Research Blog - Customer Intelligence

Once again, it's been a couple of weeks since I've blogged. I'll quickly highlight - in reverse chronological order - the people, seminars and texts before going into a lengthy ramble about ... stuff.

People: I met with my supervisor Graeme this morning, and had a quick discussion about the spectrum of formality surrounding business decision making. See the below ramble. Last Monday I had lunch with Dr. Bob Warfield - former manager from Telstra and now something of a role model or mentor for me - and Dr. Peter Sember, data miner and machine learning colleague from Telstra's Research Labs. We discussed my research, industry news and gossip and collaboration prospects.

The Friday before I re-introduced myself to Dr. Tim van Gelder, a lecturer I had in a cognitive philosophy subject a few years ago. We discussed Tim's projects to do with critical thinking, and his consultancy, and possible synergies with my own research and practice in business intelligence. While there are similarities - the goal is a "good decision" - there are differences: I'm looking at the relationships between inputs to a decision (information and decision rules) and outcomes; he's looking at the process itself and ensuring that groups of people don't make reasoning "mistakes".

Seminars: I've attended two since last blog. The first one was on a cognitive engineering framework, and its application to the operational workflow analysis of the Australian Defence Force's AWACS service. (This is where I bumped into Tim.)

The second one was on the "Soft-Systems Methodology" being used as an extension to an existing methodology ("Whole of Chain") for improving supply chains. SSM looked to me like de-rigoured UML or similar. I'm not sure what value it was contributing to the existing method (I asked what their measures of success were, and they didn't have any), but they had quotes from a couple of workshop participants who thought it was helpful. So I figure that's their criteria: people accept it. They didn't report on whether or not some people thought it unhelpful. They didn't talk about proportions of people who responded favourably, and unfavourably, and then compare with people who participated in the "reference" scheme (ie without SSM). In short, since I wasn't bowled over by the obvious and self-evident benefits of their scheme, and they gave me no reason to think that it meets other people's needs better than existing schemes, I'm not buying it.

I have to confess I'm still getting my head around IS research.

Book: I read half of, but then lost (dammit!), a text on Decision Support Systems. It was about 10 years old, but had papers going back to the 60s in it! I don't have the title at hand, but Graeme's going to try and score another copy.

I've also discovered a promising text by Stuart MacDonald entitled Information for Innovation. This is the first text I've read that talks about the economics of INFORMATION as opposed to IT. (I read some lecture notes and readings on "information economics", but found it to be an argument for why organisations shouldn't apply traditional cost/benefit analyses to IT capex.) It's quite clear that information is unlike anything else we deal with, is extremely important in determing our quality of life and yet it is suprisingly poorly understood. I would like to make a contribution in this area, and I'm starting to think that Shannon's insights have yet to be fully appreciated.

Ramble: I've been thinking that to drill-down on a topic, I'm going to have to purge areas of interest. For example, some months ago I realised that I was only going to look at "intelligence" (as opposed to "content" - see below). Now, I'm thinking I need to focus on formal decision processes. Allow me to explain ...

There's a spectrum of formality with respect to decision-making. Up one end, the informal end, we have the massively complex strategic decisions which are made by groups of people, using a limitless range of information, with an implied set of priorities and unspoken methods. Example: the board's weekend workshop to decide whether or not to spin-off a business unit.

Up the other - formal - end, we have extremely simple decisions which are made by machines, using a defined set of information, with explicit goals and rules to achieve them. Example: the system won't let you use your phone because you didn't pay your bill.

The idea is that decisions can be delegated to other people - or even machines - if they are characterised sufficiently well for the delegator to be comfortable with the level of discretion the delegatee may have to employ. The question of what becomes formalised, and what doesn't, is probably tied up many things (eg politics), but I think a key one is "repeatability". At some point, organisations will "hard-code" their decisions as organisational processes. At other times, decision-makers will step in and resume decision-making authority from the organisation process (for example, celebrities don't get treated like you or me).

I'm thinking that for each process, you could imagine a "slider" control that sets how much decision-making is formalised, and how much is informal. This "slider" might have half a dozen states, relating to process functions:
  • Documenting Maintaining the authoritative process map

  • Recording Maintaining the authoritative current state of the process

  • Controling Driving/executing the process map, changing current state and prompting people where necessary

  • Designing Building, testing and deploying new or modified processes based on experience or simulation

  • Commissioning Determining if new or modified processes are required, and the goals, parameters and resources of the process

The more informal the decision, the more you'd need to look at group-think phenomena, cognitive biases, tacit knowledge and other fuzzy issues best left to the psychologists. I'm thinking that the formal or explicit processes are going to lend themselves best to my style of positivist analysis.

So in that sense, I'm inclined to look at metrics, and their role in decision-making for business processes (customer), service level agreements (supplier), and key performance indicators (staff). Typically, these things are parameterised models in that the actual specific numbers used are not "built into it". For example, a sales person can have a KPI as part of their contract, and the structure and administration of this KPI is separate from the target of "5 sales per day": it would be just as valid with "3" or "7" instead. Why, then, "5"? That is obviously a design aspect of the process.

Perhaps if these processes are measurably adding value (eg. the credit-assessment process stops the organisation losing money on bad debters), then it is reasonable to talk about the value of the metrics (both general-thresholds and instance-measures) in light of how they affect the performance of the process? If the process is optimised by the selection and use of appropriate metrics, then those metrics have value.

While I'm not sure about this, I think it's easier than performing a similar analysis on the value of an executives decisions.