When More is much, much Less

2 08 2011

Recently I was cleaning up my Gmail inbox and it was clear to me that some people treat email like free marketing.  For example, Dick’s Sporting Goods was sending me 3-4 emails a week.  While I shop at Dick’s Sporting Goods and like the brand, it was very clear to me that they really weren’t paying attention.  My lack of response, nor opening of any emails should have been a trigger to them.  More was much, much less.  They were not alone, but one of the worst examples of over-communication.

Thoughts for email marketing:

  • Use the information effectively.  Not only have I asked them to stop emailing me all together, they have hurt their brand standing with me.
  • Test your campaigns.  Because they are free doesn’t mean everyone should get everything.  That’s just laziness.  There are too many tools out there not to be able to do some type of segmentation based upon gender, usage patterns, social, and economic demographics.
  • Learn! This is probably the most important aspect.  If a customer gives you their email address, then treat it like a valuable asset and learn from it.  It is not a resource to be used up.  Offer different things at different times, send emails in different patterns, send different offers and test the response.  And if they don’t respond to anything, pull back and wait.

I know this sounds way too obvious, but here is an example from someone with the size and clout to know better.  Chances are your marketing organization is overusing their free marketing channel and just don’t know it yet.  Go ask them for an analysis of how many emails are being sent out to each customer segment each week.  Ask them how often they clean up their contact list to trim out people who have never responded. And wait for the dreaded, “we don’t want to skip anyone in case this is the campaign that will get their attention.”  Trust me, there is a breaking point.

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Categories : Actionable Information, Analytics, Analytics & Business Intelligence, Communication, Customer Value

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.

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Categories : Actionable Information, Analytics, Communication, Culture of Action, Process Improvement, Visualization

Analytics Process

23 11 2009

Over the last couple of months I have been writing about a handful of US Economic Indicators.  While I have reviewed these over the last few years of my life, I had not done so on a regular basis.  This inconsistent and let’s call it a casual curiosity lead to never really understanding the implications behind the numbers.  Sure I could talk about them, but I could not leverage them.  While not an expert by any means, I can see a lot more now than I did when I started this blog series.

This is similar to ad-hoc analysis without purpose.  We do something once and create a little hype.  When we don’t have any vehicle to take advantage of the newly found ideas, the idea dies as does the learning.

Think about the process of how you handle ad-hoc analytics within your organization:

  • Do you have the right minds constantly looking for new issues?
  • Or, do you put the right minds on solving issues when they arise?
  • Can you name your best analytical minds?  Are they assigned to thought leadership and problem solving?
  • Do you use your analytical minds to challenge the knowledge levels of others?
  • How do you foster new thinking?

 

Consistency breeds familiarity, and familiarity breeds knowledge


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Categories : Actionable Information, Analytics, Change Management, Communication, Culture of Action, Innovation, Performance Management

Snowblowers and investing in tools

24 08 2009

How often do parents buy snowblowers right after their kids leave the nest?

Good employees often understand the tools they need to best do their jobs.  Good analytical minds usually look for different ways to extract new information out of large data sets.  This requires access to new tools, frameworks, and methodologies.  If we are not reinvesting in improving our analyical capabilities, we risk losing our best people as they quest other ways to challenge themselves.  We are then required to invest in the tools we declined to compensate for a loss of analytical brain power.

Instead of purchasing tools after a star analyst leaves, we need to find fresh ways to challenge analytical minds.  We can do a much better job of pointing people in new directions, or finding new ways to derive value.  Otherwise, we’re left investing in expensive equipment to do necessary tasks.


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Categories : Actionable Information, Analytics & Business Intelligence, Change Management, Communication, Incentive Alignment, Process Improvement

Analytics & Actionable Information

5 03 2009

I work on many projects where the outcome is  “just provide us actionable information.” While this is always the goal, I find most people use the term quite loosely, as if it were merely an additional option. In reality this is quite difficult to create. Many things need to come together to create action, and it is far more than just information or a report.

To create effective actionable information, we need to integrate people, information, and tools. We also need to have the right skills at different times. All too often, the expectation is for IT to write a single report that will answer all questions. Yet, what typically happens is the report creates more questions as IT cannot predict every need. All this has done is create more activity for IT and delayed action.

Let’s view this from a process point of view…how would it look:

First, we have a tremendous amount of data. And it would be easy to argue way too much data, hence the need to create layers of relevance. How often do we get lost looking for what we need, or recreate something because we don’t understand the business rules of the data we find? This wasted effort costs the business money and time.

We have the information, now we need a good analytical mind to review the data to create analytical models or what-if scenarios. What typically happens here is a finance or IT analyst runs a few numbers. This is probably OK for many instances, but the best option would be both a mind of the business as well as a statistical curiosity (though at this stage we need more of a statistician). IT and Finance often lack both of these to some degree – as their primarily skill is data or fiscal governance.

Now we have some level of analytical information, but still have work to do. In general, the statistical mind tries to cram in too much detail and wants to discuss the process of discovery, instead of the finding. To transform analytical information into action, we need the business to present the finding in executive terms – value created. The presentation is more than likely to include multiple reports, synthesized into a couple charts. The next step is to foster a discussion of the recommendations and potential options. The discussion will focus on gathering feedback and coalescing them into an agreed upon plan.

It is common here for people not to feel comfortable with the information and ask for additional information and analysis, but we need to fight the urge to delay and put the best foot forward. There will be times when the need for rework is great, but if the discussion includes the right people and the facts then there should be enough to make a decision and move forward. Otherwise, the risk is creating a culture of endless analysis.


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Categories : Actionable Information, Analytics & Business Intelligence