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Archive for the ‘Invoices’ Category

Quick tip: Syncing a part of your email to your timesheet

In Automation, Invoices on December 2, 2017 at 9:31 am

It is that time of the month.  Time-sheets are due every week/2 weeks/ or maybe once a month.  However the routine involves entering the number of hours, along with details of your work everyday.

As your daily routine should go, an email for a daily status is always sent.  This contains details of you work.  Scraping only these emails (at the end of your time-sheet period) and filling your time-sheet with it could avoid manual entry and a lot of last minute rush.

Syncing of only the daily status emails can be done. However the security concerns are understandable as most time-sheet applications are 3rd party apps.  So automatically backing them up and then scraping their content and syncing them to the time-sheet server or scraping and pasting them on the server could be a worthwhile effort.

Point: Write once (your daily status) copy it as many times.

Knowledge of Python or shell scripting could be very helpful.

 

 

 

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Quick Tip: Anomaly Detection to build trust with Customers

In Automation, Bills, Invoices, Machine Learning on November 21, 2016 at 4:05 pm

In a recent incident, one of my friends took his old vehicle for servicing.  Among other things, a small bulb was replaced and the bill for just that part was a whopping Rs 300/-.  The explanation given to him was that the bulb costs Rs.150/- and the labor was Rs. 150/-. Whereas the same would cost nearly half the price a few months ago. Courtesy a history of maintaining invoices, he was able to question the prices.

He was also at the receiving end for some of his other bills, when he saw some extra charges which were never charged in his earlier bills (which he had maintained).  It was later found out, that these were some “errors”.   I wonder how many people would really do all this.

For people who do not store so many bills/invoices and keep track of unusual deviations in them.  They could be ripped off.

Solution: In these days of digital records (including bills and invoices), a machine learning algorithm called Anomaly Detection could help.  A company could basically spot the outliers or anomalies and strive to eliminate them thereby building trust with their customers.  For the customers, they could benefit if certain flags are reported in their bills whenever a large variation in prices is seen in their invoices for many billing products.

Some bills, payslips etc, could contain breakups of various categories, and any missing category or additional categories can also be flagged.

All in all, a win win for both Customers and Businesses

 

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