by CIO Staff

Using data analytics to achieve competitive advantage

Mar 28, 20137 mins
Technology Industry

Governments and enterprises can use business intelligence (BI) and data analytics to achieve real competitive advantage in uncertain economic times when budgets are being squeezed, according to attendees at CIO’s roundtable “Creating an intelligent information business.”

IT leaders at the roundtable – sponsored by C3 Business Solutions – agreed that business intelligence can solve the challenge of maintaining business-as-usual operations and creating new initiatives when money is tight.

“By automating the delivery of information – particularly for manually-intensive processes such as financial reporting and consolidation – our BI program can be targeted at high-impact, high-value opportunities,” says Aidan Coleman, strategy architecture manager, IT at Stockland.

“At Stockland, we have adopted a flexible BI architecture and approach that will enable us to automate and simplify greatly, the delivery of information to the business but also deliver targeted BI solutions that provide insights into our business.”

He says that like many businesses, a significant contributor to Stockland’s competitive edge is the ability to make decisions faster than its competitors.

“Business intelligence and analytics are the enabling technologies that bring information and insights to our front line staff so they are empowered to make the decisions that sustain our competitive advantage,” says Coleman.

Staff may be making a call on the feasibility of a major investment, development project, or creating a “location, layout and retailer mix” that will make a shopping centre really successful, he adds.

Conrad Bates, managing partner at C3 Business Solutions, says business intelligence can help organisations understand where money is being spent and the specific value they are realising from that spend.

“You can then work out the most efficient way to reduce costs and more accurately target your reinvestment strategies,” Bates says.

He adds there are four key areas for “doing more with less” through business intelligence which include:

– Using an agile delivery approach to demonstrate measurable business benefits or cost savings. – Focusing on the outcome and delivering within budget using cloud and mobile BI solutions – Improving the quality, accuracy and insightfulness of your internal data and looking to potential new external data sources to improve competitive advantage – Gaining deeper business insight using predictive analytics

The latest round of “government efficiency dividends” cutting into IT budgets has meant the Australian Centre for International Agricultural Research (ACIAR) needs to focus on finding ways to reduce costs and improve efficiency, says Andrew Sinclair, manager, information technology and infrastructure at ACIAR.

Consequently, ACIAR is investigating business intelligence and data analytics.

“ACIAR is a research organisation and we have more than 30 years of data that is held in different systems that do not talk to each other,” says Sinclair.

“The research staff rely on complicated spreadsheets leading to an inefficient process that is difficult to access, resulting in problems with data quality. Business analytics will give us a single data source that will streamline the collect and sharing of data throughout our organisation.

By managing the data this way and removing the manual process, it will allow us to deliver the research staff can depend on,” he says.

The power of predictive analysis

Attendees agreed that predictive analytics – where organisations use data mining techniques to analyse current and historical events and make predictions about the future – is becoming popular.

C3’s Bates says predictive analytics is about forecasting what is inherently unpredictable: human behaviour.

“It’s critical that you have the right sample data to work from,” he says. “The first step is a clear view of when the behaviour your tyring to predict is exhibited – this will give you the best outcome.

“You’ll then need a clever business analyst to provide candidate characteristic attributes that can be lead indicators to the behaviour trait you’re seeking …. and then access to some simple tool (with high end statistical functions).

“Gone are the days where you need a data scientists to develop and algorithm – many of them are embedded into today’s tools. Only when you have a complex problem do you then need a data scientist to developing the solution for you.”

Bricks and mortar retailers like Stockland hope that predictive and even video analytics can play a role in developing new initiatives to retain and acquire customers but it’s still early days.

“However, as shopping centres enable high levels of internet connectivity, video will generate insights from tracking human movement and attention throughout the centre which will significantly enhance centre design and shopper experience,” said Stockland’s Coleman.

“One commercial opportunity is to generate real-time offers in which retailers use these insights to proactively make offers to shoppers while they are in the shopping process at the store level, likely through a mobile device.

“This form of predictive BI, along with advances in mobile and digital display technology could certainly help embed the shopping centre as the hub of multichannel retailing.”

C3’s Bates adds that video analytics is very valuable in a retailing environment to track promotional impact and customer service levels by looking at metrics such as “dwell and queue times”, when stock is running low, traffic movement and shopper navigation paths. It’s also useful to determine shrinkage and conversion rates.

“You can use video analytics to tell you what is and isn’t working in real time so you can adjust your promotional spend, merchandising approach or staffing levels,” Bates said.

Stockland’s Coleman agrees that it is difficult to devote time and effort to predictive analysis, particularly when there is so much focus on historical trends and data.

He says this can be misleading particularly in the current business climate with evermore change and uncertainty.

“Because our business relies on making great capital investment decisions that may have a 30 year lifespan, we rely on plenty of ‘what if’ scenario analysis that factor in both internal organisational conditions but importantly also external conditions (government legislation, interest rates, consumer sentiment, locality, economic growth etc.),” he says.

“It’s part of the DNA of all our people, but our research and strategic risk team really drive the overall approach, so I would suggest these skills are critically important.”

C3’s Bates ended with “Predictive is just the next stage of maturity for many customers; but you have to have the foundation stages working well in your organisation before you can start to predict the future, accurately, reliably and efficiently.”

Ensuring privacy during analysis

Attendees agreed that organisations and governments need to ensure customer information remains private when they are collecting and analysing data.

According to C3’s Conrad Bates, maintaining customer or citizen privacy when dealing with data is best achieved through a combination of policy and process. He says: “Stringent policies that protect privacy should be adhered to through rigorous, consistent, repeatable processes.”

Ian Macintosh, unit head, ICT operations at the Australian Institute of Health and Welfare (AIHW), says any organisation dealing with and analysing data (particularly data that includes personally-identifiable data) must abide by the privacy principles at the very least and should have a comprehensive review process.

“AIHW uses an ethics committee, registered with NHMRC, which diligently vets proposals and puts in place appropriate governance arrangements for each and every research project,” says Macintosh.

“This is an active process, not something of a rubber stamp and organisations that do this less than fully do so at their own risk,” he says.