Optimizing Your Data With Operational Intelligence
As we begin the new decade, machine learning remains at the forefront of modern business innovation. Technology has been integrated into almost every industry and aspect of consumer life. The amount of data produced and stored has grown exponentially, as people freely publicize personal data. Businesses can then use this unrestricted access to provide valuable insights into their existing and potential customer’s wants, needs, and preferences. Using this data to improve customer experiences and strategy is a must for almost any successful business. Having access to the incredible amount of data available on your doesn’t mean it will be easy to turn that data into valuable information. In fact, according to many data scientists, it’s management, organization and consolidation take up a majority of their time. This is where data optimization comes in.
What insights can be gathered?
Big data is incredibly valuable and is one of the fastest-growing and most complex areas of business. There are many ways businesses of all sizes can collect consumer data: surveys, tracking pixels, cookies, company records, social media, and email tracking, third party sources and big data companies and more. It is likely that a business will have anywhere from a couple to several hundred sources of data storing records of user transactions, consumer behavior, equipment processes and function, security threats, fraudulent activity and potentially more.
Why does operational intelligence mean?
Operational Intelligence sounds more complex than it is. Essentially, it consists of different methods of data analytics that prioritize the ability to implement quick, accurate and targeted business decisions based on access to live data. Operational intelligence offers your business a real-time, full-scope perspective of what exactly is happening across your IoT systems, helping you make far more informed and strategic decisions. Pulling from all of your sources the historical data can be sorted through quickly in order to deliver you the most pertinent short term KPIs and operational metrics. The real-time data analysis allows and your executive team the ability to respond a lot faster than when only relying on reflective data.
How are businesses struggling with managing data?
One of the most common issues most companies deal with is making the data they collect actionable. These days, it’s not only for CEOs, managers, and other top executives but also employees and customer service representatives can benefit from easy to understand data sets as well. Unorganized information is rarely helpful, as it leads to slow and unreliable insights. This results in a trickle-down effect of delayed decision-making, and both consumers and companies end up suffering.
Data sources are often siloed in different departments and sourced from multiple types of software and applications. Many companies also may lack ownership rights over the raw data collected. Most software vendors with self-service data preparation tools don’t allow a clean separation of raw data from the intended analytical conclusions. For example, Google Analytics is one of the most common resources providing information about a business and its consumer base. However, it only allows users access to the curated analytical results making it even more difficult for brands to connect and correlate their data.
How can operational intelligence optimize your data?
Consumer expectations and demands on businesses will only continue to grow. The amount of available data is often too substantial and overwhelming to process without the help of operational intelligence, particularly for industries reliant on infrastructures such as power, water, electricity, manufacturing, mining, oil, gas, and telecom. The best way to manage the operational data collected is by consolidating it into an operational core. This systematic approach offers more availability and transparency, decreasing the time between a problematic event and a solution.
Continuous, real-time information remains relevant, especially in a world a customer-centric ideology is so important. Our digitized economy has made it a requirement for businesses to use available data to maintain a competitive advantage in any industry. Consider how you might start improving how your business extracts and utilizes valuable data. Using an operational intelligence approach, predictive analytics and artificial intelligence is only the beginning of many more advances in the data applications industry sure to come.