Are
our MI Reports making the desired Impact?
Most often, post our discussion with our
clients and stakeholders we start creating MI reports. Reports depicting
performance trends, task volumes, success rates, TAT and a range of other
important metrics. We discuss more, and we continue creating new reports and
making amendments to the existing reports. We continue generating more reports,
for more people, with more frequency to ensure that our stakeholders have all
the information that they’ll ever need. However, twist this scenario and think.
Thanks to all our enthusiastic reporting and the reams of reports we generate.
However, will our stakeholders EVER NEED all this information?
Can we please go back to all our reports
in our respective processes and try to look at each of them through the following
seven lenses?
1. Is it simple and Relevant?
It’s easy to get overly ambitious and want
to provide highly detailed, real-time reports covering each and every slice-and-dice
analysis that’ll provide our stakeholders with multiple dimensions. But instead
of spending multiple weeks or even months working through our first iteration, take
it step-wise. Start with simple and key metrics and then work through several
short cycles of prototype, test and adjust.
2. Is it uncluttered and unambiguous?
Do not clutter
your reports with unimportant (though good-looking) graphics. Keep your report
simple and impactful in its visual appeal. Resist the temptation to make it too
flashy or over-designed graphics and charts. As pretty as those may seem, they
get in the way with your report’s objective i.e. rapidly and easily informing
your audience.
3. Is it too entangled and misrepresentative?
Often reports
start simple. And then there are complex formulae’s like percentages, lookups,
deriving values from multiple sheets, sum and if conditions, circular errors
(where a cell refers to its own value to recalculate a new value) and similar
convolutions. It is here that we run a risk of data misrepresentation. When it
takes too many sheets and entangled formulae to arrive at a new value, there is
always the chance of our final graphs (despite being visually high-impact)
showing an inaccurate picture.
For e.g. last
month the team occupancy was 80%. Of that 80%, 70% of bandwidth deployed was
for Project A. Within this Project A, we used 90% of our bandwidth for activity
XYZ. Now, a different chart somewhere might show bandwidth on XYZ is 90%.
However, that’s absolutely misleading as the actual bandwidth deployed on
activity XYZ is just about 50% (90% of 70% of 80%).
Hence, it is
always suggested to frequently go deep into all the formulae and charts in all
our existing reports. It is an imperative step to iron out all the inherent
chinks that might’ve inadvertently crept in.
4. Is it well structured, designed and
formatted?
Take care in how you design your graphs
and charts. For example,
·
3D offers no increase in viewer comprehension.
·
Garish colors can interfere with
interpretation.
·
Choosing a pie chart for more than 6
values makes the graphic virtually impossible to read.
·
Have we ‘wrapped text’ for long
remarks/statements and aligned it well (both horizontally and vertically)?
·
Are we following a standard colour scheme?
·
In case of currencies, have we inserted
the right symbol and ‘000 separators?
·
In case of numbers, have we standardized
the decimal spaces?
·
Do all the worksheets have appropriate
titles?
·
Are all the embedded links and formulae
correct and functional?
And finally, beyond the aesthetics, some of the most important
questions for all our reports –
5. Can we reduce the frequency?
Not everyone
needs every bit of information on a daily basis. Some information doesn’t even
add much value on a weekly basis (there are hardly any movements). So should we
reconsider the frequencies of our all our existing reports? Can some of them be
reduced from dailies to weeklies to bi-weeklies to monthlies?
6. Can we merge two reports?
When two or more
reports have a large proportion of exactly similar elements, why then are we wasting
our efforts in extracting the same information multiple times? Is there a
possibility of merging multiple reports and reducing our redundant efforts?
7. Can we become dispassionate and have
a realistic discussion around do we actually need a particular report? What if
we stop it completely?
Often we keep
doing things, following MI routines and generating age-old reports which are
perhaps no longer relevant to anybody. Often, we make innovations and introduce
new reports with high-relevance metrics that everyone is keenly looking at.
However, we continue to keep running the old reports alongside the new ones, just
in case, someone wants to revert to the old format for some comparison
trends.
However, there
should be a clear-cut, well-defined period of generating such ‘just in case’
old reports. If we keep generating all our old reports alongside the new
reports till eternity, the very purpose of introducing innovations is defeated.
Till the time all new innovations that are introduced (to bring in
efficiencies) do not see any corresponding ‘old practices’ being stopped, the
innovations are an additional strain on our systems and resources. It’s an
ideal case of building in more redundancies rather than efficiencies.
Hence, time and
again, keep questioning all the existing reports for the value and relevance
they bring to the table. If you haven’t heard any feedback or questions around
a particular report for a long time, perhaps no one is actually looking at it
any longer!
And how does one
identify such ‘just in case’ redundant reports? Just one approach – keep
questioning! Frequently keep challenging and questioning yourself with tough
questions around “What if I don’t generate this report?” rather than going
over-board with your ‘It will be
done!-delighting-the-stakeholder’ attitude.
In the current testing times, deriving
efficiencies out of our existing systems, resources and reports plays a much
bigger role than ever before. Do your bit. Ask the right questions. And
contribute in avoiding the information overload. Cut the flab, get lean!
Itni Shakti humein dena ‘Data’, Kabhi
Insights Kamzor ho na!
Let’s explore the Power of Data!