Why Data-Driven Companies Drive Growth

By Kerry Koutsikos, Country Manager - MEA & Turkey, Qlik


Over the past few years, the time organizations have at their disposal to make crucial decisions has been drastically reduced. According to a study by IDC, 42% of managers have just 24 hours to make an important business decision and yet, in many cases, they don’t have the access to data to help educate these decisions. This issue is a common one and, for a lot of organizations, it’s imperative they find a solution to the problem.


All organizations need to be focused on becoming more efficient and productive – and there’s a plethora of ways for them to do so.  At the heart of the solution is gaining a complete overview of what’s currently happening across the business. This means bringing all intelligence into one location and making it available for everyone to access and analyse.


Fortunately, there are visual analytics technologies available that anyone in an organization can use to gain a better understanding – on a global scale – of their organization.


Data-driven organizations share a number of characteristics that make them more efficient and productive. Here’s what to do to become one:

1. Focus on people

Data is an important asset in decision-making and a key source for knowledge within an organization, but it’s the people within that company who have the power to assess whether a decision is right or not. Therefore, companies should equip their employees with easy-to-use analytics to get the most knowledge from their data.

2. Agile decisions

64% of business managers have seen the time allowed for decision making shrink in the last 12 months, with 42% citing that decisions need to be made in less 24hrs[i].Being quick with decisions allows enterprises to better respond to dynamic business environments and competitive markets.

3. Make use of all data

Data-driven enterprises provide a framework for users to access and analyse all their data irrespective of source, internal or external and don't limit analysis to preconceived notions of how data should be structured, but allow freeform analysis no matter how it is structured.  Because it’s in combinations of seemingly disparate data that much of innovation will happen in the digital era.

4. Encourage experimentation, don’t be afraid of failure

Organizations must allow all people access to wider data sets and let them analyze freely – even if it means sometimes making mistakes.  After all, if people can analyze without worrying about risk of failure then they’re more likely to move outside of their comfort zone – and make discoveries that can really change the business.


5. Don’t make assumptions about what you might find

A lot of organizations just use analytics to get an answer to a very defined question. But this limits analysis (and therefore the insights that can be gained) significantly. If companies start using data analysis more broadly – just to see what’s going on across the organization – rather than limiting themselves to finding answers from specific data sets, then they’ll be in a better position to get a broader view of what’s actually happening.


6. Extend analysis to all levels

According to a study by Gartner[ii], analytic tools do not reach more than 25% of non-technical users in an organization. In order to achieve company-wide adoption of data analysis, platforms need to be both accessible and usable for anyone from the HR Manager through to the Head of Marketing, or even shop floor staff.  Giving everyone the ability to do data analysis means more knowledge can be harnessed, after all.


7. Make sure data analysis is at the heart of any decision making

This means giving staff access to analytics platforms from any device and from any location.   A recent study by Qlik shows 45% of users start analysis on a device such as a desktop computer, and then look to finish the task an hour or so later on a smartphone or tablet.


8. Go beyond your company

An organization’s intelligence shouldn’t be limited to internal data or the knowledge of its employees, but should also make use of data from its external ecosystem of partners, customers, suppliers, and so on. The data available for analysis needs to incorporate information from third parties as well.


9. Embrace Governance

Governance is often seen as standing in the way of the innovation and agility of a business, but without it, organizations would face unnecessary risks. Governance – getting the right data sets to the right people - is key to empowering users with the appropriate information with which to improve their decision making.


10. Data driven business models

Data-driven organizations recognize that data analysis doesn’t just help leaders make the best decisions in a quick timeframe, but can also help to identify new growth opportunities, define new business models and show new ways to reduce risks. More than half of companies with big data projects, according to Gartner[iii], focus the use of their data in generating new business ideas or design to optimize sales processes. These insights are exactly what any organization needs in order to define new business models – put data at the heart of all operations.


Organizations now are more informed than ever before. This gives them the ability to drive changes, optimize their business and, ultimately, improve their decision-making from a proven base that’s accumulating all knowledge. The key will be to equip each and every member of staff with the ability to analyze data and get insights that can help drive the business forward.

[i] “The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things” – April 2014.

[ii] Gartner; Market Trends: Business Intelligence Tipping Points Herald a New Era of Analytics; Dan Sommer; November 2014

[iii] Gartner; Answering Big Data's 10 Biggest Vision and Strategy Questions, 12 August 2014;

Douglas Laney, Alexander Linden, Frank Buytendijk, Andrew White, Mark A. Beyer, Neil Chandler, Jenny Sussin, Nick Heudecker, Merv Adrian.



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