Last week I attended the 2016 Insurance Data Management Association Annual Meeting and Seminar. The theme of the two-day seminar was The New ABCs for Data Management Professionals – Analytics, Business Intelligence, and Cyber Risk.
This was the first insurance conference I've attended and it was a really great learning experience. I think it's important, especially for recent graduates, to be able to take a break from the typical day-to-day work to learn about other aspects of the industry and stay on top of current news and changes that may be on the horizon (key word: industry disruption). It's becoming more and more important to think of innovation, whether it's product innovation or process improvement. Innovative companies are and will continue to be some of the most successful companies, and the same can be said for people. Attending a conference is definitely a great way to get those innovative juices flowing and provide additional insight outside the scope of your work.
If you are just starting off (or looking to start a career) in the insurance industry, I hope my key takeaways from the 2016 IDMA Seminar listed below can provide some food for thought.
Design, Influence and Culture
The keynote speaker from XL Catlin did a great job of describing the "Analytics Journey." In order to implement a successful data analytics program, three key components must be considered: design, influence and culture. Far too many times, design and influence are the main focus. There needs to be a balance between all three to run a completely successful data analytics program. I believe, in a way, this can apply to a lot of different projects - not just data driven programs.
Design - The program must fit seamlessly into current processes, helping to improve workflows. The implementation of the program should make processes run smoothly and more efficient.
Influence - Find the people who have heavy influence on others in the organization. These could be heads of divisions or those who have a large social network. If they are on board with the new program, they will be able to get others on board, too.
Culture - When implementing a new program, share metrics. Celebrate victories and let others know this is something that is valued. If others are able to see how important a program or initiative is, they will be more excited to participate and help the program succeed.
The most important message of this keynote was that analytics needs to become a larger part of the company culture at insurance companies. Design and influence are the more obvious components of implementing a successful analytics program, but it's just as important to try to find ways to incorporate analytics into the culture.
How can this relate to an entry-level position? Chances are at this level, you will not be implementing a data analytics program or creating a new department. However, it's still important to keep the three points above in mind while performing your day-to-day work tasks. Think of how you can work on improving processes and making them more efficient. Work on building your network at the office. Learn what other teams are working on and share any successes you've had in your team when chatting with others.
Design - The program must fit seamlessly into current processes, helping to improve workflows. The implementation of the program should make processes run smoothly and more efficient.
Influence - Find the people who have heavy influence on others in the organization. These could be heads of divisions or those who have a large social network. If they are on board with the new program, they will be able to get others on board, too.
Culture - When implementing a new program, share metrics. Celebrate victories and let others know this is something that is valued. If others are able to see how important a program or initiative is, they will be more excited to participate and help the program succeed.
The most important message of this keynote was that analytics needs to become a larger part of the company culture at insurance companies. Design and influence are the more obvious components of implementing a successful analytics program, but it's just as important to try to find ways to incorporate analytics into the culture.
How can this relate to an entry-level position? Chances are at this level, you will not be implementing a data analytics program or creating a new department. However, it's still important to keep the three points above in mind while performing your day-to-day work tasks. Think of how you can work on improving processes and making them more efficient. Work on building your network at the office. Learn what other teams are working on and share any successes you've had in your team when chatting with others.
Data Management is Key For Future Success
We are living in a data driven world. At times, it can be overwhelming. Companies are receiving more data and information than they've ever received. It's critical this data is managed in a way that can allow for quick use and decisions to be made. Here's an alarming quote from one of the breakout sessions I attended - "By 2017, 33% of fortune 100 companies will experience an information crisis". That's crazy to think of and it's important for companies to make sure they are managing their data in an effective way. It's no coincidence that data scientist jobs have skyrocketed recently (although, in another session it was mentioned that machines will replace data scientists in three years, so who knows!).
Improved data management will allow companies to come out ahead of the competition and leaders will be able to:
This is especially important in the insurance industry as there is more discussion surrounding product profitability and increasing revenue. This will be done through analytic decision making and innovation.
If you are interested in more information on how companies are interacting with the abundance of data and information, the IBM C-Suite Studies were recommended to check out.
How can this relate to an entry-level position? If your job requires you to analyze data, see if there are ways the data can be improved in any way or more meaningful. Depending on the type of information you work with, maybe there are inconsistencies in how the data was captured at a certain point. Would normalization be possible? Can additional fields be added that are captured elsewhere? Can additional analysis and decisions be made if more fields are captured? Think of how value can be added and make those suggestions.
Improved data management will allow companies to come out ahead of the competition and leaders will be able to:
- Drive improved business outcomes
- Capture the time value of data
- Change the game
This is especially important in the insurance industry as there is more discussion surrounding product profitability and increasing revenue. This will be done through analytic decision making and innovation.
If you are interested in more information on how companies are interacting with the abundance of data and information, the IBM C-Suite Studies were recommended to check out.
How can this relate to an entry-level position? If your job requires you to analyze data, see if there are ways the data can be improved in any way or more meaningful. Depending on the type of information you work with, maybe there are inconsistencies in how the data was captured at a certain point. Would normalization be possible? Can additional fields be added that are captured elsewhere? Can additional analysis and decisions be made if more fields are captured? Think of how value can be added and make those suggestions.
Let Machines do the Dirty Work
Machine learning definitely seems to be gaining traction in the insurance industry. This is huge. If a computer can be programmed to perform more of the mundane tasks of running programs, transferring information, and setting up analyses, then more time will be available to analyze the data and perform other important tasks. This is especially useful for processing that may be prone to human error.
Looking at the insurance industry as a whole, machine learning can have an impact on a variety of areas:
How can this relate to an entry-level position? Start small. If you find yourself having to repeat processes multiple times in excel, try to create a program in VBA to reduce the time spent on mundane tasks. If you work with data, learning how to code will definitely help you become an asset to your company. Try to see if machine learning could have a positive impact on your work.
Looking at the insurance industry as a whole, machine learning can have an impact on a variety of areas:
- Predictive target marketing for insurance quotes and financial advice
- Fast track underwriting, reducing the amount of time to underwrite a policy
- Form digitization allowing classification based on form type
- Personalization for customers
- Cut down claims cycle, reducing interest costs
- Identify higher risk activity and suspicious claims
How can this relate to an entry-level position? Start small. If you find yourself having to repeat processes multiple times in excel, try to create a program in VBA to reduce the time spent on mundane tasks. If you work with data, learning how to code will definitely help you become an asset to your company. Try to see if machine learning could have a positive impact on your work.
This blog post was featured on Verisk's Between the Lines in June 2016. To view the updated version, along with other blog posts on emerging issues in the property/casualty industry, click here.
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