| | NOVEMBER 202119UTLOOKHealthcare Tech to data that a business demands. If the objective truly is to enable the business to be successful then a solid strategy is needed. This strategy must enable business units to evolve and adapt to a landscape that is rapidly changing and seeing exponential growth in data generation.Centers of ExcellenceAs an organization goes through a transformation data-driven decision making, there is often sensitivity to centralizing development and support of analytics. Establishing and marketing this as a service to support analytic teams is highly recommended. Centralized infrastructure can also assist in developing governance around organizational analytics without impeding the important work being done in business units. In addition to providing this capability, it is also important to provide a framework that enables teams to collaborate, share, and promote best practices. One approach is to establish a center of excellence or an analytic resource center where teams can contribute content to be shared with colleagues. I have also heard this function being referred to as a data concierge service. Including a platform to house a business glossary where common terms and definitions are published is also recommended. Additionally, publishing links to important documentation or to regulatory information will also add value. Identifying a business leader with broad organizational knowledge to lead this effort can accelerate adoption and improve governance with a focus on developing shared content and the development of user forums and communities. Over time this function can grow to become the intake valve for analytics across an enterprise as networking progresses to connect domain experts throughout.Artificial Intelligence and Machine LearningNew technologies and solutions generally identified as Artificial Intelligence (AI) are appearing nearly every day it seems. The topic elicits a wide range of responses ranging from fear and skepticism to hopeful enthusiasm and certainly many others in between. As with any new technology, there is good reason for all of these initial reactions and perspectives which I believe are very healthy when they exist together in leaders and teams that are charged with guiding strategies to develop and implement solutions. The need for this capability is only increasing as the pace of data generation continues to accelerate with accumulated data nearly doubling annually.While the possibilities are tremendous, it can be challenging to identify an appropriate entry point that satisfies the desire to move forward and provides an acceptable risk level at the same time. Many industries are starting with robotic process automation which is in the early stages of being used to automate rule-based transactional functions. This includes banking, retail, marketing, health care, and customer service to name a few. There are numerous potential applications for sure.At the forefront of the challenges with these technologies are privacy and security. While some industries capture consent at the time of an individuals' first engagement, concerns remain with regard to how data is used, who owns the data, the insights, and the work product of the models and solutions that are developed. The potential utility of the data is generally not understood by an individual at the time consent is given. Consumers are becoming more educated, especially when a data breach makes the headlines. Effective Data Management StrategyEach of the topics I have discussed here has complexities and challenges of their own but all share a dependency on effective data management strategy. One thing that is very clear is the criticality of ensuring focus on data quality, privacy and security, and an effective data management strategy. Deploying a strategy that ensures enterprise data assets are well-curated, standardized, and fit for use is perhaps one of the most challenging to achieve but it is essential.It's still about PeopleRegardless of industry, there are multi-faceted organizational dynamics and consumer interactions that must be understood in order to make progress in any of these areas. While some may have apprehension and fear of technology replacing jobs, I submit that people and relationships are becoming more essential and not less. These tools and techniques can accelerate the derivation of insights for sure but they will aid rather than replace human decision-making and likely enable more decisions and faster innovation. I believe that the pace of change will continue to pick up speed. It is not the technology that leads me to conclude this. Rather, it is the amazing ability of human beings to adapt, innovate and create that will produce the next waves of disruptive innovation. HTThere has been a significant proliferation of powerful data visualization tools that are industry and data source agnostic
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