Know-How Exchange : Strategy

You are asking a really good question. Everyone should be thinking this way, especially now when most companies are questioning every expense.

My suggestion is to start with an ideation session. If you can find an experienced facilitator, that would be best, but if not just see if you can get half a dozen friends/colleagues to spend a few hours with you and see how many ideas the group can generate. Don't filter or exclude anything. This first step is to create the longest list possible. Shoot for 100 new ideas ... or even more. If you challenge yourselves and stay on task, you can do it.

Poor boy's version: Get the software from ThoughtOffice, and be your own ideation team. It's a little more challenging to get to 100+ new ideas this way, but it's not impossible. (ThoughtOffice software was originally IdeaFisher, and my experience with it is from that original incarnation.)

Once you have a lot of ideas, you can start to evaluate which are best, which are easiest, which can be combined with others, and which you want to pursue. It's important at first, though, to just get the longest list you can generate.

Start by looking at your competition - what are they creating?

Next, look at your non-software competition - what are people doing manually that could better be done via software?

Separate out your various skills and niche-specialties and apply them horizontally: where else can you take the skill or what other niches?

Don't forget to look afar: other countries. What are overseas' companies unmet needs?

Dear Imagine images

Visualisation in CRM and the analysis of data held in CRM systems is incredibly important and usually incredibly badly executed. That you are using maps sets you into a different league from the run of the mill CRM providers.

Have a look at what Tableau Software are doing – don’t copy them, they are the best in their field, but do understand where they came from and how they became leaders in data visualisation. They started off by asking how pivot tables in spread sheets could be made more accessible. Then they looked at ways of visualising the data to turn it into information. Next they thought about 3 dimensional pivot tables and how to handle and then visualise the information they contained. It didn’t take them long to say, why stop at 3 dimensions and heck, go for n dimensions, we can always visualise 2 or 3 of them. Next I guess that some PhD Maths bod told them about “Phase Space” so they could visualise any aspects of an n dimensional problem (Aspects of global warming for example) in an appropriate phase space – sure it doesn’t look like a graph, but then the original graph didn’t tell them anything which could be understood by a human being.

Data mining and linear programming (LP) along with operational research is key tools in the optimisation of business models. They solve problems in supply and logistics; allocate marketing resources and sales resources to match each other and they even help in my area of analysis and forecasting. The problem is that they usually require a team of PhD’s to do the maths and about a £million for the software to run them.

Visualising optimisation of sales, marketing or ERP data is not trivial, but a budget solution with decent instructions by-passes the need for teams of boffins and offers smaller companies insights into their operations which are neither intuitive nor obvious to the accounts bods. Hugh Walton cracked business optimisation of a given variable (Say turnover or profit) for a company which had x resources bounded by y constraints, in 1974 using an analogue computer. He virtually rescued English China Clays who couldn’t get their clay blending optimised to orders and Motherwell Bridge Engineering which had a similar, “What do we do to make the most profit out of the orders we’ve got” problem. Because it was done on an analogue computer, the results and intermediate results were incredibly visual – showing up on meters rather than screens and needing to be plotted if you wanted a trend.

It’s not yet been done at sub SAP or Oracle based solutions and even they tend to show the “Answer” rather than visualise the process, which is more important to the managers taking decisions and needing to explain them to shareholders.

Data mining has come along way but the visualisation of the results tends to focus on the answer to the question (42, remember) rather than the shifting relationships of different variables as the calculation progresses towards it’s goal.

Stopping visualising only answers and starting to visualise the process which leads to the answer will be a real ground breaker. Here’s the rub though – I’m not sure that a modern high powered PC has yet caught up with what an analogue computer from 1970 could do when asked to do it simultaneously and to show the intermediate results whilst striving for an optimal solution.

Over to you!

Steve Alker
Xspirt