Since 2008, Contemporary Analysis (CAN) has been the way companies learn about, train for, implement, and support data-driven decision making, predictive analytics, data science, AI, and machine learning.

Where are you in the data hierarchy?

CAN has created a unique process for implementing data-driven decision making in organizations. This process gives our clients the right knowledge at the right time as well as a visual roadmap of where they are going and how to get there.

Our process is a plan to help your organization move forward through the various levels of Data Hierarchy, which include:

Reporting

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.

Business Intelligence

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. 

Descriptive Data

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.

Predictive Data

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.

Prescriptive Data

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.

Machine Learning

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. 

Artificial Intelligence

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

Artificial Intelligence

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

Machine Learning

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.

Prescriptive Data

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.

Predictive Data

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.

Descriptive Data

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.

Business Intelligence

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. 

Reporting

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.

Our process

CAN’s role is helping companies INNOVATE their processes, TRAIN teams to perform and manage information-driven decision making, INCUBATE a data science team for companies, and MENTOR the organization to build a data-driven future.

LEARN MORE ABOUT THE DATA
HIERARCHY & OUR PROCESS

OUR PREVIOUS CLIENTS

Areas of Expertise:

ARTIFICIAL INTELLIGENCE

DATA LEADERSHIP

analytics & data management

DASHBOARDS & VISUALIZATION

BUSINESS INTELLIGENCE

PREDICTIVE ANALYTICS

DATA
ENGINEERING

Model Development

MODEL SUPPORT & MAINTENANCE

SOFTWARE DEVELOPMENT

MODEL SUPPORT & MAINTENANCE

SOFTWARE DEVELOPMENT

Company Support

STRATEGY & VISION

RESEARCH & DEVELOPMENT

STAFF TRAINING