Data-driven Decision Making Transformation
For Human Resources Leaders who want to cut their turnover by 50%
GH Smart is a consultancy working with large financial corporations on their hiring process.
There were three main questions:
1- How to identify top performers in the hiring process?
2- Why did we like someone enough to give an offer to and we ended up firing them?
3- How can we retain top performers?
Who This Is For
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If you are trying to lower your employee turnover.
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If you are worried that newly hired employees and/or high performing employees can quit anytime.
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If you have struggled with employee retention especially in the past couple of years due to remote work environments
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Companies with better offerings either financially or a more flexible work environment.
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If you suspect that there must be a better way to lower your employees’ turnover
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Everyone is going through organizational transformation especially post Covid-19
The Core Concept
You can save time and money and the company can significantly uplift its revenue by implementing a well-designed data-driven human resources hiring and onboarding process.
However, most Human Resources leaders are still managing the staffing process without implementing a holistic data-driven approach to manage the entire staffing process.
We are one of the very few people who are dedicated to solving this particular problem for Human Resources Leaders
Data-driven Human Capital Strategic Indicators
The Old way
- HR leaders set the strategic direction for the Human Capital of the organization according to the company’s values and culture.
The Old Result
- Indicators on character don’t always predict fit for culture or performance level.
The New way
- Making decisions on strategic Human Capital direction in a data-driven way
The New Result
- This results in lowering turnover as well as increased overall performance.
Is there a standard practice on how to implement a data-driven method to hire the right talent?
Each organization will be unique in the way it implements new data-driven methods based on what the analysis of their data will show them. However, the core concepts are the same and there are best practices that need to be applied
Data-Driven Proactive Retention
The Old way
- Employee retention starts when the employee gets an offer, line managers set development goals to (in part) retain top performers.
The Old Result
- This leads to a repetitive cycle of employees leaving for the same reasons, getting better offers.
The New way
- Data-Driven Human Capital Management provides a way to be proactive in the top performers’ development plan, giving employers the opportunity to retain them before they think of looking around.
The New Result
- This leads to lowering turnover as well as increasing the organization’s efficiency and productivity
What kind of data repository do we need to implement?
It can be a database/data warehouse, it can even be a process of collecting the data and storing it in one place. This depends on the size of the data that needs to be analyzed
Data-Driven Optimized Retention
The Old way
- Retaining top performers is a decision usually made by the line manager, and the constraints are usually budget ones.
The Old Result
- This results in high talent employees leaving the organization for better offers.
The New way
- Data-driven retention not only looks at the cost-to-hire, but also the cost due to performance differences between current and future employees.
The New Result
- This cuts turnover by 50%.
So to Conclude, All You Need To Do is:
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- Implement a model for Data-driven Human Capital Strategic Indicators
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- Implement a Data-Driven Human Capital Management solution which provides attrition prevention roadmaps
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- Implement a Data-driven retention model that not only looks at the cost-to-hire, but also the cost due to performance differences between current and future employees.
Now there are a few ways to achieve this
01
Do it yourself or hire a few consultants
Do it yourself or hire a few consultants to set up your project/product portfolio practice and they can attempt to do it in a data-driven way, however this will likely fail because:
- Consultants that understand Data Analytics are more likely to hold expertise in their technical fields but lack the Human Resources skills.
- Human Resources leaders who can guide and help apply new strategies for hiring, turnover, and retention lack the analytics and data science expertise.
- The skills needed to set up data-driven tools that analyze, optimize, and proactively handle hires and probability of turnover are so specialized, it will take you at least 12 hours per day for 1 year to become proficient without any help.
02
Work with Smplcty
Or you can work with Smplcty and owen your turnover by 50%, which will save you an estimate of 33% of each hired employee’s salary that you avoided hiring which will be 4 times faster and 4 times cheaper”
Who This Is For
Again, this is for Human Resources Leaders who want to cut their turnover by 50%, but are struggling with making the tough decisions of hiring the right fit employee and/or retaining top performers to have the time to focus more on other high-growth potential opportunities.
“Here’s what is going to happen when you work with us”
Turnover
You will be able to lower your turnover by 50%.
Efficiency
You can save 33% of the total salaries of employees you avoided hiring.
Decisions
You can finally make tough decisions about hiring the right fit employee for your company.
Time
You can forget about time and resources wasted.
Confidence
You will feel confident and empowered because all your decisions are now backed by well-designed analytical solutions.”
Consider this study
How It Works
Before, when you wanted to hire for a certain position you would have to guess whether the candidate was the right fit for your company or not. But now, you can use a simple Data-Driven tool to determine to a great level or certainty if the candidate is the right fit or not. Saving you 33% of his annual salary if you would have had to replace him/her a few months later without wasting time, energy or resources. Do you see how easy that is?
