How to become an agile, data-driven company

How to become an agile, data-driven company
Attributed to Jeremy Sim, Director, Industry Solutions, Qlik, APAC



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. Yet, in many cases, they don’t have access to data to make a truly informed decision. This problem is a common one and, for a lot of organizations, choices must be made quickly in order to respond to a pressing issue.

Organizations simply need to become more efficient and productive. According to the Asia Data Culture Study 2016[i], 88% of polled business leaders in Asia agree that an agile business must be data-driven as this increases the ability to make real-time decisions. While there’s a plethora of ways for them to do so, the ideal 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 analyze. After all, it’s only when you allow your staff to see the information for themselves that they can uncover new trends and relationships that facilitate decision-making – not only at the top, but at all levels.

Fortunately, there are visual analytics technologies available that anyone can use to gain a better understanding – on a global scale – of their organization. Taking full advantage of visual analytics also helps anyone in any business tap into huge volumes of data to gain insight into what’s happening across their company. With that visibility, they can make educated decisions on the best ways to tackle tasks and forge ahead.

An IDC report[ii] highlights that Asia Pacific organizations are maturing their capabilities to understand and leverage Big Data and Analytics technologies by 34% as compared to 7% in 2014. It seems like the mindset change is already underway, but how can an organization become truly data-driven? Here are some useful suggestions:

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[iii]. Data-driven enterprises differ from the rest due to their agility in the decision-making process. Being quick with their decisions allows them to better respond to dynamic business environments and competitive markets.

3. Make use of all data
Data increasingly resides across a broad ecosystem of sources - from traditional internal enterprise applications, line of business solutions, in the cloud and on people’s desktops, but increasingly from open and external sources. Data-driven enterprises provide a framework for users to access and analyse all their data irrespective of source, internal or external. These enterprises also don’t limit analysis to preconceived notions of how data should be structured, instead allowing freeform analysis no matter how it is structured. By stripping away traditional boundaries, and integrating seemingly disparate data, we can uncover insights from associations that are not immediately obvious. For example, external data such as weather patterns can be visualized with internal ice cream sales records to establish a correlation. Following which, strategies can be developed accordingly to boost sales.

4. Encourage experimentation, don’t be afraid of failure
Traditional analytics don’t encourage people to navigate away from a certain path of enquiry, but it’s looking beyond a set route that can help organizations to make the most innovative decisions. Organizations must therefore 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, 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[iv], 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.  After all, giving everyone the ability to do data analysis means more knowledge can be harnessed.

7. Make sure data analysis is at the heart of any decision-making
More people are using analytics for business than ever before, but it’s still important to make sure staff have the ability to analyze data wherever and whenever they need to make a decision. 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 should therefore not be the exclusive domain of people within the organization – it 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 needed to improve their decision-making. With this in mind, governance should focus less on power and surveillance, and more on opening access to relevant applications and analytics up to the business community.

10. Data-driven business models
Data-driven organizations recognize that data analysis doesn’t just help leaders make the best decisions in a short 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[v], focus the use of their data in generating new business ideas or design to optimize sales processes. By putting data at the heart of all operations, organizations can gain more than just agile decision-making, it may open doors to new business models.
We now have more data available to us than ever before, which makes us more informed as a society. Through visual analytics technologies, organizations are able to drive changes, optimize their business and, ultimately, improve their decision-making. The new data-driven business models need to focus on people. 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] “Business leaders in Asia believe that a new data culture is needed for successful digital transofmration” – Microsoft, Asia Data Culture Study 2016, May 2016
[ii] IDC: Research Shows Asia/Pacific Organizations Fast Progressing in their Big Data and Analytics Readiness, 15 June 2016; Shari Jane Jansen, Tessa Rago, Alvin Afuang
[iii] “The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things” – April 2014.
[iv] Gartner; Market Trends: Business Intelligence Tipping Points Herald a New Era of Analytics; Dan Sommer; November 2014
[v] 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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