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Emerging Analytic Trends
Christopher Hutchins, VP, Chief Data & Analytics Officer, Northwell Health
Analytic technologies have been advancing at a rapid pace and are empowering and accelerating the ability of organizations to gain essential transformative insights. These insights are enabling them to sustain, innovate and grow business in a very competitive and pressurized environment. There are many factors that are driving the need for this capability. Specialized verticals exist in most organizations that require career level focus from a subject matter perspective that is not easily centralized. Prioritization of analytic development across an enterprise is also challenging as there are often competing initiatives. Traditional business intelligence platforms require significant infrastructure and highly skilled labor to manage at scale. Prior to the recent advancement of self-service data visualization tools, it simply took too long to perform simple analyses and business leaders were often stuck in a development queue.
Enabling and managing these capabilities requires thoughtful strategies that do not impede business units within an organization from effectively managing their areas of purview, nor should they prevent the advancement of their analytic capabilities. There may be a temptation to stick with more traditional approaches that keep tight control on data access and business intelligence tools given the explosive growth in the generation of data of virtually every kind. It is becoming increasingly difficult to ensure data quality and accuracy while at the same time providing the level of access 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.
With the proliferation of powerful data visualization tools it is getting easier to produce the kind of outputs that will turn heads and seemingly add value. These capabilities are certainly important to delivering effective analytics and may garner a lot of enthusiasm. While these outputs can look flashy and official, they may not provide meaningful or actionable insights. This is the key concern for leaders that have responsibility for data governance and/or enterprise analytics in particular. The various platforms that provide this capability are becoming easier to use and do not require the same level of skilled labor that the more traditional business intelligence options.
Providing framework that enables teams to collaborate, share, and promote best practices can be a tremendous help with the change management challenge
Dashboards and Scorecards
There is also a trend toward integrated cross-domain analytics. These typically are presented in dashboards and scorecards and contain content from more than one data source in a single view. In most industries these data domains are managed separately and analytic outputs are accessed in multiple tools and platforms. Producing a consolidated view of key measures across an organization has historically been a manual effort. Compiling outputs from disparate systems with dependencies on each of the domains to complete their normal production routines prior to having a team or individual begin the work to produce a consolidated view. These technologies are now enabling high availability of consolidated views with the most current information available from multiple domains at whatever refresh rate the organization determines for each domain. Dashboards within a single domain are certainly valuable to leaders managing their operations. These consolidated views enable insight into multiple business units and domains at a single glance to more easily assess enterprise performance.
Enabling the generation of these insights is not only possible but it can provide a competitive advantage. Organizations generally have multiple significant disciplines that are generally not interchangeable and all are required to provide the full range of services that are required for success. Within each of these areas there are also leaders and staff who monitor, understand, analyze and respond to data that is generated to support the functions within their purview. Bringing these experts together is key in order to establish vision and collective ownership and responsibility for the quality within each domain and ultimately the consolidated views. This can certainly be a change management challenge. The additional challenge is in choosing and establishingan enterprise platform to land and organize the data to support both domain specific and consolidated analytic outputs. My suggestion is to choose a platform and focus on developing strategies that enable experts in their respective verticals to optimize their functions with effective analytics leveraging this platform establishing a collaborative framework.
Providing framework that enables teams to collaborate, share, and promote best practices can be a tremendous help with the change management challenge. 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 recently heard this function referred to as a data concierge which I think is also a good name. Much like a hotel concierge, this is a place where people can get answers to questions or be connected with experts who can assist them to achieve their objectives. Including a platform to house a business glossary where common terms and definitions are published is also recommended. This could be a website that provides a central repository for important documentation, regulatory information or links to recommended resources. Identifying a business leader with broad organizational knowledge to lead this effort can accelerate adoption and improve governance. This role would have particular focus on developing the platform to house shared content and developing user forums in addition to providing the concierge like service. As an organization goes through transformation to be more data driven and providing enterprise views, there is often sensitivity to this kind of central function. Establishing and marketing this as a service to support analytic teams is highly recommended.