Going from great to greater – from big data to big impact
FYI, this story is more than a year old
Article by Modis Australia managing director Rafael Moyano
The benefits of big data have no doubt been well documented. After all, it was first introduced to the market decades ago. A quick review of Google searches on the phrase would easily uncover that Australia’s interest in big data began picking up in 2011, with exponential increases between 2012 and 2014, eventually reaching a peak in 2015. Since then, growth has shown no signs of abating.
Worryingly, Australian businesses appear to be lagging the rest of the world in data analytics – the primary way of making sense of the 2.5 quintillion bytes of data we create globally, every day.
This was according to a 2018 global research by the Melbourne Business School (MBS) and consulting firm AT Kearney, which found that Australian businesses fell behind in terms of analytics maturity and its impact on the bottom line.
Whatever the reason for this, the cost of not harnessing analytics is high. The study highlights that businesses who are lacking in data strategies and culture could be missing out on as much as a 60 per cent boost in profits! To put things into perspective, we know of companies that have seen a return of investment (ROI) of between $1.4 million and $40 million, purely from deploying analytics.
So, what exactly can Australian businesses do to reap greater ROI and deliver real business impact?
Keep it simple, analytics isn’t complex
A key reason Australia currently lags many other countries in our adoption of analytics lies in misconceptions. One of the most common misunderstandings is that data analytics is complex.
Businesses have the perception that they need to first undertake a large-scale data quality program before introducing analytics. While quality data is a nice-to-have, even a poor data set can go a long way in producing a proof of concept (POC) to justify deeper work – as long as businesses have the capabilities to fill in the gaps. All a company needs to get started is a small project and some data.
Further to that, starting with the data you have, no matter what shape it’s in, also debunks another myth – that analytics is too time-consuming and costly to get started. In fact, the time between establishing a POC and translating the findings into actionable steps is often fairly immediate.
Deploying the highly skilled
As mentioned above, it is vital for businesses to have capabilities within to fill any skills gap. The MBS and AT Kearney research revealed that companies do fair better when they engage a small team of internal data subject matter experts on analytics projects. This is because analytics needs to be an ongoing process, so acquiring and retaining internal knowledge is critical.
However, many companies are concerned they will not be able to hire skilled data scientists to ramp up their capabilities. This is especially so with the current universal shortage of data professionals.
The good news is, there are alternatives to bridge this gap: partnering with a vendor.
We are increasingly seeing more Australian organisations request for skilled analytics teams to be deployed within their organisations. Organisations have then augmented the team with their own subject matter experts to help give business context to the analytics initiatives and grow their own expertise. We have witnessed many successes using this method across industries, from government to health, energy and mining.
Align data strategy with broader business goals
But above all, perhaps one of the most critical steps when getting started on data analytics is for businesses to assess how the current state of their data aligns with the company’s broader goals.
Without a unified vision and goal across the board, different teams within the organisation will view data-related capabilities differently. This leads to disparate data systems, which will drive up costs. In order to derive value and true ROI from data and importantly, utilise information in ways that are tailored to specific business requirements, businesses must set in place a clear data strategy.
This can be achieved by re-evaluating broader business goals and defining how data analytics can be leveraged to support the organisational mission, objectives or processes. It is also important for any insights reaped to generate returns that continue long after the initial ROI has been met.
Ultimately, with fast changing business conditions and constant disruption now a consistent trend, harnessing all the data available to your organisation will help you to stay above the noise and ahead of the competition. Don’t allow the volume of data you are generating to overwhelm you. When effectively harnessed, it can inform all the areas of your business that can either make or break you.