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Information dashboards have become quite popular as management tools among
corporations. More and more organizations are turning to dashboard technology
to distill large amounts of data into at-a-glace performance indicators.
Solutions abound with the same goal: to allow everyone from C-level executives
to operational staff to more quickly interpret and understand organizational
and personal performance through visual metrics.
While dashboards practically scream "transformational benefit," success
is harder than it looks. In addition to the common challenge of dashboard design,
there are two other primary reasons that BI dashboard projects often fall short
of their potential:
- Unclear goals. Lack of a clear and focused vision regarding which
metrics such as Key Performance Indicators (KPIs) are important enough to
be displayed in the dashboard, which means users ultimately do not find the
dashboard useful from a practical standpoint.
- Inaccessible data. The problems associated with accessing, transforming,
aggregating, and delivering data from transactional databases, multiple sources
or non-structured sources often result in incomplete or inaccurate dashboard
These issues can muddle a dashboard project from the start, stalling it before
critical information ever reaches the desks of the managers and departments
that need it. To understand how to solve these problems, this article will take
a closer look at what's driving each of these challenges and offer an alternative
approach to creating a powerful dashboard.
Defining Key Performance Indicators (KPIs)
In an ideal situation, a company has the passion, time and resources to put
together a strategy and plan for its dashboard project. This company may set
up a task force of end users, managers, IT and other decision-makers to embrace
the process of defining and ensuring access to KPIs.
Reality, however, is a different story. Instead of a concerted effort, it's
more common that a particular business unit or sales department may think it's
a good idea to have a dashboard and then try to set one up. It seems so easy,
why not just do it? The problem lies in understanding which metrics to track
and, more importantly, what underlying data needs to be available.