I finally got around to looking into MIKE2.0. I'd signed up to the subscriber list a couple of months ago and had been getting the weekly emails, but until Labor Day weekend hadn't gotten around to digging into the website content. Now that I have, I think there's a lot to like about MIKE2.0.
MIKE2.0 is a comprehensive methodology for information management applications like data warehousing, master data management and business intelligence. According to the authors:“MIKE2.0, which stands for Method for an Integrated Knowledge Environment, is an open source methodology for Enterprise Information Management that provides a framework for information development. The MIKE2.0 Methodology is part of the overall Open Methodology Framework.”
MIKE2.0 is an iterative or “continuous implementation” methodology comprised of five phases:
- Business Assessment and Strategy Definition Blueprint
- Technology Assessment and Selection Blueprint
- Information Management Roadmap and Foundation Activities
- Design Increment
- Incremental Development, Testing, Deployment and Improvement
Phases 1) and 2) appear to be more traditional waterfall, while phases 3) through 5) are incremental and iterative – in a word, agile. I like the synthesis of the two approaches: early planning mitigates the risk of the agile “fire, fire, fire....”, while agile addresses pure waterfall's “aim, aim, aim....” shortfalls. And I interpret the linear focus of 1) and 2) as indicative of the critical importance of these blueprint phases – an importance that's often missed with other iterative approaches.
The exhaustive task lists associated with each phase seem to cover all the bases – and then some. While there are separate lists for different information management projects like BI, DW and MDM, specific project tasks are often buried in the templates, making the lists somewhat redundant and confusing. Practitioners will certainly pick and choose among the tasks to suit their initiative's needs.
Just as I find strategic targeting – finding analytics opportunities and setting the analytics ambition – the most interesting endeavor for Analytics at Work, I think MIKE2.0's first phase, Strategic Definition Blueprint/Business Assessment, is the methodology's most intriguing – and important. It's here that IT and business align and become go-forward partners. It's here that the language of business translates to the language of technology. It's here that the roles of intelligence and analytics are delineated and tied to business performance. It's here that the ROI of BI is clearly established. It's here, in short, that BI evolves from a technology focus to a collaborative “science of business” strategy enabler.
Andrew McAfee from MIT summarizes the opportunity well: “you have this unbelievable amount of horsepower and a mass of data to apply it to, you can be a lot more scientific about things. You can be a lot more rigorous in your analysis. You can generate and test hypotheses. You can run experiments."
"You can adopt a much more scientific mindset...when you compare scientific to pre-scientific approaches, there’s one clear winner over and over,” McAfee says.
To evolve the business/IT partnership to a science, the business first brings its strategy formulation – strategy maps with causal linkages – to the the Strategic Definition Blueprint phase. Those maps establish the “theories” and “hypotheses” linking what/how the organization will do to increase enterprise value. The theories and hypotheses in turn provide the foundation for prioritizing analytics targets that will drive the BI and other information management initiatives.
The causal linkages take the form of “if we do A, then B will occur”, or alternatively, “the more of A that we do, the more/less of B that will result”. An illustration from the service industry might look like the following: a greater internal service focus promotes employee satisfaction, leading to higher productivity. More productive employees, in turn, generate higher service value for customers. That value leads to enhanced satisfaction among customers, who then become more loyal, thus increasing company revenue and profitability.
Outcome metrics early in the chain are called leading indicators, while revenue and profitability are lagging measures. IT and business then collaborate to “operationalize” the strategy map linkages, producing KPIs and designs to test the strategy hypotheses and ultimately measure and improve performance.
The growing visibility of MIKE2.0 as an open source initiative should be a boon for BI. A comprehensive, accessible common language for the methodology of BI and information management that can be understood by both IT and business is a big step forward. And I anticipate MIKE2.0 assuming a leadership role with open source technology kin Pentaho, Jaspersoft, Birt, Hadoop and R to democratically accelerate adoption of the science of business.