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I was managing organization wide restructuring program where goal was to map all resources with their delivery accounts to keep a track of account’s PnL and manage capability as cost centre. We also intended to design KRA and KPIs for each individual level to make our Performance Assessment data driven and transparent. This was a big change at employee level at professional and emotional level too. It meant changes in their reporting structures, extra reporting and performance management by all managers, clear KPIs alignment and selection.

Planning Level: We identified all the major business account heads, capability and other function head and organized a communication platform to make them aware and comfortable with the changes. We undertook their inputs on pros and cons and some caution to be exercised

Execution Level: We started executing these changes with L0 level employees and moved up to leadership team. Along the way we encountered some risks and outlier conditions to be managed.

Communication Strategy: We worked with all business and functional heads on our communication strategy to reach out to all the employees. Head multiple events and workshops to discuss the changes.

Data Platform changes: Evaluated all the data platform changes required and planned a phased out approach to bring those changes in the system as well.

However, when we were about to reach closure of this program, I realized that I have made a big mistake of readiness of our existing platforms to support all the changes required and existing data integrity. It really took a toll on everyone involved to clear up data accuracy before the changes could be introduced.

I think a product deployment starts with ideation.  I would crowdsource and get multiple inputs for product content to ensure the deliverable is valuable to our customers.  Then product development, which is tested iteratively by internal quality assurance and beta customers in a sandbox test environment.  Prior to deployment, I would again get feedback and iterate based on the beta customers experience.  During deployment, I would ensure that communications are delivered to customers and internal stakeholders, complete with documentation in multiple areas, including reference documents in knowledge base articles and customer forums.  During support, I would provide feedback on the most impactful areas of the product and those that generate the most time and energy to support.  This would result in product improvements and enhancements during the mature phase.  Once ready to sunset, I would develop a transition plan for our customers to the replacement product or service, mapping the old and new workflows and highlighting the changes that may be required to business processes with the new product.  Upon retirement, I would provide a complete lesson learned document to the new product service owners.

我会主动和组内的成员进行沟通，遇到风险或者问题及时上报，同时我也会考虑是否有我可以帮的上组内工作的方面

在我刚加入我们团队对产品移动端重构的过程中，我发现大家在移动端设备的调试上不够熟悉，团队选择使用的是chrome的模拟工具，但是在不同设备的兼容问题的解决上效率很低。发现了这个问题之后，我向组内的资深工程师咨询，掌握了我们的项目的构建和调试方案，通过提供fiddler，charles脚本和文档的形式，分享给整个组一套切实有效的移动端调试方案，提升了组内的mobile debug效率。之后，团队变得更信任我，在我做为新人的情况下，主动让我负责了更复杂的项目。

Assuming we are talking here about the experience of flight arrivals/departure from a specific airport.  Few key data points to be considered while designing this experience:

a. Weather of the specific area

b. Availability of runway to land or take-off

c. proper functioning of the communication devices between pilot and ATC

d. In air assistance to the pilots

e. Pilot to be able to smoothly report air/weather conditions back to a central system from where then it can be relayed to other flights passing through the same area.

While all other use cases are seem to be handled, e is the one where I feel there is a lot more that can be worked on referencing the SIA incident happened recently.

 Let's design a central system where pilots should be able to send real time weather climatic feeds. It could be a server with high computing capabilities as the data from this server will then need to be relayed to multiple other flights passing through the area. One can think of this server as a self sufficient system with all automation processes running inside it. The way it will work is:

a. Capture all the feeds from the flights in air

b. it should have access to data of all the flights of specific areas, ofcourse there will be mutiple such system deployed for load balancing, DR, security and other privacy reasons

c. All these servers should be able to communicate with each other as well

d. Any critical (Red/yellow) information to be relayed to the flights passing specific Area.

e. This should be a next-gen system which should pro-actively warns pilot/flight if any specific area has seen critical incident happening or likely hood of Air incidents when passing through the area.

f. The system should be able to help pilot navigate through turbulance if already caught like what height, speed and angle to Manov our the flight to come out of the turbulance.

g. Should be able to send SOS signals to the nearby airports/flights if the system has identified that the flight will need emergency landing assistance.

Designing such system will require extensive Infrastructure as well as thorough testing and should be piloted first with small amount of flights in the region with less air traffic and then a slow roll out per region should be an ideal way with catching and fixing bugs along the way.

Success Metrics:

North star: Accurate predictions

Number of times it relayed critical weather alert to the pilot also capturing false positives

Number of times it triggered SOS, capturing false positives

How many airports have adopted this

With scale are we seeing drop in accuracy

How many flights a single server can successfully monitor

Time it takes to process information and then send it back to pilots

Availability of the system itself

Pricing:

Given the monster system to be designed, this is likely to be pricier as the infrastructure it will need and software that need to scale with flights, people travelling across the board etc. At a very high estimate a single server may cost from 100K to 300K

I was working on a large scale program that had integration points with Lab and external 3rd party team . We were following a strict timelines and had intially aligned on end to end delivery and various cross coordination effort . since we were dealing with major cross coordination feed files for further processing from 3rd party team we had highlighted the risk to the leadership team but didn't receive a strong follow up on the risk and commitment from the 3rd party organization on the delivery date . This caused us to miss the go live date had to delay . However going forward we had frequent checkpoint calls and also as a backup for testing effort we build mockster and service virutalisation for testing effort so that we can mock the service behavior of the feeds and data that we were supposed to receive from 3rd party team and moved ahead in our schedule .Therefore for all major delivery and critical delivery of the product we assumed variability and defined on the process of backup scenario in case we encounter Andy hurdles / risk