What Anthony Nelson learned from attending Analytics Value Training
Becoming a data-driven organization is not necessarily easy. It requires a genuine culture change in the organization, and it needs everyone to have the skills required to use data and analytics—and to understand the insights that they provide. This is simple to describe but can be extremely difficult to achieve.
SAS has recognized this issue and put together a training program on analytics value and transformation. It is designed to help both individuals and groups from the same organization. The program lasts 8 to 12 months, to give plenty of time for participants to change their behavior, and develop the mindset required to use data and analytics. It includes virtual session days to provide the theory of the key models required for analytics success, and coaching and hands-on learning days. These are spread across the program period to cover the four elements of foundation, deployment, advanced and AI/use case.
The main purpose of the training is to give attendees the knowledge, skills, and abilities to handle data and analytics as part of their day-to-day work. More importantly, perhaps, it also aims to provide students with a solid mindset that is focused on the regular and routine use of data and analytics to understand customers, situations, and problems.
I recently attended the analytics value training program as a attendee, and have also spoken to a couple of customers who have attended the course. I therefore feel well placed to comment on what I’ve learned, and how it has changed my approach to analytics within organizations.
- The unexpected lessons are often the most important
Going into the training, I hoped to learn more about how analytics and data-based decision making operate within the insurance industry. More broadly, I also wanted to understand how we can help organizations to derive value from investments made in analytical software and in data science. That aim was definitely accomplished.
Perhaps more interesting was the unexpected learning that I had not previously considered. For example, I saw clearly in the program that analytics value training can build really strong bridges between data science teams and frontline service teams. I think all organizations face this problem. They have highly experienced data scientists who are great with data and algorithms. However, they often have relatively low levels of business knowledge or industry experience. On the other side, organizations also have business teams with deep industry expertise and knowledge, but little or no analytical experience. Analytics value training is all about bringing these two groups together and helping them to collaborate more effectively. It gives them a common language, and a much greater sense of what each group brings to the table.
- You will learn more if you are prepared to go outside your comfort zone
The second lesson for me was an interesting one. A lot of the people in my program were data scientists. My general impression from all of them was that they would have liked more data science in the program. They wanted to roll up their sleeves and do more hands-on algorithmic thinking, and perfect their craft a bit more.
The issue is that this is their core competence, and their comfort zone. It’s therefore completely natural that they wanted to focus on that—but it wasn’t really what they most needed from the course. Instead, they needed to understand more about how to collaborate effectively with the frontline teams and think about data availability from the customer’s perspective. The program forced them out of their comfort zones, and into those new areas. Sometimes you need to be forced into thinking about new issues, because it’s easier not to bother. However, when you are prepared to go there, you can learn a lot more. Similarly, for the frontline people, it is helpful to get more insight into how to leverage data effectively, and how it can be used to answer business questions.
- One of the best possible outcomes is having the tools to answer your own questions
Analytics value training gives organizations the tools to self-assess themselves and their analytical proficiency. They can look across seven critical data or analytical dimensions and rate their maturity. This framework can be used to help organizations to make decisions about where and how to invest in analytics, and how to prioritize various areas for development. Effectively, the training gives participants and their organizations the tools to reach analytical maturity by themselves—and that is enormously powerful.
More information
Analytics Value Training AVT start
The program for team or organizations, Analytics Leadership Program ALP package
