hances are you already know that data is important for business – really important. You’ve likely been barraged by a seemingly endless stream of data terms: BI technologies, big data techniques, advanced analytics, machine learning and AI. And despite the hype, you’re probably wondering what the fuss is all about. After all, don’t companies already make decisions based on data?

The benefits associated with BI technologies, big data techniques and advanced analytics are not revolutionary. These technologies allow companies to enhance existing skills and optimize existing processes. The key difference is one of scale - computers applying big data analysis techniques on gigabytes of data can generally identify many of the same patterns a human would, but significantly faster.

Let’s start with basics. What is business intelligence?

Business intelligence comprises the strategies and technologies used by enterprises for the data analysis of business information. Also known as BI, BI reporting, and other associated BI-technologies, this discipline is focused on providing insights to organizations.

Business intelligence and data analysis can be as complicated as applying big data analytic techniques, but often is as simple as reporting basic metrics. That's it.

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Basic reporting and business intelligence are a fantastic start.

Adding basic reporting and business intelligence can have a huge impact for a business, especially when they lack robust data infrastructure, governance and processes. We usually see the following situation play out:

1. Company has multiple data systems not connected to one another. Ad-hoc requests for reports are usually taken care of by the “data person” (usually someone from IT or Finance), and there is a long backlog of requests because this person is overloaded.
2. Company builds out proper data infrastructure that connects their different data sources. As a result, reporting requests take less time to deliver.
3. Company builds out standardized, automated BI reporting. As a result, employees and leadership teams become accustomed to seeing regular, accurate business reports.
4. Company starts to experiment with business processes and observing the impact of these changes through the new and improved reporting.

Once companies get the basics of business intelligence data right, they become accustomed to it. At this point, they start looking to do more. Enter advanced analytics.

What is advanced analytics?

Advanced analytics in action – predictions and optimizations

Advanced analytics, also known as business data analytics or advanced data analytics, are methodologies that enable the discovery, interpretation, and communication of meaningful patterns in data and applying those patterns towards effective decision making.

In a way, business intelligence and data analytics go hand-in-hand. As the saying goes, those who don’t know history are doomed to repeat it. The same holds true for business intelligence & analytics. If you don’t know what patterns occurred in the past, how can you possibly predict where they will go?

Let’s use a simple example: A mining company produces 5,000 tons of ore a day. This ore is transported to a mill that can process a maximum of 8,000 tons a day.

• Business intelligence would focus on reporting the facts: tons of ore produced and milled daily. BI would also provide other reporting metrics, such as revenue, cost of goods sold, etc.
• Advanced analytics would look to determine optimal operating conditions, anticipate production volumes, and provide predictive maintenance schedules for equipment. In other words, it would focus on providing insights to optimize existing process

A quick note about analytics vs analysis.

Just a quick note about semantics. Analysis generally refers to activities related to the interpretation of past results. Business data analysis, business intelligence and data analysis, big data analysis techniques – these are all backwards-looking. In contrast, analytics is focused on the predictive. Business data analytics, advanced data analytics and data analytics techniques all describe methodologies that give companies recommendations on how to optimize their business.

Back to business optimization.

Although there are some very advanced technologies on the horizon like self-driving cars, and even terminator-like robots, with respect to data analytics the opportunity for most companies will come from relentless optimization.

Think of a business process – perhaps it’s processing a component on an assembly line, or scheduling home patient visits. Think of all the different business processes in your organization – there must be hundreds if not thousands. Now imagine improving each of these processes by one percent. In isolation, each improvement is not much. And it’s probably not very hard to do. Now compound all of these improvements together. Making a one percent growth improvement to one hundred small processes worth 170% in growth. Making a one percent improvement to cost reduction across one hundred processes is worth a 63% reduction in cost.

Small improvements, compounded over time, can have a huge cumulative impact to a company. It's through the discover and recommendations of these optimizations that BI and advanced analytics help companies achieve huge improvements.

Do the mundane, but do it really well.

Pattern matching. Really, really good pattern matching. That's what BI and analytics provide to companies. While not nearly as glamorous as the latest news about AI or machine learning, through application of these technologies companies can accumulate enough small improvements to generate big results. And aren't results far worthier of front-page news?