Who and what does no business intelligence solution impact

Having no business intelligence solution in place impacts many things and many people. It impacts your bottom line, it impacts your customers, it impacts your employees, and it impacts the understanding of your business right now and in the future.

Your bottom line

With having no business intelligence solution in place, a business cannot see the full picture on what is happening. The business cannot see where all its money is being spent, it cannot see what areas are most inefficient, they cannot see what area they are most efficient in and why and then drive those efficiencies to other areas of their business. They slow down and prevent the business from making real-time data driven decisions. Without seeing the big picture, the business can be limited or just wrong on actions that are taken that they believe are good for the business. All of these reasons as well as many more impacts your business’s bottom line.

Your customers

Having no business intelligence solution does impact your customer. I get a lot of feedback on this one and it is usually from the people that do have the silos of data running within their business. They want to feel better by giving me excuses on how not having a business intelligence solution does not impact their customers. I always tell people that if you cannot get a full picture, a full understanding of the journey a customer takes from the start of the relationship to the end of their relationship within your business you sir or mam will never see its full potential. With so many touch points that a customer could have with a business you have the potential of creating many silos of data. These silos can be in reference to marketing, selling customers additional services, interaction with customer support and even the customer on-boarding process. All these systems and any others should be integrated in order for you to get a clear understanding of the experiences your customers will go through. The silos of data, the lack of the single source of truth will hamper that understanding and the business will never understand the customer’s journey. Picture this: a stack chart and on the X axis you have date values representing the last two weeks, and on the Y axis you have a numeric representation of hours. Within the charting you have multiple columns (different colors) representing different touch points that a new customer had to take in order to become a customer and then received their service from your business. Within seconds you can see where you can improve the process and where the process is working. That is just one powerful reason on how business intelligence can impact your customers and having a single source of truth can help your business.

Your employees

How does no business intelligence solution impact your employees? Without a business intelligence solution, you have silo’s that can affect employees when other departments within your business do not wish to share their data. Think about how many times have you heard or have been involved when a department within a business has identified a problem but cannot do anything about it. I have seen a business identify a problem and could not take the appropriate measures to correct that problem because of silos of data. This can be corrected by doing several things. First, leadership must create a unified front and be creative and tactical in their approach. Work towards a common goal. I know each department has its own responsibilities but the business should have one shared vision — the business’s mission statement. Create the data governance group because that will encourage collaboration, build repeatable processes, share measures across the business, and the group will act as one team pushing to that common goal. Most humans instinctively will get behind a common goal and will feel more united when they can share the same measure of excellence to be obtained with the person next to them.

Descriptive, Predictive and Prescriptive Analytics

What I have been seeing with all my clients over the last three years is them trying to get their arms around their data, cleaning it, gathering it into a central location which then they typically create dashboards and reports to see how their business did in the past but some are looking at how they are doing right now. So, the way most of my clients are looking at their data is called descriptive. Descriptive data analysis gives businesses insight into the past. Descriptive looks at the data, summarizes the data and then interprets that data into human readable format to give us analytics of the past. The vast majority of the statistics we use fall into this category. (Think basic arithmetic like sums, averages, percent changes). Most often, the underlying data is an aggregate or count of a filtered column of data to which basic math is applied. For all practical purposes, there are an infinite number of these statistics. Descriptive statistics are useful to show things like total stock in inventory, average dollars spent per customer and year over year, or even change in sales.

When I talk about Predictive data analysis I am looking to understand the future. Predictive analytics want to look at the data and then predict what can happen in the future. Predictive analytics want to give actionable information to its owner on what could be coming. Currently there is no predictive data analysis that can give you with a 100 percent accuracy on what the future holds. A business should take and read the results on what might happen in the future and decide on the path based on that knowledge.

These two statistics — descriptive and predictive — try to take the data that you have, and fill in the missing data with best guesses. They combine historical data found in CRM, ERP, HR and POS systems to identify patterns in the data and apply statistical models and algorithms to capture relationships between various data sets. Businesses use predictive statistics and analytics anytime they want to look into the future. Predictive analytics can be used throughout the organization from forecasting customer behavior and purchasing patterns to identifying trends in sales activities. These statistics also help to forecast demand for inputs from the supply chain, operations and inventory.

The last analytic option we will talk about is prescriptive data analytics. Prescriptive data analytics is when you want to be guided on all the possible outcomes. The relatively new field of prescriptive analytics allows users to “prescribe” a number of separate actions to and direct them towards a solution. These analytics are all about providing direction. Prescriptive analytics attempts to quantify the effect of future decisions in order to advise on all the possible outcomes before the decisions are actually made. When prescriptive analytics are at their best it will help predict not only what will happen, but also why it will happen providing recommendations regarding actions that will take advantage of the predictions. With this type of decision analytics, support business should feel comfortable with the actions that they need to take, either staying the course or pivoting to right the ship.

Which analytics does your business need? Does your business need descriptive, predictive and prescriptive data analytics? I believe in order to answer that question the business needs to know how advanced of a business intelligence solution it needs in order to be successful. In understanding how each descriptive, predictive and prescriptive and what questions they can answer for the business will drive the business to implement a simple or more complex business intelligence solution. One piece of advice that I would like to give here is start off with the simple solution and once that solution is providing the information you need, then enhance your business intelligence into a more and more complex solution. I believe taking this approach will give you a much higher success rate of implementing your business intelligence solution as well as a higher user adaption.

To quickly summarize the last three paragraphs, descriptive as we know answers the question of the how it looks at data in the past. We also reviewed predictive where we talked about how it will most likely answer questions on how something might happen. And lastly prescriptive will give you answers to questions on what actions can happen. Depending on your business goals and what answers you need from your data, the decision on if you need descriptive, predictive and prescriptive data analytics is very personal to you and the business.

I think it is important to show you the different levels of human input to draw conclusions from descriptive, predictive and prescriptive as well how each analytic area answers which questions. This will give you a good sense of employee time that will be needed depending on the way you will be looking at your data