As noted above, the SOP meeting typically
begins with a review of recent performance against plan for each
functional area. Actual customer order bookings are compared with
the demand forecast. Actual production and inventory levels are
compared with planned levels.
In most cases, reports and slides are prepared
in a prearranged format and scope, often via spreadsheets. If the
data loads are not fully automated, the data are old or
error-filled by the time it reaches the meeting. Frequently, there
is not enough detail available to answer pointed questions or
enough history to reveal long-term trends.
Most important, since the data and formats are
fixed, there is little or no ability to generate even simple new
analyses or comparisons on the fly. By definition, when the
analysis itself becomes fixed and predictable, it is not serving
the business well.
For example, let's say that our SOP meeting has
begun and right off the bat, a spreadsheet-based report indicates
that the demand forecast for Product Group X was off for the
preceding four weeks. Orders exceeded forecast causing numerous
difficulties. Why did orders exceed forecast for the group? Which
products' sales were up? Which, if any, were down? Were there
similar (seasonal) occurrences in past years? If so, how dramatic?
The next slide, complete with 3-D bar chart,
shows that finished goods inventory went up by 5% during the same
period. How did inventory go up while orders exceeded forecast?!
Clearly, we must have built what we didn't need. Which products
were overbuilt? When (in which week) did we know and when (if
ever) did we react?
Certainly, the participants must prepare for
these meetings. But rather than attempting to generate
spreadsheets and slides for all possible questions and answers, we
need to bring the data and the interactive analytical tools
into the meeting. This means we need data and good Supply-Demand
analysis or Demand Management software on notebook computers with
data display units.
For SOP purposes, we don't need real-time
demand and supply data, but it should be current to the day. That
means the data must be extracted automatically from its sources.
Data should be presented in an aggregate
product level of detail; however, we also need sufficient
underlying detail to answer reasonable questions. We need enough
historical data to assess longer term trends. To manipulate these
data easily and convert them into useful information, we must
store them in relational databases, not spreadsheets.
Standard comparison reports and graphs should
serve only as starting points for the review. From there, our
systems must allow us to customize reports and graphs on the fly,
to pick the time series data we want to compare, the calculations
to use, the level of detail, the time periods and length of
By bringing the right data and tools into the SOP meeting, we
enable the participants to ask and answer questions. More
questions are answered in the SOP meeting itself instead of
behind closed doors in follow-up meetings. These questions and
answers lay important groundwork for the subsequent meeting tasks—
evaluating and changing the plan.
To be Continued
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