You don’t drive your car while staring at the dashboard.
Sure, the dashboard provides you with excellent information: It tells you how fast you are going, whether or not you have enough gas, and even if the engine is running properly. But if you don’t look through the windshield, you’re guaranteed to crash into something very quickly.
Data discovery is very much the same. Internal data sources shed light on key internal issues. But if that is all you are taking into consideration, you are missing out on some of the most important information.
When business intelligence (BI) tools first hit the market, they focused on data from internal systems – largely data from operational databases and other enterprise software systems. When properly implemented, these systems provided companies with really valuable insight into operational issues ranging from the performance of the call center to the results of the latest efforts to fight customer churn – in short, pretty much everything that falls under the COO’s world.
This is a great way to understand what’s happening inside the organization. But what about the external business environment? Things like market conditions, competitive landscape, and economies in which the company is operating can provide critical information that is often left out of view. The truth is that companies can operate perfectly based on internal metrics, but still come crashing down if they don’t navigate the market environment effectively.
In other words, decision makers in the enterprise spend a lot of their time looking at the dashboard but have only a blurry and fragmented view of their surroundings – the markets they operate in, the economies they belong to and the demographics they target.
Good in Theory, Difficult in Reality
The truth is that there is a lot of good data out there, from public and proprietary sources alike. Government databases are opening up and contain more valuable information than most people realize. Syndicated research – trackers, forecasts, and surveys – is plentiful but hard to find and gain insight from quickly. And data from custom research, whether internal or from research vendors, is usually delivered in static formats. As a result, too much of it ends up sitting on hard drives somewhere with no good way to search, compare, or access later – let alone to keep an eye on updates to the underlying data.
This is fundamentally inefficient as it can be nearly impossible for the average user to track down this information and integrate it into her data analysis. As a result, decisions aren’t made with the benefit of the best available data. Instead, time is lost digging through piles of static documents, and companies are unable to make the most of the sizable investments they have already made in market intelligence.
Directions for Success
I am often asked how this actually works in real life. Offerings that allow users to consume data as a service provide insightful data directly to users in a format that can be integrated and analyzed easily. And some of the more interesting use cases come from basic, even rudimentary, information like weather. For example, users often look at metrics on sales and wonder why particular spikes or drops have occurred over time. Layering on weather data can reveal all sorts of interesting correlations. Perhaps there was a snow storm that stopped people from coming to the store or differences in temperature and precipitation that impact consumption trends.
One of my favorite podcasts, “Under the Influence,” actually did a show all about the power of weather on marketing. One of the most interesting pieces of information concerned supermarkets in the UK, which found that they sell more ice cream on a sunny, cool day than a cloudy, warm day. When the temperature reaches 77 degrees, ice cream sales plummet. The reason was simple: Shoppers worried that the ice cream would melt before they could get it home. This type of insight can have a significant impact on the way an organization handles its inventory and even the marketing approach, and it all comes from looking at external data sources.
In the future, I believe that leaders in the industry will continue to find ways to leverage external data in order to reveal better insights hiding within their own information. In doing so, they will gain a better understanding of their own organizations and will be able to better predict and anticipate outcomes based on external factors.
Josh Good is Director of Product Marketing at Qlik.
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