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​INSIGHT: Top 5 ways predictive analytics supports enterprise-wide strategies

​INSIGHT: Top 5 ways predictive analytics supports enterprise-wide strategies

Many businesses already use advanced analytics to address a multitude of business problems. However...

Many businesses already use advanced analytics to address a multitude of business problems.

However, too many businesses are still unaware that they could use the insights and predictions from predictive analytics more broadly to make smarter decisions and develop more successful strategies.

“Predictive analytics uses modelling, machine learning, and data mining of historical data to make predictions about the future,” says Martin Hooper, Head of business development, Australia and New Zealand, CenturyLink.

“This can help companies with tricky tasks as diverse as managing future risk, identifying potential opportunities, and making the right decisions fast when implementing new projects or strategies.”

According to Hooper, there are five key ways in which predictive analytics supports enterprise-wide strategies:

1. Getting to know customers

“Because it draws upon past customer behaviour data, predictive analytics can help determine optimal customer segmentation, cross-sell and up-sell modelling, loyalty and retention modelling, and customer lifetime value,” Hooper adds.

“Given that the customer is usually at the centre of most projects, this is a vital aspect for enterprise-wide strategies.

2. Effective marketing

Hooper says predictive analytics can provide the insight to inform marketing mix modelling, conversion modelling, the optimal mix of offer and channel, and can also help to work out the effectiveness of particular promotions.

“This insight touches all parts of the company’s marketing activities,” he adds.

3. Accurate pricing

The technology behind predictive analytics can inform pricing decisions, which Hooper considers as one of the most valuable levers that companies can use for competitiveness.

“Pricing analytics can inform price optimisation, price sensitivity, market basket insight, and identify the best product for companies to offer next to the customer,” Hooper adds.

4. Supply chain management

“Supply chain analytics, driven by predictive analytics, can help companies forecast demand, identify key purchase drivers, inform supply and demand simulations, and provide predictive inventory maintenance,” Hooper adds.

5. Managing risk

For Hooper, risk underlies any enterprise-wide project.

“The chances of something going wrong or forecasts not living up to the realities are real concerns for large projects,” he adds.

“Risk analytics provides organisations with stress testing, fraud detection, loss forecasting, and capital reserve forecasting; all of which help to make sure a company-wide strategy remains sustainable in both worst- and best-case scenarios.”


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