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There has been a lot noise around traditional BI being a failed promise. In
fact, Market Dynamics, a UK-based research organization, published a report
on how Fortune 500 companies are losing millions of dollars in lost opportunities.
Can it truly be attributed to traditional BI alone? Well, to answer that question
one needs to comprehend the context in which BI is implemented.
Traditionally, IS reports have been used by management executives to formulate
strategies for their organization at a global level. Say, for instance, a pharmaceutical
company would be more interested in identifying patterns to better understanding
the usage of a particular drug for a region or occurrences of particular diseases
in a geographic location.
These, as you may well understand, are data which have been accumulated over
a period of time, at times ranging in years. On the contrary, a downstream manufacturing
company would benefit more from tracking whether their shipments are being delivered
on time as that affects their business directly.
As you can see, that the former approach falls more in the traditional BI category
where the top brass would use the data to start an R&D initiative for a
new drug or come up with a strategy to position a different drug for a particular
market. The key thing to note is that to take such a decision you would require
data with a wider time window, possibly a few months/years of data.
In the latter scenario, the time window to respond to anomalies is extremely
short and it directly impacts operations within as well as outside the organization
to make decisions very quickly. As an example, a semiconductor company could
be providing low budget components to mobile manufacturers. In today's uncertain
times, most of the manufacturers keep a very low inventory and are dependent
on the downstream suppliers to deliver components in a timely manner as their
assembly line is completely dependent on it.
As you may be aware that a delay in shipment can trigger a flurry of activities
affecting the line of business executives directly dealing with the customer,
the finance department as a delay in shipment could affect the payment position,
the planning department would need to rework on the next schedule and above
all the customer would have to be informed about the delay so that they could
possibly take necessary actions to handle their assembly line. This is what
operational BI would help in solving: a short time window and people at the
operations taking immediate decisions.
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