Yesterday, we discovered what predictive analytics meant. Today, we'll share how it can do for your company.
Why does predictive matter for your company?
The ability to make good predictions can literally make or break your organization. And while you may have a business scorecard, you need to ask: is my scorecard smart enough? If you’re still using traditional reporting solutions that answer questions about what happened last quarter, the answer is no. Though historical reporting has value, it’s a look in the rearview mirror—telling you what has happened rather than what will happen. Predictive analytics flips that equation, enabling you to look forward so you can avoid wrong decisions and make the right ones to gain strategic advantage. For example, predictive analytics might help you:
- Identify hidden revenue opportunities within your customer base
- Retain your high-value customers, employees, and partners with the right retention offers
- Enable your call center agents to delight customers with the best next-step recommendations
- Build long-term customer/employee/partner relationships with intelligent interactions
If you think all this sounds a bit futuristic, think again. Innovative predictive technologies are already enabling many companies to achieve these goals and more. For example, SAP Predictive Analysis helps organizations use the power of predictive across multiple business functions, and SAP InfiniteInsight automates modeling and deployment tasks to make predictive analytics available to users in diverse operational environments. “These tools make it easier for end users to define predictive models for their particular areas,” Tucker says.
While there’s still a ways to go before predictive becomes the norm for every business, inroads are visible in many areas (see sidebar). Tucker likes the story of the Oakland A’s. As depicted in the movie Moneyball, the A’s successfully used predictive analysis to identify and fill the positions needed to produce a championship team—despite having the lowest payroll in all of baseball. “It’s a fantastic example of how an organization used predictive models to identify the right talent required to achieve their objectives,” Tucker notes.
Who's using predictive today?
- Utilities use smart meters to effectively track consumption in neighborhoods and homes, then compare that with environmental data to predict upcoming energy needs on the grid and take corrective action as needed.
- Healthcare organizations use predictive to map patient outcomes for specific treatments and anticipate where the market’s headed on new technologies and protocols—enabling them to staff appropriately, invest wisely, reduce hospital readmittance, and cut costs.
- Retailers employ mobility and location tools to predict and drive what consumers will purchase--for example, stores can text passersby with sale alerts about the specific items they most want to buy.
- Telecoms use predictive to monitor customer usage trends and get notified when consumption falls so they can take steps to secure shaky accounts.
- Sales teams use predictive to assess the likelihood of a deal closing in a given quarter, prescribe corrective action if needed, and correctly forecast revenues. Mobility tools give sales reps on-the-spot awareness of the probable price a customer is willing to pay.
- Staffing/HR targets the best candidates through predictive. For example, the Navy SEALs use a sophisticated model to identify those applicants most likely to make it through the strenuous and costly BUD/S training, increasing success rates while protecting their investment.
- Business planning, forecasting, and budgeting are predictive models and core, data-driven activities that every business uses. They also help companies gain competitive advantage, identify new revenue opportunities, increase profitability, improve customer service, and drive operational efficiencies—all named as top predictive benefits in a recent Ventana Research survey.
Tomorrow: we'll cover steps for best practices