Slow BI and the BIG Method Part 2

Continuing on from my last post introducing the BIG Method of Slow BI, here are the major steps and also the amount of effort I would usually expects each step to take (expressed as a percent of the total budget):

    Step Expected % Effort

    01 Initiate 5

    02 Definition 10

    03 Rapid Response 10 - 20

    04 Plan 10 - 15

    05 Analysis and Design 30 - 40

    06 Develop 20 - 30

    07 Implement 10 - 20

    08 Benefit Realisation and Review 5

So under Slow BI, you expend a minimum of 65% of your budget before you start the strategic development. You can still implement and deliver value to your stakeholders prior to this. This will be the subject of my next post.

What are the main activities and deliverables of steps 01 and 02?

01 Initiate

01.1 Business Case

01.1.1 Project Initiation Document

01.2 Corporate Performance Management Vision

01.3 Information Management Vision

01.9 Definition Stage Gate

02 Definition

02.1 Governance

02.1.1 Business Governance

02.1.2 Technical Governance

02.2 Change Management and Communication Strategy

02.3 Analytic Strategy

02.4 Information Management Strategy

02.5 Detailed Business Requirements

02.5.1 Data Definitions/Owners/Profiles

02.5.2 Data Prioritisation

02.5.3 Performance Measure Definitions

02.5.4 Business Process Matrix

02.6 Performance Management Framework

02.6.1 Corporate Performance KPIs

02.6.2 BI Performance KPIs

02.6.3 Stage Gate Success Criteria

02.7 Information Management Framework

02.7.1 Information Management Architecture

02.7.2 Information Management and Enterprise Architecture

02.8 Knowledge Repository Solution

02.9 Rapid Response and Plan Stage Gate.

Next post: Step 03 Rapid Response.

Previous posts in this series:

• Slow Business Intelligence
• Slow BI and the BIG Method Part 1

Comments

[Xristos]

So, I listened to the Mixergy pdscaot where Avinash Kaushik talked about the 5 generic cases of (web) analytics. I think they apply to a lot of marketing-related business questions. I'm going to get it wrong from memory, but the cases he enumerates are:* What is happening? (clickstream data)* How much is happening? (understanding multiple outcomes)* Why is it happening? (split testing)* Why is it happening? (surveys)* What else could they be doing/wanting that they aren't getting? (competitive intelligence)Those are pretty generic questions, and me repeating it is pretty watered down/generic, but Avinash describes some compelling use cases for analytics (specifically web analytics) based on business questions.Your post made it sound like you were looking for a business question or two to explore that you could make a case study of. In that vein, I'd be interested to see how you can cluster site visitors into personas based on what/how much/why they visit your site and correlate that to paying customers. The hope is that with this data, you could 1.) figure out how to get more people to convert by providing better content/messaging to enlarge the cluster of potential buyers. 2.) predict who might buy and adjust offers based on probability (and split test them).I'm sure other companies are working on this and wrapping it up in pretty bows with pricetags, but I'm interested in the math behind it. I think something like this type of clickstream analysis could be a pretty cool addition to fathom. (I might even offer to help implement it. *wink wink*)It's also entirely possible that I'm over-complicating and over-thinking the problem, and there is a much simpler way to do the above.peace out.

[dodo]

Nice! I am looking forward to the third part.
03 Rapid Response = quick win? :)

[OzAnalytics]

Hi Sanjay,

In response to your questions:

A rational view? Well I don't assume the world shares it, but I believe that analytic experts have a responsibility to help the business world become more rational.

You are of course correct that the world is dynamic and you will see that the BIG Method addresses the dynamic nature of the world by:

1. delivering quick wins and strategic wins.

2. providing a base of data that enables an organisation to handle change better

3. developing a business capability that handles change without recourse to analytic specialists.

I am not saying that correct planning is more important. What I am trying to say is that investing time and effort in data analysis delivers a better return than the traditional SDLC delivers when used in analytic areas.

I hope that explains my ideas a little better.

[Sanjay M Kabe]

Steve, just a thought on your fundamental assumptions:

Are you assuming a rational view of the business world?.

Are you assuming that things are not dynamic and do not change during the definition/planning phase?.

Are you assuming that correct planning is more important than execution/data collection or any other downstream activities?