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Practical Perf. Measurement (step 1 - understanding measurement's…
Practical Perf. Measurement
step 1 - understanding measurement's purpose
(focus firmly on continuous improvement as the purpose for measurement)
Bad habit - using measures to judge
BH - using weasel words
brainstorming KPIs
asking ppl to simply sign-off
rushing to data and dashboards
using report to cover your arse (fail to answer) what is performance doing in relative to target? why is it doing that? what do we need to do move it closer to target? --> The focus is in weeds, no-one is managing the landscape
comparing this month to last month
fixing performance problem by educating ppl, increasing staffing level or seeking more funding
Step 2 - Mapping measurable Results
(Translating strategy into clear, focused and measurable performance results)
vision = ideal future state, purpose = mission (more concise statement)
goal = objective
BH - action orientation, multi-focus goal, weasel word, confusion with BAU, continue to...,lack of logic
results map
Step 3 - Designing Meaningful Measures
(Choosing the most feasible and relevant
measures that provide evidence of our performance results)
1, begin with end in mind
be sensory-specific
find potential measures
(evaluating strength and feasibility of measures for community participation)
check the bigger pic - what might be unintended consequences
shouldnt only monitor circle of control, should monitor circle of influence(proactive), but avoid circle of concern
Step 4 Building Buy-In to measures
Getting ownership from our stackholders
quickly, easily and engagingly
stop doing things that affect buy-in - telling ppl measure and leave ppl to figure it out kills buy in
consulting ppl for their feedback b4 implementing measures kill buy-in - allow them make decision and felt excited
dont educate team, hold space for their discovery
dont dictate the team's goals, help the team articulate them
don't give the team their measures, teach them how to fish
dont judge the measures, collaborate to improve them
dont do it for them, let the team implement their own measures
dont trample the team's creative energy
dont dumb down the measures, trust the team numeracy skills
dont blame ppl for pef.let them fix the causes
use measure gallery to broaden buy-in
who needs to buy in
invite, dont mandate
allow space for dialogue
the right ppl will come
gather feedback and use it
Step 5 Implementing Measures
Documenting in detail the data, analysis
and reporting requirements for each of our measures
description
intent
where it fits
calculatation
the formula
the frequency
the scope
the data
presentation - what chart to use, signal are clear, valid and not distorted or misrepresetnated
response
signal 1 - perf has reached or exceed the target
find causal relationship and convert to BAU
signal 2. pef. is improvig at the rate fast enough that the target will likely be met
find causal relationship and convert to BAU
signal 3 - pefr. is improving, but not fast enough to reach the target
deeper exploratory analysis , reevaluate its ineffective action, consider if target too big a stretch for the resources avail
signal 4 - pef. us stable and not changing
deeper exploratory analysis to find key variables can be influenced
any improvement project, if yes, check its focus and its ineffective, if no, establish improvement plan
signal 5-perf is getting worse
same as the rest, but this is moment of truth where the strength of our belieef
signal 6-perf is unpredicatable and chaotic
create flowchart how process should be performed
Owner
performance owner
definition owner
data owner
part of their role ought to be document data filtering, extraction, cleaning, summary procedures
note
Step 6 Reporting perf. measure
Creating useful and usable performance reports
that inspire us to action
good reports and dashboard
alignment with org strategy
able to answer what is performance and relative to what we want it to do
why is it doing that?
now what?
automate, automate, automate to product report
Step 7 Interpreting signals from measures
Focusing ourselves on gaps between as-is and to-be performance
Noise
point-to-point comparisons -> always get conflicting conclusions. up and down variability due to inherent complexitiy rather than real change
Year on year -> no conclusion to draw
Trend over time, R2 value is low
moving, rolling or running average -> smooth out seasonal variation -> not able to draw conclusion -> depend on analysis method -> not able to manage performance
Assumption 1 - same month comparison, last year was mptmal
assumption 2 = excel can cal trend line, must be a trend
assumption 3 - world starts anew on the 1st of july every year
Assumption 4: the only probable cause for a difference is that something changed
assumption 5: all changes happen smoothly - put moving averages thru
most ppl use statistical techniques without using statistical thinking
step 8 Reaching performance targets
improving our biz processes to move as-is performance toward to-be