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5 Tips to Prepare for Human Capital Analytics: Chris Brunson, VP Total Rewards, Celanese

Uncategorized Feb 06, 2020

Summary of Guest Speaker by Emma Lokar, HR Intern (Looking for a Summer 2019 Internship) 

5 Tips to Prepare for Human Capital Analytics: Chris Brunson, Celanese, VP Global Total Rewards

Story Telling of Data
Chris Brunson is the VP of Global Total Rewards at Celanese a $6.1 Billion global technology leader in the production of differentiated chemistry solutions and specialty materials used in most major industries and consumer applications. Brunson has extensive experience in Human Capital analytics in Human Resources with  different sized companies in several different industries.

Chris shared his Five Tips to Prepare your Company for the New Age of Human Capital: How to handle your data, manage your data, and hire for your data...even when you are not good with numbers! Good analytics tells a story. The insights an organization receives from analytics gives the business actionable items to accomplish.

Five Steps
In today’s climate human capital analytics has the power to derive data that can transform decision making. Adding value is at the core of what business are trying to do. When you think about value creation Finance and Supply Chain has had their day. Human Capital insights are the next big wave and using it to tap into the potential of people.
1 - Ask Better Questions
Many companies focus on reporting and dashboards, but what they need to be doing is hone in on pure analytics. Reporting is asking, “What is happening?” and analytics is asking, “Why is it happening?” and “What can you do about it?” The most important part of beginning the journey of analytics is asking good questions. If you are not asking great questions, you’re missing the boat to derive that value.

Organizations are asking too many self-evident questions.

An example within Celanese was when the company was looking at developing their next wave of leadership. Instead of asking for a turnover report the analytics team asked, “What’s the probability of someone in this company getting multiple promotions?” That is the hallmark of development, and the data revealed Intern’s received multiple promotions within the company. Thereby, displaying the value of an internship program.

2 - Use Simple Tools
In Human Capital analytics complex platforms are not needed to find usable data. Brunson explains the data work they were doing was done through Excel, an application on virtually everyone’s laptop. Using fewer complex tools challenges the basic assumptions of HR. This ties back to asking better questions. When you are asking the right questions, you don’t need advanced systems to look at data.

3 - Focus on Clean Data
Clean data over connected systems like SAP and Workday is essential. If data is miscoded in these systems, the results are not impactful.

Information that is unstructured and together naturally shows connections.

Create the processes in your organization to gather data. These systems do not always need to talk to each other. You can take the two systems separately and put them in a simple data link like Excel and find the relationships there. This brings cost down and makes gathering data more widely available.

4 - Avoid Over Investing in Hype
Brunson shares that too many companies are wasting money and resources on dashboards that are visually attractive, but they could benefit more by investing that money in an employee with the skill set to play with that data.

Often times these employees generate better insights from the data. Companies should invest in more robust analytics, because systems don’t work without underlying competency. Be uncomfortable in hiring. Look for diversity of thought and find someone who knows how data works. This might mean they are not always from a Human Resources background.

They’ll be worth their weight in gold. There’s an element of creativity in HR hiring.

These employees can continue to challenge the basic assumptions and give you something you weren’t expecting.

If they seem like they might be different, they might be worth the risk.

5 - Watch Out for Data Privacy Considerations
As human capital analytics continues to emerge it is vital for companies to be mindful of their employee’s personal privacy. An organization might need employees consent to transfer their data from internal systems to third-party administrators. The European Union has created General Data Protection Regulations. Celanese has taken the EU’s regulations and made it their global standard. When taking an employee’s personal identifiable information to a third-party administrator you need their permission. There is a lot of legality, but it is important to work with lawyers.

As HR professionals we need to be careful how we are using people’s data, and do not violate a person's trust.

(If you would like to read more about the General Data Protection Regulations click HERE). 

Transformation of Analytics to AI
Chris describes that Total Rewards can be like banking where there are general rules of thumb that you are comfortable with decisions being made from.

You stay within the navigational beacon when it comes to adjusting things such as people’s pay.

In the path of not following dashboards Chris tapped into people development using the creative talent of analysts. The analyst came to Chris with a prototype of a Chat Bot. This Bot would answer questions and interact with a manager about pay decisions. This took the static analytics and generated insights for who should be promoted, who is going to leave the organization, and who should get paid.

When you do this you get push back, but the value is in the analytics and transformed into emerging AI.

Last Advice
When starting at the elementary levels of analytics the most important things is Tip One: Asking Better Questions. This is really at the core of great analytics. Challenging yourself to rise to those standards and how you are looking at problems.

There are a lot of ways to get up to speed on emerging analytics:

1. Dave Ulrich’s book “The Leadership Capital Index” 
2. Be open to the diversity of thought, and link with great data thinkers outside of HR.
3. Within HR there is your Compensation and Benefits team. They are responsible for the largest amount of clean employee data within the organization.


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