Calculus Help Centre

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How is it better than compensation reports produced by Aon and Mercer?

The biggest challenge with the compensation reports is that most of them are static and you will not have access to real-time data. Also, that is something you cannot play with or can change parameters. The advantage of Calculus is that it's a tool that synthesises and develops that report in real time based on the input you provide, rather than a collection of static reports that have been curated. It also represents changes on a real-time basis, any fluctuation in the market is automatically represented by the insights on the platform.
How is it better than Linkedin Insights?

The heart of this data is Salary in Calculus which we think is missing in Insights. A lot of partners tell us, That there is no substitute for Calculus, Since no other Product/ service can actually help you backtrack this data and see the profiles in real-time and help you calibrate the queries/roles you are searching for. Also, say with Linkedin Insights, it is more relevant for the global market but for Indian job markets and prospecting employees, Calculus has no substitute.
We would like to understand what is the salary structure around a median salary? Does the system capture fixed and variable salaries separately or are we seeing CTC as the median salary? And what about other benefits like bonuses, ESOPS, Retiral benefits. How does Calculus capture all these extra benefits?"

We ask candidates for their total payout. You know every organisation has a different way of structuring that salary and other incentives. As we develop this product we intend to go deeper and understand and represent those salary structures as well.
Can we drill down the data? By sector or Industry (Retail, BFSi, Telecom, Consulting)? If we see for example, that captives in BFSI in Bangalore have x demand at a certain median salary, we can strategize about our pay levels much better."

Yeah, absolutely we can drill down and it is a function of how you structure the query and how you put in those keywords. For instance: If we are looking at Equity Research from Telecom. Then we could do "Equity Research" and then select Telecom from Industry as a filter. You can also select any specific industry, So all that is available in the product helps you define the segment better.
How are the insights accurate? I feel the sample is too less.

For a Successful Statistical evaluation, a sample is drawn instead of the entire population. In this case, a subset of candidates for a specific query within a population. While sampling a frame, the system is sophisticated enough to remove any personal bias in order to provide you with the most accurate information. Calculus is based on a machine learning platform, and it is self-learning. It curates a sample set & removes ambiguities and questions that would otherwise have been overlooked with a basic keyword search. It works on stratified sampling methodology, where all the elements of the population are embraced before concluding the insights. All the outliers & misnomers etc are automatically removed. Which leads to minimal error and accurate real-time insights.If you want to look at the entire population, you can always go back to our database and have a look at all the profiles.
How do you plot the demand trend? Do you also consider job postings done on Naukri.com as well?

We only look at the database of iimjobs.com for this analysis. We get demand from a number of jobs getting posted and keywords searched have been made for the same skill set. For example, there are skills in New Technologies such as Data Science, IoT, Machine Learning and robotics which are like very fast-growing skills, where you might want to revise the compensation every quarter, just because there is high demand and very little supply.
Why do some candidates expect higher salaries than others in this distribution?

Our sense is that candidates don't think through some of this, while they are putting expected salary data, a) They don't have the perspective that employers do b) Most people will put an even number there. So anyone at 42 would put 50 L or anybody at 4 would say 10. So This is why this graph is sometimes patchy because there are levels and people want to move to the next level in compensation. That's why you see every time this median is actually at a different level in expected salary.
What is the source of this information? Are you getting it from the market or Employer?

The Source of this information is the candidates itself. Whenever a candidate is looking out for a job & register themselves on iimjobs.com or hirist.com they fill in their personal information like current salary, preferred location or past experiences etc. Candidates are the primary input for calculus insights. 1.8 million profiles are registered on iimjobs.com & 1.2 million profiles are registered on hirist.com. We do not consider the information coming from the market or any other organisation.
Can we benchmark various roles basis companies?

Yes, we have a filter called organisation where you can narrow down your search even to a company level.
Do you plan on including the database of Naukri on Calculus?

No, Both Naukri and iimjobs.com have well-defined segments to which they cater to. iimjobs only focuses on the mid to senior and premium colleges segment. Which works really well for us. We have received multiple feedbacks from our HR partners, stating that the activeness of profiles from this segment is maximum here.
How is it better than Insights from Social platforms?

The heart of this data is Salary in Calculus which we think is missing in other platforms Since no other Product/ service can actually help you backtrack this data and see the profiles in real-time and help you calibrate the queries/roles you are searching for. Moreover, in Indian job markets and prospecting employees, Calculus has no substitute.