Impact of WFH on Bangalore

The pandemic has changed our lives and this post explores the effect of the pandemic on cities in general and Bangalore in particular.

Impact of WFH on productivity

The Covid-19 pandemic has forced numerous business establishments to shut down their offices and request their employees to work from home. Anecdotal evidence indicates that most companies especially in the service sector and in back office functions are adapting well to this change without any major adverse impact on productivity.

Impact On Commercial Real Estate
Many companies are also having a hard look at their office space requirements with some even planning to do away with offices entirely. As more and more companies go down this path we will see increasing pressure on commercial spaces which will see much lower utilisation. At an extreme case some of these office spaces may just have to shut shop due to lower occupancy.
Impact on residential real estate
Apart from commercial real estate, residential real estate will also be at threat. If employees don’t need to go to work then theoretically they need not work out of the cities where their previous offices were based in. Instead they could return back to their hometowns and choose to work from there provided they have adequate infrastructure to work from home. This in turn implies rental yields could be under pressure and demand for own housing can also be at risk. Please note this will play out only if companies move to a 100% model. However if companies even insist on one or two days work from office then this thesis will break down.

Impact on Ride Providers
Outside of real estate, the next big sector that will be impacted will be vehicle hailing apps like Uber, Ola, Bounce to name a few. Even a one day work from home will mean a substantial drop of volumes which will impact the ability to scale.

Impact on restaurants / food delivery
Restaurants in erstwhile office areas will also be impacted as customers who used to frequent daily will now only visit them when they need to come to office. Instead delivery apps may be more in favour especially in double income households where both partners will not have time to cook during working days.

Impact on State Finances and Infrastructure
The fall in real estate prices will hit city and state finances and will impact the ability of the city authorities to invest in infrastructure. However on the positive side expenditure will also come down as the city shrinks and uses less of public transport and commute infrastructure.

Shift from offline to online and its impact on real estate
Customers will also increasingly prefer online channels over offline channels and hence we could see downward pressure of physical retailers which in turn will impact commercial real estate.

Impact on pollution and water resources
One positive impact will be the fact that pollution levels will go down as most Bangaloreans will travel less frequently to work. Considering that water consumption and electricity consumptions is lower, the city will also turn more environment friendly. Since water consumption is lower we may less frequent complaints of lack of water access.

Impact on family bonding

On the personal front employees will enjoy the time saved on daily commute and utilise it to either improve productivity or utilise it to spends more quality time with their loved ones.

Conclusion
In summary the pandemic has made us relook our ability to work permanently from home and therefore could impact some areas such as real estate and services that revolve around commercial real estate. The longer the pandemic stays the higher are the chances of disrupting our pre Covid routines.

Performance Appraisals – Normal Curve on its way out….

When I first started working, performance appraisals were closely linked with the term “normalization”. What we were told was that it was not just your absolute performance that mattered, what also mattered was relative performance vis a vis peers in the organization. You not only had to be good at your job, you also had to be better than others. To take an examination analogy, normalization is like the percentile system MBA Entrance exams in India follow as opposed to the absolute grading that say a GMAT exam follows. The idea behind normalization was that by force ranking peers and rewarding the best and in some cases penalizing / letting go of the ones at the bottom we would be rewarding our best talent and also improving the “average” performance levels in the organization. While in theory it seems logical, the implementation of normal curve brings in problems at a practical level:

It forces team players to compete with each other: The normal curve works well if all the team members are independently working on their tasks with no dependency on each other. However if the work is of collaborative nature, this causes a problem. To ensure that the team does its task, it is imperative for team members to teach and learn from each other – however in an environment where the sword of normalization hangs over all team members, there will be a tendency for team members to claim credit at the expense of others which in turn brings down trust in the team. Once trust falls, collaboration suffers which in turn impacts team performance which in turn leads to a blame game where every body starts blaming others for the problem which in turn leads to a further deterioration in trust and collaboration. Basically downward spiral ad infinitum.
Different skill sets may be lumped together: Normalization requires a cohort of 30 individuals. Many times smaller teams are merged into larger teams to achieve this 30 number and then a normalization is applied on this agglomeration of sub groups. The outcome in this case is never satisfactory.
Talent Levels Fall and Talent Risk Rises: Because its a “winner takes all” world, individuals generally ranked in the level right below the top performers will seek out other opportunities. When this happens the pressure for taking up the workload goes to the higher performers as replacements need time to be hired and come up to the level required. This in turn increases the load on the top performers which could lead to burnout. Alternatively it could make the company more dependent on the top performers and impact them negatively if they were to leave. The logic behind normalizing is to ensure that the top 20% can take care of 80% of outcomes – but this also implies putting most of your eggs in too few baskets.

Thankfully many companies are realizing the pitfalls of the model and are moving to a model where employees are measured on absolute levels and not on a relative basis. Reviews are also being done more frequently allowing employees and organisations to do appropriate course corrections. While this does certainly solve some of the problems associated with normalization, it also requires a rigorous goal setting exercise linked to the organizational goals. If the goal setting process is too dependent on the dynamics between the manager and the reportee then there is a chance that the goals may not be aligned with the organization and one may penalize / reward employees disproportionately. Another risk is that managers may be tempted to rate all employees as the same level knowing very well that this will probably minimize heartburn levels in the team. This in turn will lead to genuine high performers leaving for better opportunities. The organization also needs to have a clear view on the competencies required for each job, with clear and comprehensive learning and development paths that the employees can undertake to ensure that they can fulfill current job roles satisfactorily. In addition to this companies will also have to ensure that they have a robust career path for their employees along with an ecosystem that can help employees grow into roles of higher / different responsibilities.

If organizations get this right then we could see more happier workplaces that foster collaboration which will result in happier customers and wealthier shareholders. I am optimistic that this will happen!

T20 All Time XI – By Numbers

This is the last of my posts inspired by Cricinfo’s idea of selecting the best team across formats from the years 1995 to 2017. Earlier posts can be found here: Selection By Stats – Test XI for last 25 years , Selection By Stats – Cricket ODI XI , Cricket – All Time T20 XI , Cricket ODI XI for the last 25 Years , Cricket Test XI For The Last 25 Years.

In this post the idea is to select the Best XI in terms of statistics. I have used batting average and strike rate to select batsmen and the keeper and the bowling economy rate and bowling average to select the bowlers. I have put in the all rounders in both categories. The ideal team balance is to have 4 batsmen, 1 keeper, 2 all rounders, 4 bowlers.

Graph 1: Batting Average and Batting Strike Rate

Batting

Virat Kohli with a batting average of 50 at a strike rate in excess of 135 makes him probably the best T20 batsman of all time.
Aaron Finch selects himself based on the average of 40+ and SR of 150+.
Amongst the keepers ( highlighted in orange ) – it’s a choice between McCullum and Dhoni – one more comfortable opening and the other a master of finishes.
Amongst the all rounders, Shane Watson’s batting prowess far exceeds the others.
Maxwell & Munro have the best strike rates amongst all the batsmen.
Kevin Peterson and Chris Gayle are other giants who stand apart from the rest with healthy averages and high strike rates in excess of 140.

Graph 2: Bowling Average and Economy Rate

Bowling

Generally the preference is more towards containment in this form and hence the economy rate probably takes precedence over the average.
Rashid Khan is by far the pre-eminent T20 bowler. His average is around 13 and he has an economy rate less than 6.
Daniel Vettori is the only other bowler apart from Rashid Khan with an economy rate less than 6.
There is not much to choose between Badree and Narine. A host of other spin bowlers such as Mendis, Swann, Ajmal and Dockrell have economy rates less than 6.5 and averages less than 18. This also indicates how dominant spin bowlers have been over their fast bowling compatriots.
Among the all rounders Shakib Al Hasan’s average is superior to other all rounders such as Afridi, Hafeez and Mathews who all have similar economy rates.
4 fast bowlers have similar economy rates – Steyn, Bukhari, Amir and Bumrah with the latter having a distinctly higher average.

The problem here is one of balance – spinners dominate the game and if you go strictly by the numbers one should just select 4 spinners. But that will make the bowling too predictable. All rounders are also a bit of a problem – none of them except ( Watson for batting ) can walk into the team on one skill only. Packing the team with all rounders adds options but comes at the cost of efficiency. The way I have chosen to resolve this is also to select atleast 2 bowlers with high batting strike rates – the rationale being they will mostly come at the end overs and try to maximize the score. Hence average does not matter as much as strike rate. Thankfully both Narine and Rashid Khan have strike rates in the range of 125 so this makes the selection problem easier! While I was tempted to choose Shakib as a bowling all rounder I decided to go with Vettori as i could not ignore the economy rate of 5.71! I am a fan of fast bowlers and find it tough to go into a team without two genuine fast bowlers – I settled on M Amir and Dale Steyn. Bukhari was another strong contender.Moving to the batting – since the team has Narine, I would use him as a pinch-hitting opener along with Aaron Finch. One down would be Virat Kohli followed by Kevin Peterson and Shane Watson. Maxwell and Munro are alike as per numbers and I have chosen only one of them – Maxwell. At # 7 I would have MSD playing in as Keeper. 8 would be Rashid Khan followed by the tail of Vettori, Steyn and Amir. 12th man would be Shakib Al Hasan. If Shakib plays then Watson would open and Shakib would come either after Pieterson or Maxwell.

To summarize final team: S Narine, A Finch, V Kohli, K Pieterson, S Watson, G Maxwell, M Dhoni, R Khan, D Vettori, D Steyn, M Amir. 12th Man: Shakib Al Hasan.

Selection By Stats – Test XI for last 25 years

I have been writing a series of posts inspired by Cricinfo’s idea of selecting a dream team across formats from players in the time span of 1995 – 2017. The posts are of two types:

Team selected basis my personal preference : See Cricket Test XI For The Last 25 Years , Cricket ODI XI for the last 25 Years , Cricket – All Time T20 XI
Team selected basis statistics : See Selection By Stats – Cricket ODI XI

This post falls in the second category and attempts to arrive at the ideal team based on statistics. The thing with test cricket is that conditions differ by country and not all players have the ability to adapt to conditions different from their home conditions. For the purpose of analysis, I have broken down the career averages further into country averages and selected players who demonstrate consistent performance across countries. The selections and their rationale are as follows:

Openers: Graeme Smith and Chris Gayle

Following table shows average of shortlisted openers across different countries. The cells are highlighted in red are cases where the average falls below 35. Graeme Smith is the only opener who has an average of 35+ across all countries with just about making the cut in India and Australia. The second best seems to be Chris Gayle who apart from a bad record in India, averages 35 + every where. Sehwag has a dismal record in England, New Zealand and South Africa while having a pretty good record elsewhere. Alistair Cook surprisingly has a bad record in NZ and so do Warner and Hayden. New Zealand seems to be the toughest location for openers while all of them have great records against Australia and Pakistan.

Openers

2. Middle Order: Tendulkar, ABD, Kallis, Lara

Below table shows averages of shortlisted players by country. Averages below 35 have been highlighted in red.

Middle Order

This table pretty much establishes Sachin Tendulkar as the pre-eminent player of his generation. His lowest average is 44.66 against Pakistan and average 50+ in 6 of the countries. There are legions of fans who believe Rahul Dravid to be India’s best overseas batsman – however what is not so well known is that Dravid does not have that great a record in South Africa and Sri Lanka. Sachin on the other hand has a consistency that is unmatched. The only player who comes close to him is the South African maestro ABD who has a 40+ average across all countries. Jacques Kallis also has 35 + against all countries but makes the cut marginally in England and Sri Lanka. Brian Lara never played in India in the stated period – however considering his record in Sri Lanka, I am quite sure he would have been successful in India too. The ones who missed out narrowly are Steve Waugh ( bad average in Sri Lanka ), Sangakara and H Amla ( both bad records in West Indies ) and Ricky Ponting ( Bad Record In India ).

3. Wicket Keeper : Adam Gilchrist

On a dismissal per innings basis Adam Gilchrist is way superior to the other keepers – however one must also remember that this is also a function of the strength of the bowling line up. Gilchrist was keeping to some of the best bowling units in this time period – McGrath, Warne, Lee, Gillespie to name a few. Hence i have discounted keeping statistics and assumed all keepers to be of equal calibre behind the stumps. If I consider their batting then Gilchrist, inspite of a insipid record in india and Pakistan, is way ahead of the rest of the keepers and hence walks into the team:

4. Bowlers: Glenn McGrath, Dale Steyn, Shaun Pollock, S Warne, A Donald ( 12th Man )

I have considered bowling averages and lumped spinners and pacers together. The cut off for the bowling average is 30. Here are the results:

Bowler

Glenn McGrath’s record is awe inspiring and puts him streets ahead of any other bowler in the period. With the exception of Sri Lanka he averages less than 22 in every other country! Dale Steyn and Shaun Pollock’s averages go above 30 only in England and Australia respectively and are the next two entrants. There are 3 bowlers whose averages go above 30 in 2 countries – A Donald, S Warne and W Akram. Have chosen Shane Warne and Allan Donald as with this combination of 5 bowlers – I can always field 4 bowlers all with averages less than 30 in every country. Just going by pure numbers – I would put in 4 fast bowlers in India and West Indies.

A note about the other bowlers – while Kumble has been a match winner in India, his average in every other country is above 30. Similarly J Anderson’s averages dip in most countries outside England. Murali has a very good record in most countries – but struggled in Australia and India. Courtney Walsh surprisingly does not have a great record in Australia and both he and Ambrose lost out to the others owing to the fact that they did not play tests in a couple of nations. Dont be fooled by Waqar’s numbers – these are from 1995-2017, if we take the period prior to this his record is comparable to the best in the business. Fast bowlers surprisingly have a great record in the so called spin friendly tracks of the sub continent.

Overall the team has quite a bit of overlap with my earlier selection based on personal choices. While the openers are different, the middle order ( including the keeper ) is identical. I had a narrow preference of Ambrose over McGrath and Akram over Pollock. Warne and Steyn feature in both teams. In terms of geography mix this team is dominated by South Africans ( 5 ) followed by Australians ( 3 ), West Indians (2) and 1 Indian.

If I were to select the best XI to play against each country in that country excluding players from the host country ( for example, Sachin cannot play against India, McGrath not against Australia etc ) then the choices would be the following:

Australia: Sehwag, Cook, Sangakara, Tendulkar, Y Khan, Kallis, Stewart, Akram, Steyn, Donald, Ambrose
England: Cook, Smith, Chanderpaul, H Amla, Dravid, S Waugh, Gilchrist, Donald, Murali, McGrath, Walsh
India: Cook, Hayden, Amla, Jayawardene, Kallis, Chanderpaul, A Flower, Donald, Steyn, McGrath, Ambrose
NZ: Smith, Gayle, Dravid, Sangakara, Ponting, Kallis, Gilchrist, Akram, McGrath, Walsh, Murali
Pakistan: Sehwag, Hayden, Dravid, Ponting, ABD, Kallis, Dhoni, Warne, McGrath, J Anderson, Walsh
South Africa: Gayle, Warner, Tendulkar, Lara, Ponting,S Waugh, Gilchrist, Warne, Ambrose, McGrath, Walsh
Sri Lanka: Sehwag, Cook, Lara, Tendulkar, Ponting, Y Khan, Gilchrist, Warne, Akram, Steyn, McGrath
WI: Hayden, Cook, ABD, S Waugh, Dravid, Ponting, Gilchrist, Akram, Steyn, McGrath, Anderson.

This was quite a fun post to write and I hope you enjoyed reading it too!

Cricket – All Time T20 XI

As a part of its 25 year anniversary celebrations, Cricinfo is inviting readers to pick their dream teams across formats in the 25 year period from 1995 to 2017. The T-20 shortlist has 29 batsmen including 5 keepers, 9 all rounders and 20 bowlers.See full list of players here .Readers need to pick atleast 4 batmen including a keeper and 5 from the all-rounders and bowlers. Here’s my pick based on what I have observed and followed over the years:

Shane Watson (AR ), Sunil Narine ( Bowler ), Virat Kohli (Batsman), Kevin Pietersen ( Batsman ), AB De Villiers ( Batsman ), MS Dhoni ( WK ), Shakib Al Hasan (AR), D Bravo (AR ), Rashid Khan ( Bowler ), Dale Steyn ( Bowler ), Lasith Malinga ( Bowler )

The team is packed with all rounders and theoretically bats all the way down to #8 and has 7 bowling options with 3 spinners and 4 medium pacers. The batting opens with Sunil Narine and Shane Watson. Both have fantastic records at the top of the innings and in addition to this can also contribute with the ball. In fact Sunil Narine is one of the most economical bowlers around in the T20 format and Shane Watson is certainly not a bad choice as the 7th bowling option! The middle order consists of the RCB pair of Virat Kohile and ABD along with Kevin Pietersen. Together this is a supremely destructive middle order which on its day can dismantle the best of bowling attacks. They are followed by MS Dhoni one of the best finishers in the game. In addition they also have two all rounders in Shakib and Bravo who can contribute with the bat as well. In terms of bowlers, the team has a wide variety to choose from. Lasith Malinga & Dale Steyn form the lead fast bowlers. Malinga has one the most destructive yorkers in the game and many a times was virtually unplayable. Dale Steyn is widely regarded as one of the all time greats of the game and together both form a potent fast bowling unit. In addition to this Dwayne Bravo would play the role of the third seamer with Shane Watson as the 4 option. The spin bowling resources are equally impressive. Sunil Narine and Rashid Khan are some of the most economical bowlers in this format and also have the knack of taking wickets at regular intervals. They also have a third option in terms of Shakib Al Hasan who could walk into most teams as the front line spin bowler. The plethora of bowling options coupled with an intimidating batting line up makes this a team to be feared.

As mentioned earlier this choice is based on my personal choices – will draw up a XI based on statistics in a forthcoming post.