When leveraging AI-sourced data and analytics to transform underwriting speed and precision, digitally savvy and collaborative solution providers can be ideal partners.
Digital transformation is reshaping the business landscape, but the journey is often far from smooth sailing. A well-cited statistic from McKinsey
notes that 70 percent of transformation initiatives fail. So, what makes achieving successful digital transformation such a daunting task?
Here are some perspectives.
Defining the Digital Transformation Landscape
Digital transformation is not one size fits all. It encompasses various facets, including enhancing customer experiences, optimizing business processes, and driving product innovation. Organizations can also approach it in different ways – deciding to do transformations in house or partnering with solution providers. At NeuralMetrics, we focus on leveraging AI to access risk-quality data and analytics — to improve underwriting speed and precision for a superior policyholder experience. And this area of digital transformation supports the core mission of insurers and their agent/broker distribution partners.
Selecting the Right AI Solution
The optimal path to success lies in focused objectives. The sample questions below can help to streamline transformation goals:
- Who needs an improved experience?
- Are faster processes demanded by customers?
- Are enhanced information sources and insights crucial for growth?
- Is the organization fixing an existing workflow deficiency or crafting an entirely new process?
After identifying internal drivers and pain points, and to help speed up the transformation objectives, state-of-the-art technology partners can be evaluated for alignment with your processes, stakeholders, and business objectives. Collaborative solution providers who transparently communicate their capabilities and implementation results can be ideal partners in digital transformation initiatives.
Maximizing ROI
Here are three broad suggestions to enhance the return on investment (ROI) from AI-driven data and analytics implementations:
- Prioritize Clean Data: Accurate data is the backbone of successful AI projects. Maintain uniform, clean, and current data, and prioritize transparency so outcomes can be traced back to their source. Consistency in data organization across structured and unstructured sources is vital.
- Embrace the “Fail Fast” Tenet: Adopt the Silicon Valley mantra of failing fast and learning quickly. Swiftly implement trial periods and take advantage of low-commitment contracts offered by solution providers. If a solution doesn’t work, move on quickly, applying lessons to find the right fit for evolving business conditions.
- Communicate the “Why”: Simply introducing new technology won’t yield results. Explain the rationale behind these changes within the organization. Emphasize how these solutions will improve processes and workflows. Robust training and continuous support are essential for adapting to the ever-evolving digital landscape.
Go to the full article in Forbes.