In a previous blog, I outlined how context matters, and specifically how the industry context in which you are doing business matters to the strategic decisions you make. But there are also commonalities across industries. Some business challenges plague multiple industries such as how to improve customer experience, retain loyal customers, and improve sales whether in the retail or hospitality sector, or how to get the inputs you need to make your products and to get your products to market in a timely manner in the manufacturing or pharmaceutical sectors. And, everyone these days is increasingly concerned about fraud, risk and security.
Predictive analytics has become the key to helping businesses — especially those in the highly dynamic Chinese market — create differentiated, individualized customer experiences and make better decisions. Enterprise architecture professionals must take a customer-oriented approach to developing their predictive analytics strategy and architecture.
I’ve recently published tworeports focusing on how to architect predictive analytics capability. These reports analyze the trends around predictive analytics adoption in China and discuss four key areas that EA pros must focus on to accelerate digital transformation. They also show EA pros how to unleash the power of digital business by analyzing the predictive analytics practices of visionary Chinese firms. Some of the key takeaways:
Predictive analytics must cover the full customer life cycle and leverage business insights. Organizations require predictable insights into customer behaviors and business operations. Youmust implement predictive analytics solutions and deliver value to customers throughout their life cycle to differentiate your customer experience and sustain business growth.You should also realize the importance of business stakeholders and define effective mechanisms for translating their business knowledge into predictive algorithm inputs to optimize predictive models faster and generate deeper customer insights.