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Data Discovery: Looking out the “windshield” can save your business

Isometric data analysis infographic

No one drives their car staring at the dashboard. Sure, it provides excellent information on speed, fuel consumption and even find out if the engine is running properly. If the driver doesn’t look out the windshield however, a crash is guaranteed to take place very soon.

Data discovery is very much the same. Internal data sources shed light on key internal issues, but if that is all that’s taken into consideration, an organisation is missing out on some of the most important information that can steer the business forward.

An insider’s look with no external validation

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 gave companies a really valuable insight into operational issues ranging from the performance of the call-centre to the results of the latest efforts to fight customer churn – in short, pretty much anything that falls under the “COO’s world”.

This is a great way to understand what’s happening inside the organisation, but what about the external business environment? Things like market conditions, competitive landscape and economies that the company is operating in can provide critical information that is often left out of view. The truth is that companies can operate perfectly based on internal metrics, but they can still come crashing down in flames if they don’t navigate the market environment effectively.

Essentially, we are seeing decision-makers in the enterprise spend a lot of their time looking at the dashboard — sometimes literally — but only have 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, but difficult in reality

The truth is that there’s 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 realise. Syndicated research — trackers, forecasts and surveys — is plentiful but hard to find and quickly gain insights. 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 near impossible for the average user to track down this information and integrate it into their data analysis. As a result, decisions aren’t made with reference to 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’ve already made in market intelligence.

Directions for Success

So how does this actually translate in real life? Offerings that allow users to consume data as a service provide insightful information directed at users in a format that can be easily integrated and analysed. And the truth is 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 show all sorts of information. Perhaps there was servere weather conditions that stopped people from coming to the store or differences in temperature and precipitation that impact consumption trends.

This type of insight can significantly impact the way an organisation handles their inventory and even their marketing approach and it all comes from looking at external data sources.

In the future, progressive organisations will be the ones who find ways to leverage external data in order to find better insights within their own information. Not only will they gain a better understanding of their organisation, they will also be able to better predict and anticipate outcomes based on external factors.


About the author:

This article was written by Josh Good, Director of Product Marketing, Qlik