https://www.fastcompany.com/3034748/how-evolv-is-arming-companies-with-predictiv
ID: 3354600 • Letter: H
Question
https://www.fastcompany.com/3034748/how-evolv-is-arming-companies-with-predictive-data-on-employees
Review these case studies of companies that utilize Big Data. The selected companies are e John Deere .Airbnb Fitbit These case studies are in Big Data in Practice by Bernard Marr. Also, please read Employees and answer the following questions in this discussion forum: 1. Can analytics replace the gut decision 2. The Evolv CEO claims that he needed to making for hiring employees? Why? make sure that he had the right team to build and grow his vision. He needed a team to start with. So what came first - developing his model or hiring his team? How do you think he hired his original team? 3. Will Big Data replace the traditional HR department? 4. What is harder to do hire or fire someone? Why?
Explanation / Answer
Answer -1
Big Data and the intelligent use of Analytics has been one of the top usages over recent times. For anyone working in human resources or recruiting, ever greater use of data promises a revolution in the way decisions are made. Recruitment and retention of top talent differentiates a company from its competitors. Gut decisions and interviewer bias are replaced by evidence-based decision making.
To be clear, leveraging data presents both a challenge and an opportunity. The challenge is to learn the skills – and choose the technologies – needed to analyse the mass of data available within a company. Looking beyond that, we also need to start collecting actionable data that has hitherto not been collected. The opportunity is significant though – to improve outcomes across all areas of HR recruitment .
Benefits of Using Data In Recruitment
Many elements of a recruiter’s life are made more frustrating through a lack of data and insights .
The right data can help manage the expectations of hiring managers. Retention data can highlight the elements of your offer where the recruitment team are consistently overselling to candidates.
When it comes to which criteria to include in a job listing to produce the best quality of hire, data can give us the answer. With the right data points we can find out which skills, values and behaviours lead to a hire who is likely to be a success in the organisation and remain in their position long term. Those insights can be derived client by client or department by department.
Most companies know the applicant volumes they are getting from each source. Most know the shortlist candidates and even hires that each is producing. But we need more data than this to make informed decisions. Which talent sources bring in our highest achievers? Which talent sources produce hires whose retention rates are the most compelling? If data gave us these insights, we can imagine how your choices of where to invest might be impacted.
How Are Recruiters Using This Data?
To put the uses of big data into context and help us to better comprehend how we might use it, there's a great case from Xerox Corp. Xerox had estimated the cost of training each of their call center staff at $5000, yet many were leaving before Xerox could even recoup their training costs.The business had traditionally assumed that those with call center experience were more likely to succeed; however, analysis of the data proved otherwise. The data showed that candidates with experience cost more to hire, yet didn’t perform better or last longer than those without experience. The data also showed that those candidates who were active social media users had higher retention rates than other candidates. Another surprising insight was that creative types tended to stay with the company longer than inquisitive types. Analysing big data helped Xerox to cut the attrition rate at their call centers by over 20% – a significant and tangible financial saving, as you can imagine!
We can make use of data for informed decison by developing a clever system that aims to remove pain points in recruitment by first collecting and then analysing the most essential data in the recruiting process. This provides recruiters with the insights needed to make the right hire each time, from a smaller shortlist of candidates and with less time therefore needed to complete the recruitment process.
Research has shown that 90% of the data in the world today has been created in just the last two years, so Big Data use is expected to accelerate dramatically as far as hiring process is concerned. In the past the sheer cost and complexity of connecting and analysing so many data points made the use of big data within recruiting impossible. However in the past couple of years we’ve seen a rise in the number of analytical tools available to make the use of such data cost effective.
This realm of data analytics affects every area of the recruitment process including:
With such overarching effects, it’s no surprise that recruiters and employers alike are clamouring to invest in talent analytics to help meet their talent needs. The future will see recruiters using a 360 holistic approach to finding and assessing talent. One dimensional CVs and applications will be supplemented by social media data, online assessments, departmental profiling and past hiring success and failure data to more accurately assess a candidate’s chances of success.
Few important hiring querries that must be analysed are :
2). As already discussed in answer 1, any hiring today must be based on the information obtained from analysis of existant data. However when we start a process, then there will he very little data available which relates to the process directly. In such cases, we take decisions based on benchmarks of competiting similar process or based on our resources avaialblity. Once whe have taken a decision ,we carry on with the process and build data and in due course of time based on the data build up we implement data analytics in the process and keep on enriching it sustainably.
I agree with the views of Evolv CEO that he needs a make a team before making his model. This is so because a model will need resources for its creation and implementation. He can make his team based on his vision and trigger the model. As time goes, he will get data and by analytics he can fine tune on the quality of his team by inducting or firing experts.
3).big data is gonig to substitute traditionally run HR . this has been discussed in details in answer 1.
So of the salient points that substantiate my view are :-
1. the volume of data is increasing exponentially ( more than 90% of all world data was created in last 2 years). This cant be handled in traditional analysis.
2. Big data brings several layers of analysis which helps facilitate efficient decision making.
3. Traditional HR fails to give 360 degree view of the HR process which is given by big data.
4. Traditional HR cant anticipate future scenario efficiently and hence companies relying on it will be weeded out for lack of outlook .
4). Both have their own level of rigour.
Hiring requires lots of analysis ,fitment ,expenditure etc. While firing is more of an emotional issue which requires an organisation to be strong enough to say good bye .Clearly firing involves sunk capital in terms of employee managmenent cost (traiinng, working ,overhead etc)
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