29 January 2010

Business Intelligence and “Tribal Knowledge” – Part 1

Recently I was working with a client and, at the opening of the meeting, I asked the six members of their management team who were gathered around the table the following simple question: "What is keeping your from making more money tomorrow than you're making today?"

Their responses were telling: (approximate quotations)

  1. "We don't understand our customers: Who is buying, why they buy, or how they go about the process of getting a purchase authorized."
  2. "The amount of time it takes us to respond to a lead or prospect. We might get 20 to 300 leads from a trade show, but it might takes us three weeks to six months to get back to them after the leads have gone through all the hands and processes in our organization."
  3. "We don't have a good way to turn the data we possess into information that would be valuable for decision-making."
  4. "We don't have a good way to classify accounts in our customer relationship management (CRM) software so we know how to best approach them regarding our products and services."
  5. "We don't understand the secondary participants involved in our sales process with a prospect."
  6. "Our customers lack the funds to buy our products."
What is interesting about this is that, if we take number 2 out of the mix (this is clearly a policy constraint) the other five responses all have to do with "business intelligence." These folks needed to understand their customers better in virtually every aspect.

Now, in their defense, this firm has a fairly complex sales cycle with, potentially, a number of different parties involved. Here's a brief description of the participants and their relationship to the sales process:

  • School District – Usually, it is the school district that will end up "owning" the product after purchase. Frequently it is at the district level, as well, that the purchase commitment must be authorized.
  • School(s) – The individual schools and school administrators may have an impact on the purchase decision. The school(s) must be willing to take on the product before the school district will authorize the purchase, even if the teacher may have convinced the district administrator and board that it is the right way to go.
  • Teacher(s) – Teachers function mostly as influencers and catalysts to the sale. The teachers often are sold on the product and then become an advocate to aid in getting the product approved at the school and district levels.
  • School District IT Department – Since the products generally involve technology, it is not uncommon for the schools' or the district's IT departments to have de facto veto power over any pending purchase of such technology.
  • Government Programs – Since most of the schools in the U.S. are publicly funded, the funding for many of the purchases flows directly or indirectly from some government program. Such programs often set requirements and seem to have a never-ending series of "hoops" that must be jumped through before funds are made accessible for specific purchases.
  • NFP or Other Sponsor – When the school districts' ability to access funds for a desired product purchase falls short, sometimes not-for-profit (NFP) organizations become a supplemental source of funds. Sometimes, it is even the NFP, seeking a place for its funds in community projects, that becomes the initiator of the whole process. Other times, the interested teacher may know that the school or school district have no money for the purchase, so he or she will seek aid from a NFP organization simultaneous with presenting the matter to the school and district decision-makers.
As you can see, with all of these participants, and no single path for each approach, it is understandable that this organization is discovering some challenges in "understanding" their customers. Add to this the fact that their business itself was changing. They were diversifying from the product around which the business had originally been built – beginning to sell a broader range of related products into the same marketplace.

Tools at their disposal

Now, this firm does have some tools at their fingertips. They purchase the use of data made available from a data aggregator that provides a database of schools, school districts and related parties. Some demographic data is included.

Now, I am not privy to exactly what demographic data is available to them – our discussions didn't go to that level. However, for the sake of this discussion, let us say that they have just the following data points for each school and district (in additional to standard data like addresses, phone numbers, and so forth):

  • ZIP code
  • Number of students
  • Number of teachers
Using a tool as rudimentary as Microsoft Excel's OLAP capabilities, it would be relatively easy to spot correlations in the data between product sales (by dollar or by units) and these demographic characteristics:

  • Which regions of the country account for the most sales? The least sales?
    • Using the first digits in the ZIP Code gives you 10 regions automatically
    • Using the first three digits in the ZIP Code gives you a breakdown by what the USPS call SCF (Sectional Center Facility)
  • Which states account for the most sales? The least sales?
  • Which cities account for the most sales? The least sales?
  • Which districts produce the highest ratio of unit sales to students? Which ones have the lowest ratio? What about the unit-to-teacher ratio?
My guess is, if they had graphs of these data – especially TOP and BOTTOM data – their sales and marketing personnel would immediately begin to see some patterns emerging.

Likely, however, they have other data already in their possession that would give them additional insights as to sales patterns leading to a better understanding of their customers' behavior. Take the following examples:

  • Which salespersons produced the highest sales in terms of dollars and units? Which ones produced the least?
  • Within each salesperson's sales, are there significant differences by sales by geographical region or SCF?
  • Are there correlations between salespersons' sales and the discounts offered? (This would be an indicator of price sensitivity and should be correlated by other factors, like geography or average sale size.)
  • Do correlations exist between salespersons' sales results and the products or product configurations they sell most frequently?
Little of this kind of analysis was being done in a formal way at this firm. However, it seemed that they already knew they needed to "understand their customer" better. They just had not yet thought about how to leverage what they already had in their hands in order to begin segmenting their market and understanding the factors leading to less success or more success (read: Throughput).

We will talk more about this in the next post in this series.

©2010 Richard D. Cushing

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