Earlier this year as meetings moved online, I found myself drowning into them, unable to get any real work done. As I looked around for a tool to audit my calendar to figure out patterns of how my time was being spent, couldn't find any great option out there!
So, I did some data science [1] on calendar and discovered 3 primary dimensions which cause meetings to be draining and ineffective:
1. Wrong people in meetings
2. Agenda not well defined
3. Schedule not optimized for individuals
I was able to leverage these insights and cut down my weekly meetings into half!
Hence, decided to build a service so people in similar situation can seamlessly do the same.
I'd love to have you try and hear what could be built on top of the analytics to create more value for you?
I had extremely negative experience with HR from Skyscanner.
After getting the process started from mailing on the mentioned email address, it took 3 reschedules to get 1st call setup because of random reasons.
And, after first call and initial writeup submission, I haven't heard back from HR after month either way.
Considering such unprofessional handling, I'd recommend against them.
I am Sitesh, looking for exciting opportunities (Preferably around Blockchain, Artificial Intelligence, Augmented Reality). Previously have been a Software Engineer, Quant in High Frequency Trading and Founder of two startups over last 4 years since graduating with Computer Science.
I agree with the influence part. Although, Given tracking of users by Facebook, Twitter (Clicked items, Time spent, browsing & sharing patterns) & Google (Chrome history, Android), I doubt people should act surprised to find such even in current state.
And, given most of the content is curated based on people we follow in our social media feeds, I wonder if it will encourage individual contributors to work on their unique content and help in capturing majority share of a focussed set of readers value rather than being a part of narrative.
I agree with the long held role of newspapers in aggregating a set of articles based on their criteria.
But in the current age, bundling seems to be broken for 2 particular reasons:
- Most people discover content via their social networks (Twitter, Facebook, Reddit etc) where they have invested a long time to curate a set of individual journalists, public figures and acquaintances rather than orgs.
- Diversity of audience expects a rather focussed content curation from different view points rather than all encompassing single identity.
This makes me believe that going forward in future, people should be able to show appraisal to unique pieces rather than a wrapper organisation, based on their quality. This might be encourage grass root level curation by people who are incentivised for their effort rather than association with an existing brand.
Glad to announce Powow in Public Beta. We have been working on this for past 1.5 months and looking forward to what you guys think of it!
Powow is Android / iOS application that helps everyone to discover, share and connect with people, places and activities in their vicinity in natural way of conversations. We intend to make it a decentralised, implicit, geo-located communication channel for localities.
Why Powow?
Ever since starting college, we have been moving between cities, states or, even countries. But, till this date, moving is way too hard. Every time you decide to move, you have to prepare for days and weeks worth of browsing online communities like Meetups, Facebook groups etal to find interesting groups and people. Yet, there is no way to communicate with entire existing physical communities around us all the time. Powow intends to do just that. As you move, you become part of the existing society around you. No need to create and join a gazillion groups in different locations.
Don't have a mockup on paper yet. But, It will have minimal presence in Browser and, notifies the user subtly whenever the top recommendation changes.
That is exactly the case that misses out with current sharing platforms available.
So often, when talking to a person, I come across tangential topics / ideas, which would never have thought of looking up otherwise.
Same thing when you notice something on accidently snooping on a random persons' screen and notice something completely whack that you start digging in right away.
Such instances make me believe that there is scope for properly showcasing all this data being generated in a usable way.
I agree that getting all this browsing data from users will rather decrease the signal-to-noise ratio early on.
But, that simultaneously provides a way to explore much more content on web that remains simply unknown to most people because of a lack of discovery medium. From personal experience, Most people share a mere fraction of stuff they discover online. So, even though that might find some rare gem on web, they will share only items which they would be rather associated with in contrast variety of things they might be interested in.
Although, I haven't ironed out exact details, IIRC, Deep learning techniques have improved significantly to make sense out of data if fed a huge chunk of it. Basic Video and Image comprehension techniques are pretty advanced too. I'd like to believe that this system will evolve to serve the purpose too.
Earlier this year as meetings moved online, I found myself drowning into them, unable to get any real work done. As I looked around for a tool to audit my calendar to figure out patterns of how my time was being spent, couldn't find any great option out there!
So, I did some data science [1] on calendar and discovered 3 primary dimensions which cause meetings to be draining and ineffective:
1. Wrong people in meetings 2. Agenda not well defined 3. Schedule not optimized for individuals
I was able to leverage these insights and cut down my weekly meetings into half! Hence, decided to build a service so people in similar situation can seamlessly do the same.
I'd love to have you try and hear what could be built on top of the analytics to create more value for you?
[1] [Github link to analytics](https://github.com/sitz/calendar-analytics)