While many businesses are beginning to recognise the huge potential that effective use of data analytics can bring to their organisations, there is still a wide gap between the companies that fully exploit this and those that only make cursory efforts.
In particular, it was noted by Gartner research director Lisa Kart that there is a world of difference between a firm that merely uses business analytics and one that can truly be considered an 'analytics business'.
Speaking ahead of the research firm's Business Intelligence, Analytics and Information Management Summit, which takes place in Sydney on February 23rd and 24th, she explained the most effective organisations are concerned with much more than just reviewing transaction data.
"The biggest opportunities are with connecting the data you already have," she stated. For example, getting a complete, cross-channel view of customers means digging deep into their data warehouses and connecting their silos together, in order to transform the data into something consumable.
She added the best-performing firms use correlations and find patterns in disparate, linked data sources to yield the greatest insights and identify opportunities to transform the way they do business.
Gartner identified four main types of business analytics – descriptive (what is happening), diagnostic (why did it happen), predictive (what will happen) and prescriptive (how can we make it happen).
While many firms may be able to conduct descriptive or diagnostic operations, getting all of these working together with be the key to moving from a business that uses data to a firm that is driven by it.
Ms Kart said the first step to successfully completing this transition will be to tie a firm's data to an actual business need. It is often the case that people get overwhelmed by the promise of big data and try to jump in before they have established exactly what they want to get out of the technology.
Gartner stated the real question they need to be asking is 'what is your business trying to accomplish?' This could take many forms, such as improving marketing, reducing risk, making operational changes, or boosting revenue.
Ms Kart therefore highlighted some positive examples of what can be achieved with a clear big data strategy, such as fashion house Burberry, which turned to the technology to help it better engage and interact with its customers.
The company used analytics to create a high end, in-store customer experience that offered customers greater intimacy and interaction. This was achieved by leveraging data from customer purchases, surveys and social media and using this to identify and greet their customers when they walked in the store.
"Burberry was able to blend the in-store and online experience for their customers," Ms Kart said.
Elsewhere, Gartner pointed out how Coca-Cola uses big data analytics to guarantee consistency in the juice it sources for its Minute Maid products.
"Using satellite images, weather patterns, expected crop yields and even variables in flavour such as acidity and sweetness, Coca-Cola was able to fine-tune their formula to such a point that they could respond and change within five to ten minutes of a hurricane or frost," Ms Kart continued.
The exact formula for this is a secret guarded as closely as its famous cola product, she said, which shows how big data can be used to assist almost any business function.