Frame Of Reference
Analytics in Operations Part 2: An analytics map, systems, tools, methods, process and communication
An Analytics Map
Are you trying to improve analytics in an operations function (finance/FP&A, HR, business development, etc)?
Do you wish that you knew more about data and analytics?
Would it help to have a map?
The nature of operations leads to analytics challenges in operations functions that can undermine company performance. These issues arise because of weaknesses in one or more of the following areas: systems, tools, methods, business process, and communication. Understanding these components, as well as how they’re connected and impact analytics will help in understanding and addressing analytics challenges.
Systems
Systems are where data is entered and stored. There are a wide variety of systems used by companies. These include human capital management, customer relationship management, talent management, enterprise resource planning, and more.
WHY THEY MATTER
While largely the domain of IT, ensuring high-quality data requires input from business teams and good communication between business and technology teams.
Tools
A wide variety of analytics tools exist, from basic and user friendly to advanced and complicated, and from general to highly specialized. These include business intelligence/dashboard tools for reporting and data visualization, as well as more powerful analytics tools and programming languages for data analysis and data science.
WHY WE NEED THEM
Tools are used by anyone who needs to work with data, which is just about everyone now. These are software packages that can be used to extract, aggregate, transform, analyze, and visualize data. Excel is still the most widely used tool today but, as you may have experienced, it has its limitations.
Methods
Tools are only helpful if people know when and how to use them. Even Excel requires some basic data analysis knowledge.
WHERE THEY COME IN
To use these tools effectively analysts must know or learn analytics methods including data cleaning, data integration (combining data from multiple sources), data transformation (changing the structure or format of the data), statistical analysis, and data visualization.
More advanced analytics professionals (like data scientists) must have knowledge and experience with more advanced analytics methods such as modeling/forecasting or handling extremely large or real-time datasets.
Business Process
A business process is why systems exist and why tools and methods are needed.
THE STARTING POINT
These processes are necessary to run a business and will determine what type of data is collected and stored, and which reports are needed to support the process.
Understanding the types of problems a business is facing will influence the type of analysis needed to understand and solve these problems.
It’s critical to start with a good understanding of the business process. This will inform the data and analytics requirements and drive decisions about systems, tools, and methods.
Communication
Successful business processes require good communication. Multiple skillsets, departments, and people are needed to meet the analytics needs of business operations. Better communication skills are critical for everyone.
THE DIVIDE
Unfortunately, there is often a disconnect between the technology and analytics teams and less technical business teams. Better understanding of the challenges in each direction can improve coordination and project outcomes.
Full Circle
Systems, tools, methods, business processes, and communication are key pieces of a successful analytics process. Understanding each of these pieces and the connections between them provides more context when thinking about both the nature of operations and the analytics challenges in operations.
With this map in mind, the next post in this series will consider the analytics challenges in business operations.
Do you need guidance in how to improve reporting and analytics in your operations functions?
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About the photos: In memory of Ariel, companion, hiking buddy, and therapy dog.
Thoughts: Ariel was the inspiration behind the name Ariel Analytics. She was an avid hiker and a certified therapy dog who loved to visit the local nursing home and make people happy. She persevered through many challenges in life (including being in a shelter and having knee surgery - twice). She was an inspiration to all who met her. I wish I could say that she was a great guide though the wilderness, but while she had a fantastic memory and was a great communicator, search and rescue was not her calling. Sadly, we lost Ariel to cancer in February 2020, but her memory lives on as our company namesake.
Have a data or analytics question that you’d like to see answered here? Email your questions to stacey@arielanalytics.com.
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Stacey Schwarcz is the Founder and CEO of Ariel Analytics. She specializes in analytics for business operations, helping these functions improve their analytics capabilities. She is also the creator of The Data Wilderness ® Blog, which provides practical introductory analytics content for business professionals who are not analytics experts and want to learn more. LinkedIn