Image by Gerd Altmann from Pixabay
The promise of predictive analysis: Obtain forward-looking insights to innovate and quickly recognize opportunities for growth.
Despite the overwhelming mystery surrounding predictive analysis, you can become adroit at developing and using it.
Hoping for higher profits, financial services, insurance companies and big retailers have long used predictive analysis.
However, many companies struggle with information overload and don’t know how to begin – the only reason the use of predictive analysis isn’t widely used.
You don’t have to completely overhaul your structure. To use a metaphor, you don’t have to throw the baby out with the bath water.
Actually, it’s relatively simple to start. All you have to do is start with what you know and use it as a foundation on which to build.
Here are the key moves you need to make:
1. Consider your key performance indicators and how they can be leveraged.
Understand how solutions might help you to achieve your business goals. Review your target audience, customer behavior and operations.
Target your best-prospective audience by using simulations to merge your business-performance data with your market’s demographic data.
You can enhance your lead-generation, if you evaluate your customers’ behavior to decide which of them are likely to buy and what they’re likely to buy.
Evaluate your operations and processes. Make improvements where needed.
If you make a successful transition to predictive analysis, you’ll be better able to improve business performance, understand your customers, predict their behavior, maximize your decision-making, and overall predict trends.
Obtain the right data. It’s all about quality, not quantity. Some insurance companies like Safeco have a history mistakenly making decisions without accurate data.
2. Recruit the right analytics team.
You must have the right talent to develop accurate insights.
For instance, this has been part of the Safeco insurance company’s problem – the wrong people reading the wrong data making wrong decisions.
For years, Safeco has been on roller-coast profit and loss track, and ranked next to last among Pacific Northwest insurance companies in J.D. Power’s 2016 study of customer satisfaction.
It’s important extract the right data, develop data profiles, and outside participants or consultants who will fully understand the data and make the right recommendations.
So the team must include knowledgeable data analysts, consultants, data experts and predictive-analysis scientists.
3. Manage effectively.
You probably need to evolve culturally, as this whole process is foreign to your staff. Many people are threatened by change. Trust is a problem.
Learn your employees’ concerns. Encourage them to engage your and the process. Use focus groups to query them if necessary.
For acceptance, keep employees informed. It will make it easier to empower them to implement your predictive-analysis success.
Conclusion
If you make a successful transition to predictive analysis, you’ll be better able to improve business performance, understand your customers, predict their behavior, maximize your decision-making, and overall predict trends.
From the Coach’s Corner, here are related sources of information:
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Is Your Company Under-performing in Marketing / Sales? Evaluate Your Culture — If you’re dissatisfied with your revenue, it’s time for an assessment of your culture’s operation. Why? Superior cultures drive business performance.
Data has a story to tell you — for profits.
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