CES 2017 – Random Thoughts On Future of APIs In An AI world

I spent half this week at CES 2017 in Las Vegas !


To say the least, it puts the “enterprise” side shows to shame in number of people it attracts, variety of solutions it offers and how boldly the future is thought about. It did not take any time to see that the future is all about AI – and how expansive the definition of AI has become.

There were bots of all flavors there – but voice was the major interaction media, and it was hard to walk the floor without hearing “hey Alexa” type conversations . Also noticed a lot of VR and AR. I walked away thinking voice will rule the consumer world for a while, and between VR and AR – I will bet on AR having more widespread use. While VR based video games are indeed cool – putting on something on your head to use technology makes me wonder how many will actually use it. Like 3D televisions – where you need special glasses, and hardly anyone uses it that I know.

The generation of products using AI that I saw (admittedly I only saw a small fraction of the HUGE show) barely scratched the surface of what is possible. If I think of what I saw with my engineering hat on , it is something like this

  1. Human voice or text waking up the AI service ( “hey Jane” )
  2. A natural language based request ( “When is my next meeting” )
  3. Voice to text translation as needed
  4. Intent and entity extraction ( me, my calendar, current time, read entry)
  5. Passing it to a structured API ( calendar.read ) and get a response
  6. Convert output to a string ( “your next meeting is in 2 hours with Joe” )
  7. Text to voice translation
  8. Keep the context for next question ( “is there a bridge number or should I call Joe’s cell?” )

This is easy stuff in general – there are plenty of APIs that do stuff, and many are RESTful. You can pass parameters and make them do stuff – like read calendar, switch a light on , or pay off a credit card. If you are a developer – all you need is imagination to make cool stuff happen. How fun is that !

Well – there are also some issues to take care of. Here are 5 things that I could think of in the 1 hour in the middle seat (also in the last row, next to the toilet) from Vegas back home.

Like say security – you might not want guests to voice control all devices in your house for example (which might not be the worst they can do, but you know…). Most of the gadgets I saw had very limited security features . It was also not clear in many cases on what happens to data security and privacy. A consistent privacy/security layer becomes all the more important in the AI driven world for all APIs. 

Then there is Natural language itself. NLP itself will get commoditized very quickly. Entity and intent extraction are not exactly trivial – but its largely a solvable problem and will continue to get better. The trouble is – APIs don’t take natural language as input – we still need to pass unstructured>structured>unstructured back and forth to make this work. That is not just elegant – and it is not efficient even when compute becomes negligibly cheap. Not sure how quickly it will happen, but I am betting on commonly used API’s should all have two ways of functioning in future – an NLP input for human interaction, and a binary input for machine to machine interaction (to avoid any needs to translate when two machines talk to each other) . Perhaps this might even be how the elusive API standardization will finally happen 🙂

If all – or most – APIs have an easy NLP interface, it also becomes easy to interoperate. For example – if I scream “I am hungry” to my fridge, it should be able to find all the APIs behind the scenes and give me some options and place an order and pay for it. And my car or microwave should be able to do the same as well and I should not have to hand code every possible combination . In future APIs should be able to use each other as needed and my entry point should not matter as much in getting the result I need. 

Human assistants get better with time. If an executive always flies by American Air, when she tells her assistant to book a flight, the assistant does not ask every time back “which airline do you prefer” or “should I book a car service also to take you to the meeting when you land”. The virtual assistants – or pretty much any conversational widget – I saw this week had any significant “learning” capability that was demonstrated. While I might enjoy having a smart device today since it is a big improvement from my normal devices – I will absolutely tire of it if it does not get smarter over time. My fridge should not just be able to order milk – it should learn from all the other smart fridges and take cues from other data like weather . In future, “learning” should be a standard functionality for all APIs – ideally unsupervised. 

The general trend I saw at CES was about “ordering” a machine to do something. No doubt that is cool. What I did not see – and where I think AI could really help – is in machines “servicing” humans and other machines. For example –  lets say I scream “I am hungry” to my fridge. The fridge has some food in it that I like and all I need is to put it in the oven. So fridge tells the oven to start pre-heating – and gets no response in return ! Telling me “the oven is dead” is a good start – But the intelligent fridge should be able to place a service order for the oven, as well as offer me an option to order a pizza to keep me alive for now. APIs should be able to diagnose ( and ideally self heal ) themselves and other APIs in future – as well as change orchestration when a standard workflow is disrupted. 



Future of Project Management 

Next to programming , Project management is the role that gave me the most satisfaction in my career. So after Rethinking IOT and AI for future , and Future Of Technology Consulting – I spent some time organizing my thoughts on where project management is today and where it is headed .

This picture is an old one – where I was leading a consulting team as the PM at my client, and we were codeveloping a product with SAP. There was no way to distinguish who worked for which company in this team. It was a highly stressful time – but also the most fun and productive time of my life 


In general I think project management as a profession has lost its stature and for all the wrong reasons . I also think that it will regain its lost glory, and then some, starting almost immediately !

Utterly stupid is how I would describe the move to commoditize project management over the last few years . The PC version would be penny smart, pound foolish !

Several factors played a part – and I think the wrong use of PMP certification is one big reason.  I am personally not a big fan of certifications in general. I (and others) have successfully managed hundreds of millions of dollars worth of projects successfully without a PMP a . When I was a full time PM (also when i was a developer) , none of my clients ever asked me if I was certified . In my view PMP and tech certifications are a definite plus for the job – but should not be a mandatory requirement .

PMP gives a false sense of security and accelerates the path to “if everyone has a PMP , they must be roughly equal in skills – so let’s choose the cheapest one for the job” . When I convinced my old boss many years ago that I don’t need a PMP – my defense was that we commonly knew at least ten people in their early twenties – who have never even been a team lead – pass PMP exam with flying colors, and neither one of us were confident enough to let them run a team !

To be perfectly clear : PMP itself is not to blame . I have studied the “body of knowledge”  closely and it’s pretty good . I encourage all PMs and aspiring PMs to study it . I am just strongly opposed to treating it as a way to falsely equate everyone who has it to be of same project management ability .

Becoming a PM is best done in an apprenticeship model . Project plan , documentation , chasing down tasks etc are good things, and you can learn it from books – but successful projects are mostly about making people successful  , not tasks successfully completed ! There is a big difference and a full appreciation of that only comes from watching and learning from folks who do it consistently well . However smart you are – you can’t learn it by studying a book or taking a multiple choice exam .

Sadly – and probably due to the mandate to commoditize all parts of IT projects  , task management – which was a means to an end in the past – seems to have become all of project management today !

Consistency and repeatability and scalability are all good for efficiency . So dumbing down of some project management aspects have that aspect going for it . But what is missed out today is effectiveness – efficiency without effectiveness leads to failed projects . And effectiveness is all about people !

People have only so much intellectual and emotional capacity and not all of it is spent on work . Example – the best programmer in my team in Bangalore spent 4 hours every day on commute . Even then he was twice as good as the next programmer . I let him work Mondays and Fridays from home and he became three times as good at what he did . I knew that issue because I went to Bangalore and lived there for a month to see the team and work with them and become one of them . I couldn’t get the same result by asking him to document more or sit in more status calls . I also remember a situation where we had an unreasonable client who made constant demands of our time to meet time lines that were not realistic . After two weekends back to back at work – my team had no energy left . My solution was to stop working weekends and instead we all went out bowling for a whole day on Monday and followed by a potluck on Tuesday . Even the client could not believe we hit the deadline with room to spare !

Motivating and getting the best out of your team is one aspect – equally important is making your client successful . By that I don’t mean the client company – I mean the human beings from the client team who work with you and sponsor the project . This means you need to get to know them , what makes them tick and what success means to them. No certification teaches you empathy !

To make clients successful – you need to know their business and their industry cold , or know others whom you can tap into for that knowledge . You also need the ability to make short term vs long term trade offs .  I once had a finance director of a company as my client – and she was stressed out that there wasn’t enough time left to build 150 reports that were scoped for the project . I worked with her and told her similar projects in past only needed 50 or so reports for similar functionality and the two of us spent a day looking through the specs and quickly brought it down to 40 reports . My employer had a short term revenue loss because of reduction in scope – but this lady was publicly recognized by the CFO of the company for getting the project done on time and under budget . And she got a larger portfolio and I got a lot more business from her , which in turn helped my own career progression .

Project managers need the respect of their team to succeed. PMs who manage a project where they don’t know any aspect of what is being done generally find it harder to get the team’s respect. It can be done – but it is an uphill task and you need superior skills and patience. This is another reason why commoditizing PM skills is a terrible idea – people who grew into PM after being developers, consultants, team leads etc can empathize and add quality to their team’s work much better than someone who can only manage tasks.

Why do I think this will change quickly, and for the better ? Its because the complexity of projects and client expectations have both risen to a level where commodity skills and elementary automation cannot keep up. Fear of failure is very high today thanks to a lot of failed projects in past – and at the speed at which technology is progressing, there are very few “apples to apples” references to say “this will work”. Good solid project management is the need of the day to help realize the value of technology innovation happening around us. I think employers and clients are both ready – or very close to being ready – in treating PM again as a critical role in making projects successful .

Those of you who manage development teams as PMs might enjoy this post this post I wrote in 2010 🙂

PS : Might as well add a shameless plug – If you have experience as a PM in big data, analytics, IOT etc – I am hiring in North America. Ping me !


Future Of Technology Consulting

Its the last week of the year – and that gives me the luxury of time to spend thinking of some big picture topics. Last week I was Rethinking IOT and AI for future . And that led me to think of my own profession of technology consulting in future. Especially important to me since my 11 year old daughter wants to be in this profession when she grows up . She wrote this in her first grade journal – so it is official 🙂


As always – these are just my personal points of view and do not represent the views of my employer.

Tech consulting is bound to get disrupted at least twice in my remaining professional life – with pendulum swinging first in the direction of flexibility, and then in the direction of convenience. That means the big and small companies that play in this ecosystems, and the assorted consultants that work in these companies are in for some crazy times. I would venture a guess that the first wave will be within 3 to 5 years, and the second one probably 7-10 years out from now.

When I joined consulting, the career option was pretty straight forward. If you were good at what you did , you can make Partner in about 10 to 15 years and then reap the benefits of that till you retire and then retire on a comfortable pension. Billing rates of $500 to $800 an hour did not raise many eye brows in those days. Well – that has changed for sure over my professional life !

When I hire new college grads these days, I see only a minority who have a career plan of sticking it out at a consulting firm for 10-15 years to make partner. Most of them plan to keep their options open to explore other careers along the way. When I hire for experienced roles – I increasingly see candidates who are from non consulting backgrounds wanting to try consulting for the first time. I also saw the reverse of this when I was in the software business for few years – many consultants (like me) wanted to gain exposure to software business. I am not a career channel management executive – but I had a great time establishing a channels business at MongoDB. In short – traditional career paths are dying and more and more people at all levels of their profession are vying for flexibility .

Interestingly – while employees have made the change in large part to this “flexibility first” mode, most employers are still in “traditional” mode. I believe the inherent difficulty for larger companies is how the financial market looks at them – risk taking is encouraged for small companies, and punished at larger companies. And changing the org model is fraught with short term risk by definition – so employers resist change in many ways. The more progressive ones encourage flexibility in hybrid models – take one day a week to do your own projects, put a consulting guy in charge of channels team, take a line sales leader out of the business and put her in charge of HR etc. They try to “force fit” employees with “new” ideas into “traditional” career paths. It does not seem to scale very well from my (admittedly limited) perspective.

At the moment, number of employees with such career attitude is not large enough – but in 3 to 5 years, I expect it to overwhelm and overpower organizations that a new paradigm will need to be built. And when overwhelming force is applied to organizations with a lot of inertia, the pendulum swings to an extreme. My bet will be that technology consulting firms will become master orchestrators that bring a tailored collection of skills to a client – even though majority don’t work for them directly. But this model has one inherent problem – elasticity is not your friend in labor based business.

So that means – tech consulting companies will need to shift their business model to be more of an IP based one. That needs new skills that historically were not important to these firms – like engineering, product management and product marketing at scale. A lot of existing roles will probably go into a “freelancer” system. Another way of saying it is – there will not be much difference from what is a product and what is a service. These lines will all get very fuzzy . A natural side effect will be acquisitions of product companies by tech consulting companies – at scale, unlike the handful that happens today !

The disruption this causes will be tremendous. Procurement function will need new ways of evaluating suppliers . Analysts and VCs/PEs will need new ways of assessing value of businesses. HR will need new ways of sourcing and developing talent. And so on . I won’t name names – but I have a list of tech consulting companies in mind that probably cannot deal with this and will end up in utter chaos at a minimum, or go out of business at worst. Yeah, I think it will be that dramatic (and I hate drama at work).

What happens next ? The way we deal with such chaos is usually to swing the pendulum in opposite direction. About couple of years into the chaos caused by this disruption – I totally expect leading companies to realize that for scale, some centralization is a must. Its like mainframes to client server to cloud to edge computing – centralization and decentralization happens back to back at intervals to keep the universe in balance. I don’t think the asset based nature of business itself will go away – but I do think the employees and employers will realize the pragmatic limits of autonomy and flexibility and make compromises.

But that still leaves the wild card – the power of automation to disrupt the disrupters. In this 10 years or so that I painted above – there is no saying how quickly automation can influence tech consulting’s business models fundamentally. The incremental changes are already well known – but as with every long term disruptive force, I would bet on us having under estimated the effect it has on our future.

Rethinking IOT and AI for future – I don’t want to take cloud to a drone fight !

IOT has always fascinated me. As a young developer in the 90s, I made a living doing mostly integration work – making two computers talk somehow . And then I moved into the world of data management and analytics. IOT is one of those things that just combine all the good and bad of what I know from my data and integration background. It is of particular interest off late to me given its part of the portfolio I lead at IBM – so I have a practical need to understand it better and think about where it is headed.
When I think of IOT – like many others, the first thing I think of is mobile phones to get the idea clarified in my head. 

I started with “How does an app really work ?” . You do something with the app as a user -leading to some minimal processing that happens in the phone using its RAM and CPU and then some information gets sent to a server somewhere ( as in cloud) where it does the heavy lifting and then it sends  back simple instructions back to the phone. Rinse and repeat for every action . 

The computers in the data center and the processing power of the phone are all improving exponentially . What is not keeping pace is network bandwidth. Network is the biggest bottleneck today and with the explosion of data that we live with today – its going to choke even more tomorrow . This is already true for non IOT world – for example I know SAP Hana projects that could not go forward because of insufficient network capacity . 

That is just phones. What about all the other “smart” devices that have processing power ? Everything from toothbrushes to cars already have, or will have, significant processing power soon . And that is only going to increase over time. 

I don’t know for sure – but between our two cars, I am guessing there are couple of hundred processors sitting in my garage as I am typing this. And my cars are not Teslas,  which probably have many more. As “things” stop needing humans to do their “thing” (see what I did there cleverly ? )  – they will have more and more processing power and local memory. They will generate even more data that needs to be analyzed quickly . And “network” as we know it will be toast dealing with all the traffic .

Already machine generated data is many times bigger than human generated data. These “things” won’t rely on “small data” to work without humans – this will be the “real” big data challenges we need to solve. It won’t be simple text files that count as data – it will be things like sound and video. 

The volume, variety and velocity of data will become quite unmanageable if we wait for these things to ping the cloud , transfer data and get a result back. You don’t want a drone to crash into something because it could not reach its cloud source to exchange data and find out how to land. You get the general idea – things that need quick request/response generally cannot work like how the average phone app works today. Even the next gen of phone apps probably can’t work like how they work today !

So what is the big deal ? Well – the current thinking on systems architecture needs some refresh. Maybe a significant refresh !

I don’t think cloud will go away per se. Just that it will become more “hybrid” in nature. My purist cloud friends who hate the term hybrid cloud will probably yell and scream at me – but for now, I am going to take the heat on that 🙂

What I mean is – a lot of processing where latency is a critical factor – the “things” will become mini clouds themselves. I am sure there is (or will be) a better term for it – but till then “mini cloud” is the official technical term for me. 

These mini clouds might be very powerful – many CPUs/cores/storage/RAM etc – and should be able to do pretty much all real time processing, and also be capable of some point to point interfacing. 

For example if I ordered Sushi and my wife ordered a burger – and two drones are trying to both land in our front yard to deliver our orders – they should be able to talk to each other on who lands first and not wait for both to talk back and forth with their respective clouds. If there are only two drones – perhaps we can tweak existing infrastructure and design patterns to make this work. But what if there are two million drones over my city doing different things ? I don’t want to take cloud to a drone fight !

My other passion is AI and analytics . How do they play in the IOT world ? Well – they need to play in two places at least . A micro version needs to play in the “thing” (the mini cloud) and a “macro” version needs to play in the traditional cloud . And there might even be a third version that brokers information flow in the middle . 

The reason is straightforward  – things need to make autonomous decisions like a drone figuring out where to land given what it can sense . There might not be enough time to ping the cloud and get an answer and hence the mini cloud needs algorithms that help with the task at hand . But this way the drone never gets much better beyond what is already coded . For the drone to get better at its job – it needs to learn from every other drone , as well as some external data like weather etc . In some smaller scenarios I guess point to point interfaces can solve this problem . But at scale – this would mean the big cloud runs advanced algorithms ( probably AI types ) and what it figures out gets shared with all the drones that it serves . 

This is a non trivial problem . Just to reliably sync regular text databases in a distributed system makes life complicated for IT shops around the world today despite such techniques being available for a long time . Just getting one set of machine learning models going is a pain for many teams . IOT just makes it much harder problem to solve – especially considering different vendors might own what goes into the brains of a drone and what goes into the centralized cloud . 

Not to make it more complicated – there are all kinds of “quality of service” questions to be considered too like performance , security , disaster recovery, standards and so on . And of course there are the unknowns – like what happens if a brand new communication protocol comes up that eliminates the network bandwidth problem ? 

Not all scenarios need all the bells and whistles of the drone example I used to make my case . A smart toothbrush probably doesn’t need as much sophistication to reach its peak potential compared to a drone . What that means is that whatever is the future architecture we come up with – it needs to be “sliding scale” friendly . Otherwise at a minimum the economics might preclude scale and viability of the solution . 

Interesting world eh ? If this kind of work fascinates you , let me know – I am always hiring 🙂





2016 nearly in the rear view mirror 

Last year , this week , I was in Austin TX -meeting my new boss and forming a team and planning for what we wanted to accomplish in 2016 . Turns out , this year I am going through the same thing this week – just a different boss/city/team . How cool is that ! On top of that – this might be the last flight of the year too . After the first 100K miles, I don’t keep track closely – but I am sure I didn’t cross 200K miles this year . There is a blessing !

Last year in fall, I lost my father in law and my uncle . This year , I lost my fur kid Boss .

He left me sleeping in my arms , just as he slept in my arms as a puppy the day he came home . I will miss you for ever kiddo !

Sadly , my sister lost her fur baby too – two year old Charlie whom I loved just as dearly . Such a tragedy 

There were just two international trips this year – the lowest in two decades . I could get used to it !

The trip to U.K. was extra special this time – I got to catch-up with friends and relatives I haven’t seen in ages . The last time I saw my young cousin , he was in high school – and now he is a plastic surgeon who bought me a lovely dinner ! 

Next time I should find some time to visit my old Liverpool neighborhood .

Then there was the trip to India for my college reunion . I never had a chance ( and had a fear of public speaking ) in college to get on a stage . So it was amusing and exciting to get an opportunity to address my friends as well as the final year students this time 

Also managed to have breakfast with school mates , hit a movie with my bff from childhood, and ran into a buddy from school after 25 years and he works in IBM too, and managed to have meals with friends in Bangalore that I am in touch only on social media these days   – absolutely priceless !

Even sneaked in a conference on sentiment marketing at SCMS business school 

The best part of that trip was the couple of hours my father and I went out for dinner at the new restaurant next to his house. Achan used to take me to dinner frequently as a child and it was very nostalgic to do it again just by ourselves 

It was also pretty cool that we managed to celebrate Onam with my sister and family in Dallas – something that has not happened in a long time . 

Talking about Dallas – we started the year there celebrating my brother in law’s 40th birthday . And to add to the fun – I also managed to recruit a young rock star developer at the party ! Always be recruiting 🙂

Things were pretty good on work front too . Between (my) luck and (their) smarts – we had an amazing year with fantastic results . The sheer variety of transformative projects – redefining guest experience for a theme park , cognitive analytics to get fine grained insights on viewership at a cable company , advanced smart metering at utilities ….the quality of work we did for clients was outstanding . I can’t wait for more in 2017 .

The real highlight for me this year was that I spent equal amounts of time with my team that I spent with clients . I think I have somewhat succeeded in letting go of my urges to be a front line player and become more of a full time coach for the team – of course with a few(?) exceptions 🙂 . The best part of the time I spent with the team was with my younger colleagues who are startup off in their careers . I am convinced that I want to work for some of them before I retire !

I am also blessed with a bunch of senior partners that I learn a lot from every time we talk . The guy on the left of this picture below – Dave Lubowe – was the one who taught me many years ago that we don’t have customers ,   Only clients !

A highlight for me this year was college recruiting . The passion and curiosity that I see in the next generation of leaders that I met at universities – its the most energizing experience . We are in the talent business and I will do more of this next year without a doubt 

I took a conscious decision last year to minimize the number of conferences I attend . I only did 4 – and the big ones were SAP’s Sapphirenow and our own World of Watson . Both were amazing events and it was great to to catch-up with old friends and make new ones . But the one thing I will never forget is meeting Grady Booch ! 

I also have mixed feelings when I look at the photo below that we took at sapphire . My two dear friends Gagan and Dale have both moved on from IBM . I look forward to cheering them on as they start their new adventures

There was a lot more work life balance this year . I got to drive Shreya to school , attend her orchestra concerts and swim team meets and go for weekly family dinners to our favorite restaurants . Dhanya and I also managed to go to an Ilayaraja concert in Dallas . 

All it took was to reasrange my work life a little by taking less critical calls while driving , delegating a bit more and generally stopping a bunch of low value work that I routinely did in the past . The only part that didn’t work out was a Canadian vacation which we had to abort after one day to rush home to take care of Boss . The one casualty was that I had to get out of a few whatsapp groups to make this work – need to find a way to make this work as I absolutely love the conversations there .

Hobo is now the senior guy since Boss left . He is about as mature as a 6 month old puppy , although he will be 8 on New Year’s Eve ! I am still not used to seeing only two fur kids in my photos instead of three

The photo above reminded me that we did move to a new house earlier in the year . It was quite dramatic with how the process rolled out – but it’s home now and we love it . The only regret is that I have not even hit the driving range once , let alone played a round here . On the bright side – the sheer number of golf balls that land in my back yard gives me comfort that there are plenty of bad golfers out there in the wild . I am in good company 🙂

India has had an amazing year of success in cricket and I managed to catch most of the matches live by sacrificing sleep . If they continue to have this form – I think 2017 will see me sleeping less too . That said , I hardly attended any dog shows . Need to change that next year . 

While I did not manage to read all the books I wanted to – it was an above average year in terms of quantity and quality of reading . The three that I loved a lot outside business books are here 

On blogging front , I was just plain lazy . I read a lot of blogs but generally didn’t write as much as I usually do . Laziness combined with lack of inspiration is a bad combo . I will need to try harder to write more . For the first time since I started blogging , I have plenty of drafts in my wordpress app – just need to decide if any are worth publishing . My gut feel is that I will delete all or most of the drafts over Xmas . 

Merry Xmas and Happy new year everyone !

Granularity of measurement is directly proportional to fear of failure !

Its December , and its that time of the year when I am torn between planning for next year and closing out the current year on a strong note. As I sat down with a bunch of paper drawing up crazy ideas of what we will do next year, I realized I am falling prey to my biggest strength and weakness – the desire to measure everything at the most granular level.

I grew up in BI where if you had granular data, you can generate very sophisticated insights. And I have spent countless hours modeling such data, and writing ETL scripts to get that data in a shape I like. Over time, this has become second nature to me even though I don’t get to do the fun stuff with data any more. Most of my decisions are made on aggregate data today, and the only time I need granularity is when things go wrong and I have to “debug” to find out what the heck happened.

Granular data comes at a high operational overhead – in terms of management itself, and a lot of data wrangling. You need codes to tag every bit of data – and I am not kidding when I say that some times I come across more attributes about the data, and the number of data records itself 🙂

So as I sat here staring at the stack of paper on my desk and the array of spreadsheets on my macbook, I came to the sad realization that my penchant for granularity is simply a representation of my fear of failure. Over time, I have taken over more and more responsibility at work – and the measurements have also become more and more complex and time consuming. This is true for pretty much every employer I have worked for and every client for whom I have designed solutions.

Which brings me to the “scale of failure” issue. As your responsibilities increase, the number of ways in which you think you can fail also increase. And to compensate, we try to measure across multiple dimensions, and matrix the organization some more. At some point, you will absolutely realize that operational over head is not worth the trouble (do you need more checkers and double checkers than people in the field?) but by then you are also a creature of habit that cannot get away from this mess you created for yourself. And finally you also make everyone else in your team miserable – because you force them to tag more and more attributes and unlike you, they might not even know why they are tagging it. I am not kidding – there are many things I was told to do 10 years ago that I had no clue why I had to do. It would have lessened my grief significantly if my bosses at least explained why they made me do it then 🙂

Tagging data and multi dimensional operational reports have another consequence that was perhaps never intentionally designed – the sinister idea of taking credit for someone else’s work . At some scale of business – especially in sales type work – it is hard to pinpoint what all led to a given sale. You will have a direct sales team, and assorted over lay teams that all think they were the ones who drove the business. So they will enthusiastically start tagging more attributes to show their value add and we end up with “everyone is a winner” type scenarios. Even then we won’t typically stop this madness.

So my current plan is – I am going to sacrifice some granularity of measurement in our measurements. I want me and my team to design our work around the idea that we are aiming for success instead of lack of any kind of failure. I would rather fail responsibly quickly and stop doing things that don’t pan out, rather than worry about it every step of the way for all activities for ever. Lets see how that goes 🙂



Boss Vijayasankar 3/12/04 – 12/3/2016

He was the biggest teddy bear of a pup when I picked him up from Marjorie Blake’s house in Bakersfield on May 8, 2004 . Turned Dhanya , who was mortally scared of all dogs , into the biggest dog lover overnight

He helped raise our daughter Shreya – she used to call him Chetta (big bro) till she was about 5 🙂

He was a great big brother to Hobo , when he came home for Shreya’s 4th birthday

He loved his toys – and food . Learned everything he needed for competitive obedience in about 4 weekends and two packs of hot dogs

He was a sage by the time Shreya was born . He got to be a puppy again as Hobo grew up . Hobo was ten times stronger , and Boss was a hundred times smarter and wiser 🙂

Along came little Ollie – Boss was already 9 by then but young enough to show the kid the ropes .

He kept alive my dream that Shreya would some day choose to handle in the show ring 🙂

He loved water – and was the ultimate gold fish . I must have tossed a few thousand oranges into that pool in last decade 🙂

Boss never met a stranger – he loved everyone . But for me he was my best buddy , my shadow . If I slept in – he would come find me and wake me up without fail . He loved riding shotgun with me in the SUV

He was the “boss” of the gang – from day 1

He grew older gracefully , and we celebrated every birthday

He was diagnosed with Hemangiosarcoma in September 2016 . He underwent surgery to get a tumor removed . The surgeon gave us three months with him , and we tried our best to make every day with him the best he had

And today , December 3rd 2016 – he had all the ice cream , eggs and bacon he could eat . And before the vet took over – he had a giant slice of chocolate cake

And he went to sleep on my lap , just as he did the first day I met him and brought him back on a united airlines flight back to Phoenix .

You will always live in my heart Bossappai – you were and always will be the boss . Till we meet again , buddy !