Tuesday, September 13, 2022

SHADOW OF THE BLACKGHOST

(EFFECT OF BLACKLISTING AND GHOSTING ON YOUR CAREER AND LIFE) - Life Coaching Series


He’s a published author, a doctoral scholar, a mentor, a business consultant and much more. He has worked with fortune 500 companies with his career spanning across 2 decades and 4 continents. He has also won a few professional & business awards and has led a quite successful life from the POV of a common man.

But strange as it may seem, he’s grounded since the last 2 years and unable to find any meaningful employment. He’s not outdated or redundant since he has upskilled himself in the recent years, has an ATS compliant CV and an excellent LI profile. Furthermore, he has a good network of former colleagues and clients who he can always contact and quote for any reference check. He’s bemused and dismayed at his present predicament. He has been applying to several relevant and matching positions online at many popular jobsites since that has become the norm in the post-covid era. There have been several occasions when he has encountered the following patterns explained further.


Note: The above process flow is from the POV of the jobseeker and does not depict the hiring process.

At different stages of the hiring process, he has experienced something called as “GHOSTING”. A brief snapshot of the scenarios is listed below as shown in the above diagram:

  • a.       No further communication after receiving an initial shortlist email from the recruiter
  • b.       Recruiter does not respond to phone calls or emails after the initial screening call
  • c.       There is no interview / meeting link received after it has been scheduled OR recruiter gives a “NO SHOW” for the pre-scheduled interview
  • d.       Recruiter does not update the status or communicates further process after the interview
  • e.       Recruiter literally acts like a ghost and becomes uncontactable OR passes the buck asking you to contact someone else in the organization who has no idea about your status of application
  • f.        Recruiter ditches you at the last minute and conveys a rejection (usually without justifying any reason) after finalizing terms of the offer

When these similar scenarios keep repeating over and over again, he gets into action. Being an adept and seasoned professional, he reviews his digital presence by doing a basic OSINT exercise on his own online accounts. Here’s the summary of what he finds initially:

  • 1.     LinkedIn profile has a social score of 90 and all his data is verified
  • 2.     Resume has an ATS score of 84 and all the information is true to the best of his knowledge
  • 3.     Other social network profiles do not have any offensive, violent, abusive, sexual, or objectionable content
  • 4.     All his online accounts are secure with 2-step verification enabled
  • 5.     SEO ranking of his name and associated identities is also good
  • 6.     He doesn’t have any unknown contacts / unverified accounts connected to his social network

So, he wonders that he is probably amid a “Mid-Life Crisis” and eventually things will change for the better. But there are questions that keep haunting him night and day –

i.      How will I explain this gap in my career? Sundry projects / freelancing / part-time work / volunteering are not going to add up to anything worthwhile!

ii.    Why am I going through such a rough phase? Never been removed or laid-off from any job, never had behaviour or character questioned, never lied or misrepresented facts, never hidden anything relevant, never been into any type of criminal activities or misconduct, never been into any type of political activism or never committed any type of fraud, then why?

There are many such cases of innocent individuals whose career and life has been affected by a term called as “BLACKLISTING”. It is the blackhole of the HR domain that very much exists but is denied by everyone in the industry. I’m not referring to a plain simple case of blacklisting of prospective candidates by individual recruiters for genuine or not-so genuine reasons. That is done by every other company on the planet over their internal database. What I’m referring to is the maintaining of a very large database of persons and other entities that is subscribed to by several large corporates including background screening and verification companies. Such databases are often stored secretively and shared with select few members within the HR domain in the corporate world. Prima facie, there shouldn’t be any problem in doing so since organizations need to keep a tab on who enters their organization as it is all about brand management and goodwill. The problem lies in the legitimacy and integrity of the data that is often scoured from several sources including third party operators, contractors, and sub-contractors. The moot question is – How reliable are those players and who owns the accountability for maintaining such a database? Let me clarify that I’m not referring to data protection laws or right to privacy legislation here at all.  Please note that this is something maintained privately and is not a government database like “Early Warning System” (EWS) of the UK or “Global Internet Forum To Counter Terrorism” (GIFCT, maintained by internet & social media giants) of the US that is referred to by government agencies or SITA Goods & Passenger Tracking System (S-GPTS, aviation industry) accessed by most airport authorities worldwide.

A few names that I’m aware of are First Advantages Esteem, Lexis Nexis, Skynet, World Check Database, Refinitiv World Check Risk Intelligence, Facebook Secret Blacklist, etc. There are big corporations that maintain some of this type of database like Thomson Reuters, Stratfor, Pinkerton Global Intelligence, etc. Once your name / identity gets inserted into it, a tag / label is attached which can classify you as a “Heightened Risk Individual” or “Dangerous Person” or similar category for no mistake of yours. The database need not mention anything to justify the tag or could also contain falsified information. This is sufficient to deny any opportunity in the corporate world and even bring you under the radar of various government and / or private agencies. Further, forget about correction, there is little you can do to even request access to such data as an individual.     

This type of approach can lead to a tragic “comedy of errors” (compiled from real-life incidents from various sources) as shown below:

Name (changed to protect identity)

Blacklist Tag

Actual incident(s)

Mohammed Imran

Narcotic

Bought tranquilizers to manage anxiety / stress without a doctor’s prescription from a local pharmacy

Chruen Cassidy

Terrorist

Profusely sweating at an airport due to stress and physical exhaustion

Disha Saxena

Lazy & Quarrelsome

Altercation with local community members on the issue of hygiene and cleanliness

T. Bala

Politically Exposed Person

Tweeting in support of his home government over a national issue while working overseas

Navneet Singh

Social misfit

Unable to communicate effectively in English in spite being a good software developer

Alex Mayor

Fraudster

Defaulter for personal credit card payment of a miniscule amount

Akash Jain

Anarchist

Online search for terms like “crude bomb”, “anarchy”, etc. to gather general information in order to write a fiction novel

One can easily see from the above table that such data can be unverified, biased, outdated, or irrelevant. How names of simple & unsuspecting individuals make it to such kind of databases will be largely unknown, unless thoroughly investigated. 

Is it just a complex algorithm or a mean person behind it will remain a mystery until the shadow of the “BLACKGHOST” is exorcized!

So, if you meet with ghosting repeatedly, you can be sure that your name has been blacklisted. You need to prep-up your act and perform your own due diligence before it destroys your peace of mind.

Contact the author to know more about identity management, online reputation management and OSINT.

References:

https://mikesouth.com/free-speech/the-internet-blacklist-database-72337/

https://www.refinitiv.com/en/products/world-check-kyc-screening

https://www.mirror.co.uk/money/revealed-secret-international-blacklist-can-7332879

https://www.theguardian.com/uk/2009/mar/16/blacklisted-workers-hotline

https://insights.dice.com/2019/03/12/exploring-secret-practices-tech-recruiters/

https://forums.studentdoctor.net/threads/pharmacist-blacklisted-on-global-database-esteem.1370449/

https://www.bindmans.com/insight/blog/world-check-database-due-diligence-or-blacklist

https://www.zdnet.com/article/inside-the-global-terrorism-blacklist-secretly-shadowing-millions-of-suspects/

https://www.zdnet.com/article/skynet-nsa-terrorist-terminator/ 


Thursday, May 12, 2022

CONSUMERISM KILLS...EVENTUALLY!

(Life Coaching Series)

Last week, I was doing some quick errands to buy some pending grocery and sweets to cross my home-shopping checklist. I just happened to be on my toes for hours with constant updates over my mobile which included targeted ads across various apps and services that I regularly use. Let me tell you that I prefer walking out to buy my grocery rather than order it online, even in the post-covid era. Throughout my shopping spree, I was bombarded with “relevant” ads, some of which are listed below along with my take on them:    

 


For starters, water is made potable by several methods that include filtration, distillation, reverse osmosis, ultraviolet radiation, etc. Each of these processes along with cleaning the water depletes the mineral content in it. Consumption of such water form bonds with the minerals inside our body and is passed out through urine and sweat; thereby depleting our mineral intake. Firstly, they deplete the minerals from water to make it potable and then they add minerals to make it healthy. I would rather drink directly from a natural and clean pond than falling for this gimmick.


In the last decade, it has become the norm in our nation to gift chocolates on auspicious occasions and festivals. Thanks to this excellent ad that has carefully and consciously manipulated our thought process. We are a nation that celebrates at least three festivals per month (refer any Hindu Panchang i.e. Ephemeris) where each festival has an associated culinary diet that is most suited to the season and region. For example, “thandai” (natural home-made cold drink that cools the body) at Holi (around March / April) which is the onset of summer or “tilgud” (natural home-made sweet rich in oil content) at Makar Sankranti (around mid of January) during autumn. Why do we need to replace such a rich and healthy tradition with fermented and preservative infused food?


As far as I know, cold-pressed oil (still available in rural India) poses the least risk to our health since it is free of man-made chemicals and good cholesterol is preserved. In the modern refinery, filtration of oil takes place in the presence of CMR (Carcinogenic-Mutagenic-Reprotoxic) substances. No matter, what the brands might claim the end product is certainly a risky proposition. Any given day, I would bet on unrefined / unfiltered cold-pressed oil to keep my heart beating normally.  


With the advent of shopping malls and supermarkets, we have unwittingly started consuming processed vegetables instead of fresh vegetables. Most of us are unaware that the preservatives, artificial colors and artificial flavoring used for processed food often contain CMR substances and are never listed on the label. Is it just our ignorance or is it our fast-paced lifestyle that makes us too lazy to work with fresh vegetables?

Each of these ads are an example of brilliant consumerism and are probably used as case studies at B-schools. But the moot point is – where do we draw the line? This kind of consumerism is like a slow poison that kills both the consumer and the society in a gradual manner.

I’m neither a nutritionist or a medical doctor; but as a systems / process auditor I have had the opportunity to audit entire food chains across India & Africa. What I am presenting here is out of direct experience from years of observation, both as an auditor and a consumer. Just like you, I’m a consumer first and an auditor later. So, it does concern me when I find that I’m unaware of what goes inside my body willingly.

Remember that each time you eat, you are either fighting disease or feeding it!

Follow this simple formula to stay fit – OPPRESS:


Oil – Reduce your intake of oil and fried food

Processed – Avoid anything that is labelled as “processed” since it is mostly less natural than you think

Packaged – Avoid anything that is labelled as “packaged” since it is mostly less natural than you think

Refined – Avoid anything that is labelled as “refined” since it is mostly less natural than you think

Excess – Avoid any type of overindulgence including food for thought viz. digital exposure  

Sugar – Reduce the intake of sugar and sugar-based foods

Salt – Reduce consumption of salt and salt-based foods

This way you can OPPRESS any disease with ease and stay fit for a longer period. And, don’t take my advice with a pinch of salt – Just try it out and you will feel the difference!

Thursday, September 2, 2021

Von Westendorp Approach Using Python

 

Von Westendorp Approach Using Python

(Artificial Intelligence Series)


Strategic pricing is a critical process of Product Management, when it comes to launching a new product. There are many methods to pricing your product and one of the most popular ones is the Von Westendorp approach. The beauty of this approach is that it provides a glimpse in the form of a “Price Sensitivity Meter”. Once the graph is plot, we get the following price points at the intersections:

a.       OPP (Optimal Price Point) – The ideal price where the consumer is most willing to pay.

b.      IPP (Indifference Price Point) – The price where the consumer is least willing to pay.

c.       PMC (Point of Marginal Cheapness) – The price beyond which the consumer will consider the product to be too cheap and might not consider buying.

d.      PME (Point of Marginal Expensiveness) – The price beyond which the consumer will consider the product to be too expensive and might not consider buying.

From the above four price points, we get the RAI (Range of Acceptable Index); which can be used to price our product. All said and done, let’s get our hands dirty now!

A survey is conducted to assess the likely price points with questions like:

·         At what price would you consider the product to be too expensive and out of reach? (Too Expensive)

·         At what price would you consider the product to be expensive but still worth buying? (Fleecing)

·         At what price would you consider the product to be a cheap and worth buying? (Bargain)

·         At what price would you consider the product to be too cheap that quality would be doubtful? (Too Cheap)

All the responses are collected and the dataset is arranged in the following manner:


Please note that the first two columns are sorted in descending order while the last two are sorted in the ascending manner. Using this dataset, one can plot the Von Westendorp graph in excel itself. While this might seem quite easy and does not require any other dependencies like a Python IDE; I personally detest doing it in excel. I will explain the reasons at the end of this article.

I’ve used Miniconda CLI, Jupyter notebook and .csv data format for this project. You may choose other IDE and tools that you are comfortable with like Spyder, NoSQL, etc.

Launch a fresh notebook and import the necessary libraries. Now, load the data and check the shape as shown below:


Next step is to remove the intransitive price preferences* and compute the cumulative frequencies, as shown below:


Once the above is done, we need to define a table where all the array values can be tabulated.

 

Now, we need to compute the results and get the values, as shown below:


The last step is to plot the graph:





The output graph will look like this:


So, that’s it, pretty simple, isn’t it? Well, no. It wasn’t that easy when I did it for the first time. Let me share my learnings with you. Prior to plotting it in Python, I did it with excel. I’m presenting a comparison table of the values that I got:

One can easily note that the values arrived at via Python are higher than those from excel. The reason being the following:

·         In Excel, it will accept all price points from the dataset as it is, in order to plot the graph while in Python, I have the freedom to “remove intransitive price preferences*”. If I had skipped this step, values from Excel would match those from Python.

·         It is imperative to remove the intransitive price preferences as not doing so would present a skewed graph, as well as, generate incorrect values.

·         As a result, my data shape dropped to 16 from 39; meaning entire 23 rows were invalidated.

The obvious question that would arise in the minds of data analysts and machine learning enthusiasts is – Why not scale or normalize the dataset?

The answer is plain simple here – applying normalization to the dataset would replace the suspect values (intransitive, duplicate, etc.) with the average or mean. Since, this is akin to “changing the respondent answers”, it would amount to gross manipulation of data and render the purpose of survey useless.

Thus, the key takeaways from this exercise are:

1.       Statistical inferences are better accomplished with Python than with Excel

2.       Respondents are prone to error and one might need to drop off the incorrect answers

3.       Adequate sample size is a must to ensure that there are enough data points to suffice for the inference

4.       Scaling or normalization is not a ‘one size fits all’ solution and must be applied with sufficient caution

5.       Intent needs to be preserved even if it is at the cost of the content

Note: *intransitive price preferences – the price points that are not linear but are concurrent. This can happen where a respondent might choose the same price point for more than one question. For e.g. Rs. 8000 selected as ‘bargain value’ as well as ‘too cheap value’.

P.S. You can contact the author to know more about this article. The sample python code is available at https://github.com/southpau79/humintonline .

For those lazy to read & have scrolled to find the end of page, here's the video:



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