Categorized | Goalsetting

Be S.M.A.R.T and Lead a Data-driven Life

Continuing with my quest in the search (and the definition) of the ultimate life-management webapp I have revisited an old concept which I used to apply in my life but sadly have forgotten (continuity – another of the issues that I want to address and solve with my service). I have since then reinstated this practice in my life again.

I am talking about the S.M.A.R.T criteria. This mnemonic is used in project management at the stage where one sets the objectives of a project.

S.M.A.R.T is typically defined as such:

Letter Major Term Minor Terms
S Specific Significant,[3] Stretching, Simple
M Measurable Meaningful,[3] Motivational,[3] Manageable
A Attainable[4] Appropriate, Achievable, Agreed,[5][6] Assignable,[7] Actionable,[8] Action-oriented,[3] Ambitious[9]
R Relevant Realistic,[7] Results/Results-focused/Results-oriented,[4] Resourced,[10] Rewarding[3]
T Time-bound Time-oriented, Time framed, Timed, Time-based, Timeboxed, Timely,[4][6] Time-Specific, Timetabled, Time limited, Trackable, Tangible

Source: Wikipedia

It is not perfect but it sure as hell works well. S.M.A.R.T goals converts fuzzy ideas that are difficult to act upon into something actionable and manageable. I have followed this criteria for about 3 weeks now and it works. It helps me focus and it gives me direction which I think is the most important aspect of it.

Measured life – taking a data driven approach to life

What mostly intrigues me is the M = Measure. I am fast becoming a firm believer in what Peter Drucker is famously believed to have said:

You can only manage what you can measure.

It would be interesting to see a webapp that used data to try to evaluate and predict the success of initiatives in order to develop life-strategies. By taking a data-driven approach to how we manage our lives it might be that we can act faster upon the goals and objectives that are important to us. Having access to a rich data-set could help compare and contrast and in this way assist a user in his pursuit of a goal.

Interestingly enough this is where my thoughts have headed the last weeks. I asked myself; How can a system harness the success of other users in order to calibrate and optimize goal “roadmaps”? (I see several ways how this could work but for all the same rule seems to apply – the degree of success gets higher with a greater  amount of data available.)

It would be damn near impossible to adher to a strictly data-driven life but I am quite convinced that a quantitative analysis is an important foundation when defining goals and related milestones. Just look at Google. They tried out 41 shades of blue on their links in order to see which performed best.

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