Capturing the relevant metrics and utilising them to make business decisions, has always been tricky. As business environments change, the question of metrics gets all the more complex.
In this webinar hosted by Aritha, Padma Satyamurthy — transformation leader at Walmart Labs India, discussed about the metrics conundrum faced by enterprises of various sizes. Based on her experience in working with various organisations, Padma set the context clear at the beginning of the webinar, by stating that she is not going to talk about what metrics to use, the formula, or the sources to capture the metrics. The focus of discussion was regarding the challenges one would encounter when going about evolving the suitable metrics with a whole enterprise picture in mind.
Image analytics attempts to replicate the possibilities of human eyes with the computer. It’s application could be as simple as an OCR or as complex as analysing micro-seismic images which helps us predict natural disasters like earthquakes. In this webinar, a use case of developing an AI application used for extracting key fields from scanned images was explained.
Pruthvi drew from his personal experience of working with a large organisation where the document scanning and update was happening manually (keying data into excel and updating database) for millions of records. That is when the data science team was consulted for building a homegrown AI based application for automating the process. Text extraction was achieved using the open source library “pytesseract” in this project. Text Extraction Pipeline with text detection done using Deep learning technique was explained in detail. The text extraction pipeline contains 5 steps:
In this use case, the detection accuracy was 90 – 95% as deep learning technique was used. There are expensive tools to achieve extraction, like the Amazon’s “textract” tool, for more accurate results and more complex requirements like extracting handwritten text.
Three distinct advantages of implementing such a solution are:
Pruthvi walked the audience through various other tools available for OCR like the OCROpus, Ocurlar and SwiftOCR apart fromTesseract. He concluded the talk by listing some of the limitations of using Tesseract. The session was lively with participating audience.
Some interesting questions answered during the session were:
Padma discussed these top challenges in arriving at metrics for software teams, programs, portfolio and business:
Popularly used in analysing Baseball game performances; Padma cited how Sabermetrics evolved after closely watching the correlation of actions and outcome, followed by customization to suit the current set of goals. A recommended watch is Hollywood movie, Moneyball, that showcases how Sabermetrics was put to good use, which holds a lesson or two for the software enterprises.
As per the results of the poll during the webinar, 60% of the organisations are capturing and publishing metrics even at the business level. Which is a good number, considering that a constant watch at the performance of the overall business is very important. Padma emphasised on the importance of choosing right metrics set and the also the importance of perspective while looking at the metrics.
Padma ended the webinar by sharing this simplistic approach that has worked for her:
Start from where you are >> Focus on the Goal >> Evolve and Grow
Some of the questions that the audience asked during the webinar are captured below. If you have similar questions in mind, please watch the recording of the webinar to know the answers provided.
Goals can be long or short term. How to fix metrics in such a case?
How to handle if the top leaders aren’t interested in any metrics?
Should metrics be linked to OKRs?
In a transformation program when an organisation is new to agile ways of working how soon metrics can be introduced?
Should metrics be changed frequently?
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