On Friday 1/19/2018, I got a new role in IBM services as the CTO for North America.

It was an honor and privilege leading the CBDS business and I am very grateful to our team and our clients for a very fulfilling time. Pat Eskew and Rafi Ezry will lead it to greater heights and I look forward to working with them and cheering on the team every step of the way.

There are a few people to explicitly thank specifically for this new adventure I am embarking on. First, my boss Ismail Amla who runs services for North America for his trust in me. Second, my uncle Dr Krish Pillai who gave me his computer and the Dennis Ritchie book on C, when I was in eighth grade. I learned BASIC on that computer to code video games and had a huge collection of custom games on cassettes. And I struggled through the K&R book line by line till C became how I think of logic. Third, Prof Kalyanaraman who taught me statistics in Business School – he bridged the gap between math, computing and business for me.  I owe a huge gratitude for my parents who never questioned or hesitated in finding ways to support my varied interests , even when times were REALLY hard. And it goes without saying – more people than I can list here have helped me and continue to help me. Please know that you have my sincere gratitude and I will continue to seek your guidance.

I have some hopes and dreams about the journey ahead of us.

What I would like us to do for our clients is to be a champion for technology minimalism and simplicity. 

Technology has become incredibly sophisticated over time, and unfortunately also quite complex. On top of that there is the constant noise on hype. Every category of tech is a trillion dollar opportunity if you believe the analyst reports. This complexity and hype leads to clients not being able to use the sophisticated tech to solve their biggest problems. Instead – best case they get stuck in endless proofs of concepts, and worst case they stay still and risk becoming irrelevant for their customers.

Its very rare that any one technology is going to add value by solving a big problem. It usually takes the convergence of multiple technologies to arrive at meaningful solutions. This comes with the risk of over engineering , low speed of execution, and a real danger of designing a brilliant solution that can’t change on a dime when market changes. Striking a balance between all these is where engineering meets art.

I have a degree in engineering and business. And though not by design – I had a career where I had one foot each in tech and business. Growing up as a developer and later as an architect, I absolutely enjoy tech for the sake of tech – and I am not ashamed of it in the least.  But with roles in delivery, sales and general management,  I equally appreciate that in enterprise software, no one cares about tech that does not make or save money for our clients. Bringing biz and tech together – discussing the art of the possible, providing reality checks on emerging tech, ethics and trust issues that come with tech, connecting clients with each other and with ecosystem partners, building business cases to justify investments , debating usability of code for humans and machines etc are all things I look forward to working with clients on.

End of the day, its not what we make that is important – its what we make possible for our clients !

I would love for us to be known as the team that our clients depend on for solving their unknown unknowns  

We have an amazing team with a multitude of backgrounds, skills and experiences. Thanks to the opportunity to work with clients across several industries and solving a variety of problems, we know several common problems and also the solutions for those. That minimizes the risk of reinventing the wheel, and maximizes the execution speed.

But that is just the starting point – we need to be able to help uncover problems and opportunities that are not well defined yet. For any given problem – I have no doubts we have the skills to solve it. But a problem is only as good as how it is defined – simply because solutions depend on how a question is asked. The speed with which the world around our clients is progressing – we need to feel comfortable with the unknown unknowns, asking better questions and constantly striving to iterate towards better answers. Technology might not even be the lone answer for many questions – it could be a change in process or people.

This needs us to keep learning, and teaching each other  – broadly and deeply. Tomorrow belongs to the polymaths ! A very wise leader told me once that learning is like breathing – you just can’t stop. I plan to actively continue with our learning initiatives – both as a student and as a teacher/sponsor. The world of technology consulting is changing quickly , and in quite disruptive ways. I hope and dream for us to be on the right side of this change.

On the personal front, there are two things I am committed to this year . First is to exercise more . And after procrastinating for over a decade, I finally signed up with a personal trainer yesterday. I told him that I will hold him responsible for my success in my new role since I will need a lot of energy and strength .  He nodded, and there is a possibility that he may have rolled his eyes 🙂 .

The second is to teach programming to my daughter, to supplement the class she has started . Today I helped her with some nested conditional logic. She was impressed for about 10 seconds and then started telling me that such complex code is useless because she won’t be able to remember later the reason for writing it and none of her friends will get it . A part of me is proud that she immediately realized something about the big picture that took me a few years as a developer to get . And the other part of me is wondering if I have it in me to keep up with this despite my resolution . I see a lot of eye rolls in my future 🙂

As of now, vacation has ended and I am back at work. I am starting a new role at work this year – more on that later. The last couple of weeks gave me some time to think about what is in store for our industry in 2018 . Despite my own misgivings on making predictions in general, I thought I will write these down any way in this blog. As always, these are strictly my personal musings .

1. Data becomes sexy, again, thanks to AI

Customers who have started on the AI journey all realize the same truth – this only works as good as the data that AI has access to. And most companies have less than stellar capabilities when it comes to data management. I totally expect 2018 to be the year of data ….again ! Of course tooling will change from the last time this “data is sexy” thing happened . Rejoice , my friends in data modeling, ETL and so on! 🙂

2. Data security and privacy becomes mainstream – thanks to GDPR and AI

All major companies always had to deal with security and privacy. Now with GDPR, this will become a mainstream topic both for SW and services – with cost and revenue impact . Its not just a back office problem like it was historically treated. Now front office functions need to be redesigned to make sure no regulations are broken. Europe started the trend, but obviously everyone else is going to have their version too soon. If history is any indication, we will end up with even more disparate rules and guidelines across the world. I have this feeling that most international tech companies will spend significantly in 2018 to lobby governments across the world.

GDPR is only one reason – the other is Artificial intelligence becoming a reality pretty quickly all around us. There is a lot of fear about privacy and security – some misguided and some very valid – and this will only amplify in 2018 and beyond.

I am tempted to say something about standards too – but the reality in this industry is that if there are two competing standards, people will come together to create a unifying standard, only to see that now we have three standards instead of two we started with. So – while much needed – I am not holding my breath 🙂

3. Chatbots will get a redo

Everyone seems to have a chat bot these days – but most are useless. I tested at least a dozen over the holidays as a consumer and it was a horrible experience. I think this will start seeing a big change in 2018. To begin with – I think more and more companies who jumped in and created the first generation of rules based chatbots will now start moving fully or partly to more of an AI driven chatbot. Instead of answering just short tail questions, I expect chatbots to answer more and more context sensitive long tail questions, and start to learn more from each interaction. This is another reason for data management to get a big boost. 2018 might also be the breakthrough year for voice to text capabilities – this is something close to my heart, given my thick Indian accent often confuses existing APIs.

4. AI will start democratizing visualization of data

I grew up in BI. From the time I started as a young BI consultant, I have believed that the best BI experts are more artists than engineers. It took me a long time to become a decent visualization guy. And having been in the field for a long time, I know I am in good company. We have more people who are experts in back end engineering than we have people who can make high impact visualizations. I don’t think the core principles like making data actionable, making sure it is context sensitive etc will ever change . Now the tooling has improved significantly and that is absolutely a good thing. Unfortunately, the complexity of the data (types of data, their interconnection, the speed of change of data etc) has also increased a lot and the challenge of visualizing has also increased a lot. I think this year we will start seeing the world of visualization start to rely more on cognitive technology and try to democratize data visualization for lesser mortals like me. I am not sure if this is a prediction or really a cry for help 🙂

5. Open source starts looking more like proprietary  

Everything new eventually starts to look like its predecessors in our industry. It usually takes 15-20 years or more. I think Opensource software is now at a stage where no one has any sustained advantage, because there is hardly any barrier to entry for someone else. Also, every popular category – like databases for example – is way too fragmented. By becoming extremely developer focused, many new companies ignored ops tooling which adds to the customer head ache. At some point it becomes an untenable management overhead for customers to run a different software for every unique workload. I think this year we will see a change to this – OSS companies will probably start keeping more of their wares on commercial licenses , some larger companies will buy out a bunch of smaller public and startup companies and so on. I could be wrong on timing – maybe status quo will prevail another year or two, but I definitely think this will happen very soon.

6. World starts to come together for better/simpler debugging and monitoring

2016 and 2017 have made sure that containers and micro services are here to stay. Most new development will be cloud native in nature. While my purist friends still are waiting for one public cloud to rule them all, I am still on the commoner band wagon of hybrid cloud as the only pragmatic option. With every passing day, we will also create more and more sophisticated abstractions. All good things for the “happy flow”. But life in enterprise computing is rarely about happy flows – the effort to debug and monitor across all these layers has also become tedious. With all my previously stated misgivings on efforts to standardize – I do think we need thoughtful and simple open standards for debugging and monitoring in the increasingly distributed computing landscape. Given the momentum we are seeing, I am betting on this year forcing the community (perhaps led by APM gang) to come together and start putting the building blocks in place.

7. Lot of tech M&A in store, probably more startups will exit/ IPOs too. 

Companies are sitting on a lot of cash already. On top of that, the GOP plan has a tax holiday for bringing money from abroad. After giving $1000 bonuses and increasing dividends, there will still be plenty of cash sitting around in big company bank accounts. Estimates of $1 to $3 trillion have made rounds on how much cash is stashed abroad by American companies.  The sensible move is to use a good amount of this cash to start massive consolidation in the industry. This should happen across all segments – HW, SW, Cloud,…

A side effect of this is that startups should get a lift – either via IPO and/or by selling out to someone with deep pockets.

8. Devices/Things will become smarter and more secure

IOT , despite the hype, is a thing already. The fear of man made calamities like DDoS is also very real. And it is clear that leaving all decision making logic to cloud is not viable for more interesting use cases (say like a self driving car). I expect to see a lot more logic being executed inside the device itself , and a lot of hardware level security features added that cannot be changed via a software hack. None of this is new – just that I think 2018 will be the tipping point for this to become more mainstream. A good starting point in my opinion would be the routers on home networks – designed ground up with the idea of securing connected home devices on the network it controls.

9. More block chain branded companies this year

Last year we saw big data companies make the pivot to be machine learning companies. They did not want to be known as hadoop or ETL or NoSQL or anything remotely related to data, but over night change to Machine learning companies . Those that missed that round won’t probably bother with AI/ML anymore – I expect them to find a way to brand (hopefully also engineer something real – at least some of them) themselves as blockchain companies. Nothing wrong with this per se – no one is really fooled in this industry anymore with branding changes. There will be a temporary head ache for real blockchain companies to demystify stuff for their customers, on top of the topic of the day which is crypto currencies themselves.

10. ERP companies will yet again start to design their next generation products

ERP has evolved a LOT over the years, and mostly for the better. Just a few years ago, I thought their hardest challenges will be the move to cloud and improving usability (better UI, speed, simplicity etc). Those challenges have been addressed – admirably in general, compared to where they started. But I think even bigger challenges have now come up for this category.

ERP was fundamentally designed for efficiency and for human users. Now with AI allowing machines to learn and improve, the static nature of ERP is fast becoming a thing of the past. Small AI innovations have been started by pretty much every ERP vendor – but that is not even minimally indicative of much their world is going to get disrupted. The next generation needs AI at its core – it should be the center of continuous learning for every organization . It means not just efficiency is key, effectiveness becomes the new normal. On top of that – human users won’t be keying in much of the data any more. That work will be taken over more and more by machines . A lot of logic associated with screen flows in ERP today will be useless in that world. Even the current sophisticated interfaces built on ERP will be less efficient when it is always a machine that is going to talk to it in binary, or if its a human using voice or text strings . To some degree, I know the internal architecture of the main ERP systems in use today. Barring maybe one exception (not naming anyone given everyone is a friend) – I think rewriting most of their software from the ground up is probably the only way these existing systems will move into the future. If they don’t do it – I am reasonably sure that someone else will disrupt them from outside .

I have been listening to a bunch of old songs this morning, while also taste testing different coffee beans I bought over the holidays. I am not sure why, but the lyrics keep giving me hints about technology. So here we go 🙂

1.Artificial Intelligence 

I can hear the sound of violins long before it begins

3. Crypto Currencies 

But there’s a side to you
That I never knew, never knew
All the things you’d say
They were never true, never true
And the games you play
You would always win, always win

4. Internet of Things

5. ERP

6. Predictive Analytics

Do you know barbarella, magical barbarella
Mystical fortuneteller
Selling your dreams to you

I started 2017 on a rather sad note, having lost our older fur baby Boss towards the end of last year. A year has passed since the day he went to sleep on my lap and that pain lingers – though I must say old photos of him do make me smile more now.

To their credit, Hobo and Ollie have been trying their best to cheer me up since Boss left us .

On the bright side, I also had started in a new role in IBM as the GM of Cognitive business in North America, which made me excited and nervous in equal measure .

I inherited a team that was 4 times larger than my last one , with an extra zero at the end of my target numbers . Almost every one of my direct reports had managed me at some point in my past career – so I had a group I had known very well and trusted each other for a long time. I had a new manager, whom I knew from before but hadn’t worked with since then (who turned out to be a great friend and mentor) . To make things even more exciting, I also got a portfolio that was a mix of our bread and butter businesses and our hyper growth businesses .

We were not short on opportunities or challenges this year. Giving confidence to clients across North America to pioneer new technology, modernizing our skill sets and business models , integrating new members into our gang and bidding farewell to several friends , learning the parts of the business I did not work on previously, Acting as a sounding board to my team mates , Getting mentored by great leaders … it just was a blast !

I learned a lot too!

One of the biggest learnings for me was that “Authority is an illusion “. I had heard it before but now I have a first hand appreciation of what it means. I had to learn how to influence and motivate more than use formal authority. I am far from mastering it, but I have started on that journey.

I have always prided myself as being good at delegation. And yet it became clear that as scale increases, you have to unlearn and relearn how to lead. And to delegate effectively, I needed to recruit and train better , and learn how to motivate a large heterogeneous team and so on . Clearly I had several areas where I could spend time to improve . And I chose education as my primary theme for the year, while trusting my team to take care of other important aspects of the business .

In retrospect, I am glad I prioritized learning.

We are a services firm which means we are a people business. We are competing in a fast changing market where you become obsolete very fast if you stay still for even a short time. Sponsoring our first business leadership school ( Bee school ) and our Technology school (T school ) also gave me several invaluable benefits I did not expect . I got to meet hundreds of consultants and engineers and learn about their work and what their hopes and fears are . I got a whole new appreciation of several back office functions like Ops, Finance ,HR, L&K and so on than I ever had in the past and as a result I will never take them for granted anymore and will be very grateful for what they do. I met several leaders who volunteered as faculty and learned from their experiences. What an absolute blessing it was !

Some things did deteriorate this year as well . I nearly didn’t read as many books as I usually do . I am getting caught up towards the end of the year, but it’s something I need to keep an eye on for next year.

I also did not blog as much as before – which I am not actually unhappy about . I just switched to more short form posts in LinkedIn . I did have two fleeting moments of internet fame – one for defending Watson and another for highlighting the challenging life of product managers 🙂

2017 turned out to be one of the few years when I didn’t go to India. But my parents and my mom in law visited us here, so at least part of the India visit was covered indirectly .

And I only had one international trip this year , to Japan .

Clearly I was on the road enough to retain my executive platinum in AA and diamond in Hilton Honors with room to spare. Travel continues to be the most unproductive part of this profession that needs an urgent disruption .

One experiment on personal front that I am happy about is on gardening front, thanks mostly to my mom in law staying with us for several months this year .

Between assorted flowers and a small vegetable garden, I started reliving the joys of childhood ! Plenty of rookie mistakes made , but what the heck – it was a lot of fun .

Also, on the (very) positive side – I got to spend more time with my wife and daughter this year than usual. The highlight was the trip to DC and Maine to check out National monuments and fall colors. The big regret on that front was not being able to make Shreya’s concert at school this fall when I was stuck in east coast .

I have practically stopped competing in dog shows, but I was fortunate to visit a few as a spectator and hang out with my old friends and their fur kids. Also for the first time, managed to see the Great Dane Nationals, which happened in Chandler. Icing on the cake was that for the first time since I moved to US, I found 3 friends from India that I showed dogs with back in the day.

All things considered, I am truly grateful for this year. I just wish I spent more time slowing down to smell the roses . Well, there is always the next year to do that, right ?

Wish you all a merry Christmas and a happy 2018 !

My guess is as good as yours on how AI will influence the world around us in the long term. All possibilities from solving world hunger to we becoming Cyborgs remain on the table. However, I do have some thoughts on where this field is headed in next few years – say the 5 to 10 year window. As we wind down 2017, I thought I will share four of my thoughts on this topic – enjoy it with your favorite holiday beverage 🙂

Invisible AI vs AI face-offs every second

Several big companies have invested in personal assistants powered by AI – with varying technology maturity. Some of the hottest startups across the world are working on giving the big companies a run for their money. Given I am not an impartial observer given my day job, I will resist the temptation to predict a winner. More and more money and time is being poured into this category across the industry.

Personal assistants will be a part of everything we routinely do going forward. And the change it will bring profound disruption all around us. For example – we might outsource our routine grocery purchases to a personal assistant. The logical next step is for grocers to stop sending us coupons and loyalty cards, and instead market to our personal assistants. That does not need TV advertisements or glossy news paper inserts or targeted emails. That communication is on some machine readable form – say JSON or perhaps even binary. The best Ad agencies will need to hire best AI experts, not (or at least not just) the best creatives.

When customers outsource buying to personal assistants, vendors will need to resort to AI to respond as well. And working backwards, the entire supply chain will need to get redesigned to be a lot smarter. Both consumer and enterprise tech will face a fast faced evolution.

The interesting aspect will be that most of this profound disruption will happen behind the scenes without us realizing what is happening – there will be an AI vs AI face-off (hopefully of a good kind) every second as we go on with our lives blissfully unaware.

AI Safety frameworks will emerge 

As Spiderman said “With great power comes great responsibility”.

This takes many different forms in the field of AI, and might never get fully solved even in long term. Also, vast majority of these smart applications are probably never going to be actually harmful, even though they may become super annoying ( I am looking at you , Linkedin algorithms favoring double spaced god awful posts.) . 

1. Since fast iteration is the norm for most AI initiatives, it is important that we have some way of proving safety of such applications mathematically before deploying in production. Today, we can already prove somethings – but this needs to improve big time and become mainstream.
2. We need consistent hardware level protections. Most interactions generating data for AI to work on will be between machines , or between machines and humans. Software cannot be the lone line of defense – hardware level security should become a given. That will need a lot of standardization, which is not a term our industry particularly likes.
3. Ethics and law needs to be taught to all AI practitioners, and need to become part of the curriculum in early education. Awareness of the distinction between good and bad usage of AI need to become a minimum requirement.

AI Project team structures will change

Math and coding skills are not enough to do AI projects well. This is not new – we have already known this for a while. I think we will start seeing teams organized in four overlapping specialized groups going forward.

Most AI roughly follow the same cyclical sequence .

1. Understand ( language, sound, vision, smell, touch etc) and Organize information from the environment
2. Reason using math and logic , and make trade-offs and come to decisions
3. Interact with humans and/or machines to convey decisions (UI, psychology, visualization etc) and collect feedback
4. Learn from results on how the decisions worked and tweak how the problem will be solved from now on

Today, we try to do all of this with very little specialization – except perhaps in the math/logic side, and industry domain knowledge. But that won’t sustain going forward to cope with the scale – each area will need specialization and a lot of collaboration with each other.

Academia and Industry will become indistinguishable

There are two things an AI team needs to stay cutting edge – quality of AI talent , and quality/quantity of data available to make the solutions smarter.  No surprise then that most of my time gets spent finding and retaining such talent. This is true for all my peers across the industry too . If there is one set of people who are under even more stress than us in the industry – that would be the leaders of top universities. Industry and Academia has generally had a good working relationship historically , but the war for AI talent has Industry aggressively poaching AI talent. This might be great for the short term – but absolutely horrible for the long term. Who will teach the next generation if industry keeps poaching the best teachers and researchers ?

Academia has started great initiatives to let professors go to industry and come back – but not in a mainstream way as far as I can tell. And industry has not – in a mainstream way – gotten into the habit of thinking of academia beyond special projects and consulting. This is not an AI specific problem – AI will just make it painful enough for both sides to get to a solution quickly. I think what will happen is a de-facto working arrangement where there is little to no difference between academia and industry in the field of AI with experts just wearing different hats as needed.

Happy holidays !

Fair warning – this is a rant ! You should probably stop reading now .

Every year, I read 15 to 20 non fiction books. For last 5 years or so, the trend is exactly the same. I get to about 5 books by end of September…and then pick up speed and read 3 times as more in one third of the time. Also, I only read physical books – I don’t use an electronic book reader. Its an “old world” habit I am incapable of kicking. Its one of those things for which I have no rational explanation 🙂

Any way – this year I also noticed one more thing making reading harder for me. I started reading Satya Nadella’s auto biography and its not really a long read. I should have finished it in one day. Instead it took a week or so. The reason – every time I settle down to read, I want to put a song on my phone, check email, see the cricket score, play 2048 on my phone or something. It was ridiculously bad – and it took me a week to realize I can’t read a full book if my phone is anywhere close to me. So I started switching it off and leaving it on a charger in a room as far away as possible to where I was sitting. In planes, I started putting the phone into a bag that I shove into over head space. Pure magic – every book again returned to a one day adventure !

And then I realized the second problem. I have no patience left for long form prose. Thanks to micro blogs, blogs  and bulleted emails that I deal with all the time, beautifully written prose no longer looked beautiful and I was getting irritated. Thankfully couple more books in, life returned to normal and I started enjoying the good prose like usual.

Twitter does not take much time for me – I scan it about three times a day and very rarely have quality conversations on it. Thanks to carefully choosing who I follow, twitter has become a great news feed for topics I like. Any time there is an election, I mute a bunch of handles to keep the noise down. In general, I have no complaints. And strangely, the number of followers keep increasing all the time.

Similarly, I have no big issues with Facebook. I have a lot of friends and family connected on FB. Quality of conversation is extremely high and a lot of topics which used to get debated on twitter has moved on to FB now – and not really to linkedin which is what I expected.

Linkedin on the other hand has become a major pain in the rear for me. For a while, it was a nice place to use as my address book, and even more importantly – it surfaced some amazing content for me to read every day. There are two primary annoyances for me these days on linkedin – 1. God awful job recommendations ( including Catering, Truck driving, divorce attorney etc )and reading list recommendations and 2. People typing up double spaced single line sentences ad nauseam on HR and sales topics.

The double spaced thing looks like this

I interviewed a young man today.

He had no experience.

Looked like he had not showered in a week.

He never went to school.

He was not getting hired anywhere.

I skipped the interview process and hired him on the spot.

Because that is what leaders do.

Now he is the Chairman of a $20B business

My coping mechanism is straight forward – I block the people who post it, and also the people who share/like/comment such things and makes the linkedin algorithm put it on my feed.

And then there is whatsapp – which is supremely useful except for the flood of forwards and “good morning” messages from friends and family. Again the solution is simple – warn the folks who do it, and block repeat offenders. I think half my contacts are now blocked and I am guessing I won’t be invited to several Xmas parties this year 🙂

Every year I have taken social media sabbaticals for a month or two from multiple channels. That has been plenty to keep me sane these last ten years. But clearly that is not enough today. These channels are quite useful for many things – and filtering only goes so far. For now, I am planning to take longer social media sabbaticals . I also need to find/read about the latest greatest tips on how to not get overwhelmed by my social channels and phone. If you have good tips – pls do share.

End of rant !

Although I have spent a lot of time with lawyers reviewing contracts and stuff, I have never set foot in a court room in my life.  But, I have always loved court room drama in movies. I love the debate between opposing sides, with a judge providing guard rails and taking a decision based on evidence, laws and consistency.

The first line I picked up as a child from the Malayalam movies I grew up with was  “Objection, your honor !”.  This usually involves one lawyer jumping up dramatically from his seat to register his objection to what the opposing side is saying. The judge would then make a determination via “Objection sustained” or “Objection overruled”. The beauty of the system – at least as shown in movies – is that all sides agree and move on once the judge makes a determination. Worst case, one side presses on after the judge ruled, and a strict warning gets issued which returns the situation to an equilibrium.

I have not seen a movie yet where the lawyer who is asked to stand down then throws a fit and leaves the court, and sends in his resignation from his phone :).

For a long time, I consulted to a client who had this culture in their DNA. They called it “Disagree and commit” and practiced it religiously.

Literally anyone in the meeting can – respectfully – challenge any prevailing wisdom that is  being discussed. As long as the eventual decision was not opposed to company values, and did not have ethical/legal type issues – people who originally disagreed with the decision also commit to make it successful. Decisions were not always democratic – sometimes it was just a leader taking a judgement call . Having watched it play out for a long time – they largely followed through on that promise. That company went from strength to strength. It also helped shape my philosophy early on about stellar team performance in a big way.

“Disagree and commit” is EXTREMELY HARD ! . And it only gets harder as you take on more senior roles . A lot of things need to fall in to place for this to work well.

To begin with, you need some conviction that the rest of the team is at least as smart as you – if not smarter. If you consistently think the rest of team are dumb asses who just don’t get it, you will only ever disagree – you will never commit ! .

The resolution varies from you getting coaching to get a fresh perspective, the team getting redesigned (perhaps by excluding you) , or you finding a team where you fit better and trust and respect the folks around to you.

Since decision making needs to happen frequently in any team – its usually too late to resolve this dilemma post facto. The smart thing to do (whenever you can) is to be very careful where you choose to work, and who you work for.

It is quite possible that you are the smartest person in the team and the rest of them truly don’t get it. This is a true test of leadership. The make or break here is empathy – whether you can put yourself in their shoes, and reframe your point of view to change their thinking. Its also a test of your own ability to make trade offs. Can you live with yourself if the mission fails ? Is it better to not rock the boat and risk losing your job with a mortgage to pay and two kids in school ? Can the team course correct if you succeed to show them half way through that the original idea was not the best ?

One tactic I have used with better than modest success, to commit to something I have disagreed with, is to get the team to set up a few early milestones as check points.

This is not always possible – some times they are “all or nothing” commitments . Yet, whenever possible, it helps to minimize potential damage. I readily admit that some times such check points have proved me wrong ( so much for my strong belief that I was the one who was smartest in the gang) .

What if you truly can’t live with yourself with the decision that the team agreed on ? You wholeheartedly disagree – but you just can’t commit. Hopefully these are few and far between scenarios (If they are not, most certainly you should quickly take help from your coaches and mentors).

The first thing to do here is to make a determination whether you can let the team do what they agreed to do without causing any additional roadblocks yourself actively or passively. When we are experts in an area – we tend to think in extremes. Everything that could go wrong, we will assume they will go wrong, and horribly so.

The truth is that only very few risks have high probability to occur and high impact if they actually do occur. So perhaps you can help the team identify those, and provide ideas to mitigate – as opposed to just dismiss the whole idea summarily.

There is also the idea to resort to “policy by lapse”. The idea is like “If you don’t like the weather, just wait a bit and it will change”.

This could also work, if used occasionally. Unfortunately I have known many who choose this as first and only way – and they become a boat anchor on their team’s neck. The first chance they get, the team will get rid of you from their midst. Ergo – use with extreme caution !

If none of that work,  the next thing to explore is to find something else to do – in your current team, or elsewhere. While you are searching, you need to find a way to minimize spreading negativity. By spreading negativity, you will continue to be miserable, make others miserable, and earn the kind of reputation that will be hard to shake off.

It is never easy to go find another team if you just realized you need to do it and you have only 3 days to do it. Unless you are on par with Elon Musk – You should assume throughout that you need Plan B and Plan C at all points, and keep them refreshed periodically.

All those things like having an active network, keeping your skills sharp, letting the world know of what makes you special etc – they are essentials in your career for a reason !

I will make one last point before I sign off. If you are miserable and are looking for your next adventure, don’t just go looking for what open opportunities exist in your network. A focused “This is what I would like to do, and here is why. Can you help?” ( being careful to not come across as arrogant) will trump the generic “Here are my skills and experience, is there anything open that suits me?” most days.