Data Drives Lean
Data is needed to focus improvement efforts.
- Objective data is needed to make sound judgments.
- Data from time studies, equipment loading data, takt times, staffing
requirements, process yields, and lot and kanban sizing information
will lead to workflow configurations and process layouts that help
optimize value streams.
Data sources for lean efforts include:
- Almost everyone thinks they know how much time it takes to perform
routine process tasks but time studies usually prove that the
assumptions are wrong.
- There is no substitute for real time studies, a staple of the
"old-time" industrial engineer, compete with a stopwatch and
- Equipment loading rates are a function of throughput rates,
bottlenecks, and takt time.
- The nameplate capacity, full loading potential, and capacity
utilization rates together create the basis of reality checks on
- The takt time is established by the customer's average buying rate.
- If the takt time is 10 minutes, that means that over the course of a
day, week or month, customers are buying competed products at a rate
of one every 10 minutes.
- If any process equipment in the workflow fails to function when it
is scheduled to do so, the entire workflow comes to a halt and
customer demand will go unmet.
- Data on reliability of the equipment can be used to adjust full
loading potential and throughput rates until TPM efforts can improve
- Historically, scheduling practices have favored long runs and large
lot sizes to reduce the impact of the time and cost of tedious
process set-ups and long product change-overs.
- If set-ups and change-overs are significantly reduced, the benefits
of converting to small lot sizes are enormous.
- Data on current lot sizes and the rationale used to set current lot
sizes is helpful as a conversion to lean and pull manufacturing
practices is planned.
- Data on actual process yield rates is a necessary planning input for
a lean conversion.
- The reasons for yield losses is important information. Sources of
yield losses are usually targets for improvement efforts although
they may influence lean plans as well.
- For example, if a process has a fixed quantity of inherent start-up
waste that cannot be eliminated or reduced with current technology,
the impact of small lot sizes on yield may overshadow the benefits
of small lot sizes.
- A conversion to lean can have a major impact on staffing methods as
well as staffing levels. Staffing levels are commonly reported to be
at least 20%.
- Crew staffing instead of worker staffing is often more effective in
- Current staffing data provides both a baseline and reality check for
confirming planned lean staffing requirements.
Good data collection forms organize information into useful formats,
serve as communication tools, and help trigger solid improvement