009

How often do you look at the indicators that a customer is thinking about leaving you?  Do you have a process around this, or do find yourself saying “why did this customer leave us?”

What are the possible indicators for a customer leaving:

  • Time between purchases
  • Decrease in volume
  • Time to Pay bills
  • Increase/decrease in calls to customer servicce
  • Temperature of calls into customer service
  • Longer sales cycles
  • Time between customer visits

Some of these may be difficult to quantify, but are well worth understanding.  I would venture a guess the cost to replace that customer (including lost opportunity value) is less than the effort to put a process into discussing customer abandonment.

If you have stories on how you track customers, or customers you lost and how you should have known, please share them.





Business Modeling

30 06 2009

We spend a tremendous amount of resources on preparing financial models for the company.  Which is absolutely necessary, but we also need to model the operations as well.  For example, if we model the customer lifecycle we can begin to better understand each of the subprocesses within.

This leads to many different insights into the business:

  • Critical transition points within the process – target higher impact performance areas
  • Segment the customer by value – thus better alignment of product and services
  • Better communication of value to stakeholders
  • Enhanced sales negotiation

If we can build the formula around each of the key business processes, then we are providing more tools for the organization to use to focus resources and priorities.





Data Warehouse Design

24 06 2009

One of the main problems with Data Warehouses is that they are designed to answer any question.  The problem is that they usually fail to answer the one someone is asking.  DWs are usually good for referencial information – meaning I can answer questions like “how many customers do we have that have spent over $100,000” or “which customers bought the blue widget.”

There are a number of points of failure that hamper DW projects:

  • They are usually complex and very costly
  • The business changes (regions, product lines, sales heirarchies, etc) in the middle of the process
  • The end use is not well defined
  • Lack of analytical skill and knowledge of data structure in the business users to get the right data
  • The end result is too complex for the users to understand where to go to get the right information
  • No one tells the organization “thou shalt” use the data warehouse – so people get data from all different sources making a common version of the truth difficult to get to
  • There are often no rules of engagement for how to use the environment, or data in general

If organizations only use 6-10% of the data they collect, how do you design the DW for greater adoption?

For starters, understand the common business questions and the potential levers that can be pulled. For example, one of the areas that always surprises me is the lack of information around the success of marketing campaigns. Marketing campaigns and price are really the only levers we can pull in the short term to increase revenues. What we often fall back to is the sales whip – where we put more pressure on the sales team to perform. This is a strategy of hope (which is not a recognized as a successful strategy practice). We apply the pressure without providing much in the terms of support.

Instead let’s say we are ending the 3rd quarter and our numbers are a little behind and the pipeline is not as strong as we would like.  We know we have some time, but the programs have to be very tactical to find low hanging fruit. Instead of reviewing the potential marketing programs or trying something new, we cross our fingers and yell at the sales team. We could cull the DW to find large groups of customers who had not bought specific groups of products and offer incentives for them to buy.  We could identify the groups/verticals of customers with the shortest sales cycle and build a promotion and program for them as well.

Yet why do we not do this…we typically lack the information in a format we can use in a timely manner.

So if we design the data warehouse (or perhaps data marts) around specific business levers we stand a better chance of answering the one question we need. We just might trigger some very interesting questions about our business.






KPI Design: Better than average

16 06 2009

In the June 1st issue of ESPN Magazine there was an interesting story about Rafael Nadal.  In the story there is a call out with some interesting facts about his play.  One of the items is his rotations per ground stroke versus the average pro.

Nadal Math Smaller
While this is fanatastic information to explain why he is better than average, what might have been more relevant to the article which is about his excellence would be to compare him versus the other top players.  What if all the top players are hitting at 5,000-6,000 rotations per ground stroke?

As we are designing KPIs and targets we need to make sure we are measuring against a relevant target, not just an industry average.





KPI Library: Profit per Employee

14 06 2009

If you are looking for a productivity or effectiveness KPI, a sure place to start is revenue per employee (unless you are in the public sector).

  • It is a straight forward calaculation
  • It is easy for every employee to get their heads around
  • It is a measure of scalability
  • It is a crtical measure for long term success
  • It triggers great conversations about the health and direction of the company

It has one primary weakness in that it is a lagging indicator.

Similar metrics to this are Revenue per Employee, Expense per Employee, Expense per Sale, Profit per Transaction, Profit per Customer.