Revenue management and predictive analytics

Illuminate the future

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 Illuminate the future

The time is now for tech companies to transition to revenue management and predictive analytics.

Responding to the opportunity

Today’s revenue reporting and forecasting approaches will be obsolete soon because as technology innovation drives accelerating waves of business disruption, it’s more challenging than ever for tech companies to analyze and forecast revenue and profitability.

Meanwhile, recent rapid advances in big data analytics and machine-learning technologies make possible much deeper insights into enterprise-wide financial performance — and the underlying business and market dynamics driving that financial performance — than ever before.

Ask yourself

  • What enterprise information management practices can we improve to raise our organization’s revenue management maturity level?
  • In what ways can our organization make better business decisions with more holistic revenue accounting detail?
  • Is the revenue reporting data being fed into our organization’s decision-making processes the best it can be to help us make the right decisions?
  • Is our organization being limited by integrated internal and external reporting platforms?
  • What enhanced business insights might our organization derive from more detailed and timely reporting of revenue and margins?
  • Will “freeing” business units to measure unique key performance indicators more closely enhance their decision-making?

Start planning now

With the advent of new and more volatile technology business models such as cloud-based services and the sharing economy — and with the firm conviction that newer and still more volatile models lie just ahead — tech companies have little choice but to make the leap to sophisticated, enterprise-wide predictive revenue analytics or risk losing competitive edge.

In that light, tech companies considering changes to any aspect of revenue management or revenue reporting would do well to take a step back and develop a strategic long-term plan. The purpose of that plan should be to establish a revenue analytics platform that helps you to respond quickly when disruptions happen, so you can maximize revenue opportunities across your product suite. Near-term changes should fit into your long-term plan.

We encourage all tech companies to start thinking about their predictive revenue analytics plans right away. The main reason is that these programs take time to bear fruit. In addition to training staff, additional time is needed for people to adjust to the new approaches.

On top of that, it even takes time for the technology itself to adapt — with machine learning, it takes time for the algorithm to train itself. Unless tech companies start thinking now about making their strategic moves to predictive revenue analytics systems, they will not be able to adapt quickly enough to remain competitive with those companies that do.

“Given that being first to market is such a huge advantage in technology, imagine how important it is to predict what will come. Predictive revenue analysis capabilities can give tech companies that edge.”

Matt Alexander
Advisory Services
Ernst & Young LLP (US)

 

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