Apples as Oranges: Complexity of the Concept
Great (yet tiring) trip this week out to California. I spent a couple of days out with the IBM team for a few of our ‘Break Free’ events. I’m currently waking up <yawn> from a red eye flight from San Francisco, waiting for my last leg to Raleigh.. so apologies in advance for the potentially slipshod writing.
One of the more interesting aspects of technology (make that information system) marketing is the complexity of the concept. What I mean by this is that there is an inherent difficulty to communicate both what you are trying to sell, as well as what the customer is trying to buy. There are many different facets, and many different layers to the system at hand (for this discussion, call it the ‘data warehouse’, but can be applied to any Information Management system). What I call a data warehouse, or what IBM calls a data warehouse is not always what an analyst views as one (less likely – but gets a bit more funky with the technology direction), and even more importantly what a customer views as one.
Case in point illustrates from a conversation that stemmed from my presentation yesterday. Was speaking with a prospective customer about a number of offerings in our portfolio: The IBM Netezza 1000 appliance and the IBM Smart Analytics System.
After some clarification of each solution’s sweet spot, reference stories, etc. I start to probe the customer about what they are doing now, where they want to go into the future, and it comes out that they are a SQL Server customer that has ‘hit the wall’ with application scalability – Quality of service is not up to par with the demands of the business and they need to re-architect a data warehouse strategy to get them there.
Ok, at first glance my thought is that we have a number of technologies that can you there, and well this is an all too common story. Slam dunk right? – Well no. because we have not discussed what kind of data we are looking at here. Upon further analysis, this customer is looking at aggregating social media feeds (en masse) – Gigantic data stores of information…
“Ok, is this data pre or post cleansing?”
So at this point we are now at a ‘Big Data’ discussion rather than a ‘Data Warehouse’ one. The issue at hand is less on the warehousing of the data, but potentially the processing and cleansing of the data before it even gets into the warehouse. (Note: For brevity I am simplifying the actual discussion)
This conversation then moves along the lines of operational data store (ODS) or not, what ‘real time’ means …and when. And to make the discussion even more interesting, this was not the only customer at the event that was probing this exact same scenario. (Note: Special presentation from our own Data Warehousing CTO, Bill O’ Connell this Wednesday, September 21st HERE)
The summary of this all, is that fools rush in with both system sales and marketing. Way too many times (myself included) we push solutions or concepts because we think that is what the customer wants – or what we are told to sell. (and same for the customer, they jump at a solution, or at a brand) We need to foster comprehensive discussions about current, short term and long term need with the client, agree upon common definitions and then propose a comprehensive solution without getting into the ‘Chinese menu of options’.
As I write this, I acknowledge that to many this is just common sense – like ‘duh’, this is how enterprise IT is sold. But you have to ask yourself, are you ever guilty of rushing the gun on either end of the deal? …seriously.
I’m rambling now (floating in and out of jet lagged consciousness) but I hope that this makes sense. We have to balance simplicity and ‘hype’ with functionality and purpose and this process is not always clear. Add to this that we could also be marketing apples as oranges, …and well if you state that you are looking to acquire an orange, yet really want a pear…