Automated Decisions

Once you have mastered Machine Learning and trust the recommendations the models are making, you can now take the final step in the Data Hierarchy - automating the decisions. Automated Decisions mean you can finally automate those pesky recommendations into full blown decisions - tasks like auto-sending emails to customers found to have a low customer score. It frees your team to tracking those customers who respond (or don't respond) with the final human push. AI doesn't eliminate people, it frees them to do the most valuable part of the business process - human interaction

Automated Recommendations

Once you know the levers to pull, and are planning strategically, you begin to see you need more information to make better decisions. You will want data from other datasets inside your organization (a different division) or from other organizations outside your organization (purchased data) to try and enhance your current datasets in an effort to find new patterns. You will also begin to automate models running on your data to serve to you recommendations for you to make decisions on. These recommendations give your team the ability to act at speeds and in ways you never could before. You can know your team is managing in the most effective way it can, the most amount of customers it can.

What should we do to make it happen?

Once you can predict outcomes you can start looking at how changes to the variables change the outcomes: E.g. If we hire more people now, off season, how does that speed up production in season? If we wait to buy inventory and the price goes down, how does that affect our profitability? You will know the levers to pull and begin to strategize more effectively.

What's going to happen next?

With a robust data set you can use the information you know for a fact to predict outcomes. You can now act proactively--Change a belt before it breaks or order a tire before it blows! This level of intelligence means you are now planning for things that have a high accuracy of happening when you have the time or dollars--not when the action dictates it. This will lead to less cost, faster action, and better results.

Why did that happen?

With a robust data set you can use the information you know for a fact to predict outcomes. You can now act proactively--Change a belt before it breaks or order a tire before it blows! This level of intelligence means you are now planning for things that have a high accuracy of happening when you have the time or dollars--not when the action dictates it. This will lead to less cost, faster action, and better results.

What Just Happened

Business Intelligence takes the data you’re tracking and puts it into a visible format. Visuals allow you to identify trends and see patterns you could never discern otherwise. It also allows you to make decisions off this data rapidly. This rapid decision making and formerly unknown pattern recognition makes Business Intelligence a minimum for success. 

What Happened Yesterday

The first step to working with data is simple record keeping. Tracking your data points allows you to build more complex data driven decisions down the line. It is important to make sure you’re tracking the valuable data points that drive value later.