Top 3 wrong assumptions of business analytics

Top 3 wrong assumptions of business analytics

Gartner’s Svetlana Sicular debunks the biggest myths many organisations make when it comes to business analytics

Svetlana Sicular

Svetlana Sicular

Executing an effective business intelligence (BI) strategy is at the front of many CIO's minds as their organisations rely more and more on data to make decisions. But many of these IT leaders are making the wrong assumptions about BI, says Gartner research director Svetlana Sicular.

Already a big trend, BI is set to become even bigger over the next few years. Gartner forecasts Australia will be the biggest in the BI market across Asia Pacific, reaching $372.9 million in 2014 and growing to US$443.5 million in 2017. In New Zealand, the BI market is forecast to grow from NZ$61.7 million in 2014 to US$55.8 million in 2017.

At the Gartner’s Business Intelligence Summit in Sydney, Sicular said she interviewed organisations with different levels of maturity in deploying and using analytics to come up with lessons learned and the assumptions that lead to pitfalls when executing a BI strategy.

Here are the top three incorrect assumptions CIOs are making about business analytics.

Technology is the driver of business analytics success

Many organisations that started out on their BI journey initially thought the technology chosen for deployment was the primary driver of analytics success.

“Technology, even though it’s extremely important, is not the primary driver nor is it the single driver,” Sicular said. “The business drivers were the primary cause for the organisation’s vision and strategy… and the vision and strategy was driving the business analytics approach and success.”

There are many ever-advancing analytic technologies that are “alluring” and “attractive to the business”, Sicualr said. However, CIOs need to be careful not to get too caught up in the hype and investigate the real capabilities of tools and if those capabilities actually meet what they are trying to achieve.

She used the example of ‘real time’ and how that could be easily misunderstood.

“For one person real time is one tenth of a second, for another person it is today. So finding out what real time means to your particular analytics goal is also very important so you won’t overshoot with technology.

“I spoke with one [organisation] who started with one-tenth of a second, but then they ended up with 10 seconds as that is how much time people needed to really digest information.”

Collaboration and the ability to easily share data is also an important factor to consider in analytics technology. Sicular said many companies are looking to the cloud to easily disseminate data across the business.

“It doesn’t mean you need to drop everything and go to the cloud, but thinking about hybrid solutions is important,” she said.

Build it and they will come

A data-driven culture is imperative to business analytics success. “Often times you build it and it’s a beautiful technology, but nobody comes because they don’t know how to use it, or they are not ready for it, or the culture is not there,” Sicular said.

She used the example of Facebook where every single employee who joins the company has to go through a two-week boot camp on analytics and learn how to become data driven.

“Even though Facebook may be a different business to yours, think about how you can make those employees data driven from the top down as well as the bottom up.”

Changing the culture of an organisation to become more data driven is no easy task, and the longer people have been with a company, the harder it is to change them, Sicular added.

“Some people don’t want to admit their experience may not be enough [and they need insights], some people just don’t feel [comfortable] with analytics, and some people use analytics just to confirm what they already know.”

One of the participants Sicular interviewed for her research put it eloquently: “It’s a 1980's solution using 2013 products.”

“It means people who don’t change their mindset don’t benefit from any technology,” Sicular said.

Sicular suggested starting small and building incrementally to get people into the practice of using analytics to determine business decisions.

“Find something in your organisation, something small which is done now on the ‘gut feeling’ and see how you can help with analytics. Then start expanding from there. Find those champions in the company who can help you to support this.”

Business analytics is IT’s domain

There’s a strong assumption among many IT professionals that business analytics is strictly in their domain.

“Some people have a very strong opinion that business analytics belongs in the IT domain, some people have a very strong opinion that is belongs to the business.

“What we have seen is automation and enablement belongs to IT; descriptive and diagnostic analytics reporting belongs to IT. Business analytics, more advanced analytics belongs to the business.”

Sicular said even though IT is becoming a front office instead of a back office because technology is a business advantage, the different lines of business are the primary consumers of analytics and so it is a shared domain.

“The business people are the ones who understand what to do with data. More importantly, those are people who can act upon insights. Often times, this is a missing link for the business analytics success,” she said.

Bringing specialised people with non-traditional occupations into the organisation, or partnering with them, to help businesses understand how to utilise specific data can also drive success.

“Some [organisations] were hiring people with non-traditional occupations such as behavioural psychologists, social anthropologists, and linguists for text analytics,” Sicular said.

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