Leveraging Operational Intelligence for Proactive Insights (2)

Part 1 of this series discussed the way technology and its adoption are shifting within organizations. Now, business intelligence (BI) and analytics are much more flexible and can adapt to a variety of business needs beyond simple reporting, dashboards, advanced analytics, etc. Storage options, the Internet of Things (IoT), operational insights, artificial intelligence (AI), and predictive analytics are being adopted by organizations to complement their traditional BI implementations.

Taking advantage of what the market has to offer can make the difference between being able to align analytics to quantifiable business value and simply delivering traditional reporting and dashboards to a series of end users. The potential to drive operations and create competitive advantage remains limited with the more traditional approach.

The Shift in BI Infrastructures and Data Access

Before organizations consider changing the way they address BI and analytics, they need to educate themselves about where technology is headed within the market. For instance, the role of traditional data warehouses is no longer essential to BI and analytics deployments within certain use cases. Some companies have adopted big data infrastructures as a centralized data store while others look to real-time data streaming to support operational visibility. A good example is the use of sensors for quality control or worker safety.

Taking advantage of the right technology for the right use case requires an understanding of the following:

1. Technology: Understanding innovation and how current and emerging technologies will affect a particular industry is important when evaluating solutions. Some organizations focus on deploying a set of dashboards or a self-service portal to access their analytics, but overlook the data management requirements that will actually support the types of analytics required.

Technology adoption should be directly tied to the desired outcomes. With all of the messaging in the market, identifying the right set of software or the right infrastructure to support advanced analytics can be a challenge. Although traditional reporting and analytics will always provide value due to visibility into trends, BI infrastructures moving forward need to take into account both traditional and operational analytics. This means ensuring right-time access to data and leveraging technologies that can be flexible enough to shift with the changing needs of an organization.

The ability to leverage IoT data or create predictive models are only two areas that are becoming more important. Making sure that business and technology considerations take into account both current and potential future requirements will make it easier for organizations to mature and broaden their analytics use as their needs expand.
   
2. Industry and competitive factors: It is not always easy to anticipate future challenges or industry direction. At the same time, it is possible to research what competitors are doing, understand market trends, and make sure that the technologies selected take into account these trends and can meet these needs. Understanding the competition and what competitive and environmental factors may affect the business can help organizations hone in on what type of solutions they require and the type of analytics that will best meet their needs.

The reality, however, is that organizations often need to be forward thinking and ensure their technology investments can be leveraged in the future. Otherwise, projects and what they can accomplish become short-sighted based on the fact that once a solution is implemented, it may no longer meet all the organization's needs. That is one of the main reasons proactive analytics is important and should remain a key consideration when looking at technology adoption and competitive factors.