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Which data tools do you need to make information actionable?

Organizations now know that lost employee productivity comes from data overload. Which data tools can help workers sift through the information?

Over the past couple of years, companies have paid more attention to data, which isn't surprising considering the volume of information they now generate.


Big data is here to stay, and organizations are waking up to the fact that a major cause of lost productivity is employees' inability to make timely business decisions from this data overload. It's quite the opposite problem from the past, where we had limited data and tended to overanalyze the little information we had, which led to some analysis paralysis. Today we suffer from a different problem, and having the right tools for the job is more important than ever.

Assuming you can store the information from across your organization, there are several things to understand before choosing the right data platforms. In the current business climate, people refer to these as business intelligence (BI) and analytics (dashboards), but there is much more in play than a software choice. When used correctly, these tools can have drastic effects on your results.

The right data tools for the right user scenarios

First, let's define the options before we identify how to decide what you need for the situation you are trying to address. Reporting is two-dimensional, like taking a picture at a park.

Business intelligence, on the other hand, provides an added layer to the data, giving you the ability to see the same park from different angles, but also giving the flexibility to decide how to see the picture.

Reporting is two-dimensional, like taking a picture. Business intelligence provides an added layer to the data.

Finally, analytics gives a view of the park, along with statistics on the number of visitors in the park and whether they have pets. Or, it could provide the average number of friends each family member at the park has on a particular social media network.

Now that we have defined the tools, let's put them in the context of customer relationship management  (CRM). To do so, let's establish the context of the audience. To keep it simple, there are two types of consumers: internal and external. Internal generally break into managerial and front-line users, and external break into legislative, partner and customer types. Let's consider these scenarios in light of the data tools you need for each user.

The easiest scenario to outline is legislative, where there are financial implications for not providing the information as is legally required. Like tax returns, much of what we have to report is documentation, with no particular flare for design or structure. The reporting has required data points, but there is no intrinsic value in providing deeper context to the information.

Partner or contractual consumers of data have similar needs as those for legislative requirements. Often the level of reporting is the same except that the recourse for not providing the information is more civil than criminal. In this situation, if the partner is complex, providing  BI may be suitable and an analytics dashboard of critical metrics would be suitable for less-capable partners.

External consumers are our customers, and the information customers require depends on what they can do with the data. Identify how they need to see data broken down, what is contextual to that information, and the decisions that need to be made from the data.

For example, if I am a facilities manager, and I want to understand the volume of cleaning supplies I ordered for the year, what else do I need to know? And would I want to see products or transactions in a different way, or do I expect to be presented with information I didn't know about my ordering patterns in a dashboard that produces a different effect on how I order in the future? I may benefit from a two-dimensional report of transactions that I can show to my boss that highlights I would have benefited from ordering in volume.

The good news is that we don't really need to delve deeply into our internal groups because the customer scenario dictates the tools that make the most sense. Know why the information is needed, who needs to see it, and what business decision is being made, and you will be well on your way to success.

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What steps have you taken to tailor data to the right constituency?
It's a pretty obvious statement, but the first step is to understand your constituencies, their specific needs, and how the data will be accessed. For example, we have a lot of users in the field who access their data from mobile devices. This drives the requirements for presenting the data in ways that can be processed and displayed on those devices, which in turn drives requirements for the data types that are queried and presented.