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 organisations to make the most innovative decisions. Organisations 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 organisations 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, analytic tools do not reach more than 25 percent of non-technical users in an organisation. 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
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