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Everyone strives to achieve
better results – better investment returns and better
operating performance at lower costs. But “better” can be a
relative term. The phrase “investment returns” is a commonly
understood metric, and its calculation is subject to
industry standards. Operating performance, however, evokes
different connotations in the minds of many colleagues. Some
think about the output produced each period; others consider
the cost and effort to create these outputs. But the best
way to achieve optimum performance is to measure both output
and effort.
Effectiveness versus Efficiency
Focusing on process outputs
examines how well you are doing at meeting established
corporate or business objectives. This is the client-facing
perspective, whether your client is a customer or an
internal group. Since customers (ultimately) pay all of your
bills, it is important to measure the results that are
important to them and build the capabilities needed to
produce these results.
It is equally important to determine how well your internal
processes are working at meeting these external goals.
You could, for example, exceed your revenue target, but
at the expense of incurring extraordinary costs to bring
in new revenue. The clarification of these internal, efficiency-focused
metrics gives you a better understanding of the processes
that are working well and those that require adjustment.
| |
Operational
Effectiveness |
Process
Efficiency |
| Focus |
Achieve
business and client objectives |
Manage
costs/time |
| Typical Metrics |
#
Transactions/Period
(Throughput) |
Time
to complete a transaction
(Time efficiency) |
| |
#
Failed Trades/Employee
(Productivity) |
$
IT Cost/ $ Revenue
(Cost efficiency) |
| |
Customer
Satisfaction Rating
(Service Performance) |
$
Operations/ BPS
(Cost efficiency) |
| |
$
Trading volume/ Trader |
$IT/
Employee |
The best solution, from a
corporate perspective, is to measure both effectiveness
and efficiency and to tie these metrics together to ensure
that investments in infrastructure (to improve process
efficiency) directly impact the bottom line (effectiveness).
Of course this is easier said than done. It will take
time to tie investments in infrastructure, e.g., technology
upgrades, to specific divisional goals. The trick is
to start at a high enough level where you have good measurement
data, and then refine the metrics over time as you gain
comfort in interpreting your results.
If
the high- and low-level goals are not aligned, you could
waste time and money on efforts that are not going
to improve the bottom line. As an example, suppose your
divisional goals included meeting a profit objective of
x% and exceeding a certain revenue target. At the process
level you might have a goal to reduce transaction costs
by y%. If you focused only on the process metric, you could
determine that replacing an OMS would allow you to improve
your throughput enough to meet your target. However, a
technology replacement would cost several million dollars
and could disrupt your operations for several months, potentially
compromising the trading group’s ability to meet
its revenue goals. A more thorough approach would be to
identify solution alternatives that can satisfy all objectives.
After some analysis you may determine that the best approach
is still to replace the OMS, but you would do so with a
better understanding of the impact that this would have
on the overall operation.
You
should apply this same reasoning when you benchmark your
operations. Some organizations choose to benchmark technology
performance; e.g., cost/transaction, $IT/employee, but
fail to extend the benchmark to include all related components
of an operation. By narrowly focusing on technology performance
they run the risk of fine tuning the engine and neglecting
the rest of the car. A good benchmarking program will
establish high-level criteria to gauge operating performance
and then drill down into specific process and technology
metrics to allow you to determine which components of
the operation need help. For an example of a “good
benchmark”, think of a trading process. At the
highest level you will want to establish benchmarks that
measure how effectively you are completing trades. To
fully understand this metric, you would also want to
create detail metrics that look at the efficiency of
the trading process; e.g., # transactions/day/desk, %
transactions routed directly to the market, and at the
underlying technology; e.g., % trades completed using
OMS, % failed trades. The high-level data will tell you
how well you are doing at reaching your business targets.
The lower level information will give you an indication
of what actions you need to take to boost performance.
Two-level
benchmarking is more complex than standard IT benchmarking.
However, the results are more valuable to anyone charged
with running a business. And the program is more satisfying
because it provides you with additional “dials” on
your dashboard to fine-tune your business.
This
is an occasional series on Benchmarking. In the
next article we will discuss the importance of benchmarking
your outsourced processes to make sure that your
vendor
is meeting all of your customers’ expectations.
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