And Vijay Says…

I joined IBM …again , after nearly a 3 years gap, for my second innings !

Today morning , as I woke up in the morning in my hotel room in Asheville, NC – I reached for my iPhone to check mail . Then , as usual I quickly scanned Twitter and then Facebook . And there it was – FB alerted me that this was the day last year that I joined IBM , with a photo that I had posted from my orientation class in Herndon,VA . Talk about “digital transformation” being real 🙂

I can’t believe a year has passed ! Time really flew by me . In this short time, I have already worked in three roles across sales , delivery and service line leadership . That is one reason I haven’t noticed the time – each role needed me to learn something new and that has kept me on my toes . That in a way surprises me . In my last two jobs – after a few months, I generally had a feeling that I have a grip on how to run the business. Once I came back to big blue – most days I get up thinking “there is so much more to learn”. My current passion is machine learning – and how I wish I spent more time listening to my statistics professor .  All of this comes with its own fair share of pressure , but for the most part – it’s pure fun!

Travel has not reduced significantly – but not as many international trips given my patch is North America now . I have travelled about 70K miles already this year, and probably will do another 80K in second half of the year . But I do get to spend some more quality time with family and have slowly gotten better about not being on email throughout weekend etc . Not sure if my family and fur kids think of it that way 😉

One thing that helped me get settled quickly in my second innings was that I tapped into my network of mentors early and often. Even got a few new mentors along the way . I have also consciously decided to spend more time coaching our new hires and helping them get settled – and nothing is more gratifying seeing them succeed . It doesn’t hurt that I am blessed to have a fantastic team that makes me look good 😉

Our team is very diverse now – across multiple dimensions . I wouldn’t have it any other way now – the business results prove how valuable it is to have a team that is diverse . I have some great partners, associate partners and senior managers in my team – but what makes my gang special is the sheer talent of the New college and grad school hires. These are our future leaders and I already think I will work for some of them before I retire . Absolute rockstars !

I have also had the chance to try a few new things in my job . I now interview candidates at all levels over coffee at the local Starbucks on Friday afternoons . It helps my recruiting team schedule better , and I get to observe them in a neutral setting which helps them be at ease mostly. We even do some joint coding or design to see if we can work together . I am also slowly getting comfortable with interviewing on video via hireview. 

Another experiment that is working out well is changing how my staff meeting works . We meet every Friday morning for an hour . For the first half hour we discuss regular business – pipeline , talent etc. For the second half hour – I invite an eminent external guest to address us. These are customer CXOs, analysts , executives from competitors , etc. These are informal sessions – they talk candidly on a topic and we get to ask questions . No PowerPoint , no recording . Just straight talk ! And it helps keep us grounded and minimize the echo chamber effect . 

There are plenty of areas to improve too – like delegation . At every order of magnitude of your portfolio, you have to relook at how you delegate . I have some ways to go there . The ability to better balance short term with long term is something I am learning from my boss now – and I am sure I will figure it out soon . 

A few things have suffered along the way . Reading list has grown , reading has not . Same thing with blogging . And I generally avoided conferences for most of last year – except two. Those are all in the bucket list to get better at .

Before I end this rather long blog – if I could only thank one person for keeping me productive in IBM, I will choose my executive assistant Thelma Reed (and Andrea Edwards who backs her up, and who is literally a clone ) . I don’t know how she does it all so gracefully and efficiently , but if she wasn’t there – I know I will be paralyzed just dealing with my calendar . Thanks for everything you do Thelma !

Can’t wait to see what is in store for future 

A couple of months ago, my wife and I found a house that we really liked – nice neighborhood, close to our daughter’s school and so on. So we decided to put an offer and see if we could get that house.

Our realtor uses docusign – so the entire offer process was done online. And I started to think that this home buying exercise would be such a frictionless experience. Boy , was I wrong !

Lets start with the loan application.

We had enough savings to put a downpayment .  I have an extremely good credit score and fairly low Debt to income ratio. I have also had my checking, savings and credit card at the same bank for many years. I even had my past mortgage and line of credit with them . The bank would know everything that happens in my life – after all I have been in their top tier of loyalty program . I generally expected to walk into the bank’s office , sign some docs, share my tax info and W2 etc,  and expected a loan to get funded in a few weeks . 

I also wanted to take a home equity line of credit from the same bank and filed an online application for that .

Guess what – turns out , my bank doesn’t know anything about me . My line of credit application went into a black hole . Few weeks later , I called them and forced them to work on it . 90% of information they collected from me are things they readily have with them but didn’t seem to have access to ! 

The end of this process was even more weird . They sent me a letter saying I asked for $X and it is denied because my house appraised at a value that is slightly (by few thousand dollars ) lower than what’s needed for the line of credit . So rather than offer me a slightly lower credit line , they just denied it . So much for all the top loyalty tier and time spent on it . I am still shaking my head on that . Absolutely bizarre !

The actual loan application didn’t fare much better . And finally they came back with a loan that cost me more than what internet lenders offered . Plus they needed several more weeks to close than others . 

Cut to the chase – I went with another lender who offered a better rate and faster time to close . My bank just lost my business – they tried really hard to not win it . 

In hindsight , I should not have been surprised at all . A trained monkey looking at my checking account statements would know when my car lease would end . My bank was never once able to use that information to offer me a car loan . This doesn’t need complicated analysis – it’s just stupid . Clearly, you can’t fix stupid . 

My lender wanted to get a HELOC note for a line of credit I had paid off and closed in past. I  went to the bank only to be given a toll free number . After speaking to multiple people , I found a helpful lady who found the note for me . However she only had two options to send it to me – regular mail or fax . Email apparently is still alien technology for them. I had to call my wife to hook up a fax machine and get the document . My neck hurt from all the shaking .

So yesterday I went to the bank to get a cashiers check for the down payment . I used my debit card – which has my photo – to take the money out of my account . The teller then exclaims she cannot verify my signature because I had opened that particular account online without a paper form showing my signature . My debit card PIN and my photo on it , and the signature on my drivers license didn’t count . She had to get her manager , make me sign more paper before they could get me a cashiers check . Easily an hour lost for me , and three employees at the bank . I now have a bald patch on my head thanks to scratching my head since then till now . 

So that was the bank . Let’s move on to the actual paper work after the loan is secured. Barely 20% of the documents can be electronically signed . Rest needs trees killed and ink spread on paper . Emperically – redundant information to be filled by the title company is probably around 50% across all the forms I had to sign . Chances of making errors are everywhere , let alone the sheer time needed to fill all those forms . Even if “digital” can be ignored , why not at least streamline the paper forms ? 

A company like DocuSign can single handedly disrupt this terrible manual process and bring it to 2016 digital standards . They will have the gratitude of home buyers and sellers across the country – and their money !

These are not insurmountable problems even by technology capabilities of a few years ago – which is why I am all the more annoyed with this . I am not calling out the bank by name – but I am going to find the CEO’s email id and send this information . And then I will wait by my fax machine to hear if he can do something about it . 
 

I had a lengthy conversation with an old client yesterday on his plans to start some cool new projects . That is what triggered this blog 

Most of you already know that I am not too big on categorizing this topic into predictive , prescriptive , cognitive and so on . I never cared about the old “is it analytics , is it BI , is it just reporting” debate either . All I care is whether data can be used to solve problems somehow . So when I say advanced analytics – all I mean is using data slightly more sophisticated than to report past performance . 

On the software side – volume is no longer as big a challenge as it once was . Storage ( and RAM and CPU and …) is getting cheaper and compression is getting better . It’s still not trivial ( for example – when a semiconductor chip is produced , one optical scan can produce 10 to 30 TB of data per wafer . Even at current prices , that is expensive to store all of it) . 

The hard parts are still velocity and variety . Everyone can eventually get to the same result – but competitive advantage is only for the first few who can see the result . Even within that set – only a small number can actually act of information quickly . Now if the raw data hits you really fast – there are real challenges . 

Software ( whether it is app or database)  is hardly optimized for read and write at the same time when the incoming data is variable . If you need to put a lot of data into your system at a high speed like say in some IOT scenarios – there are databases that are optimized for it . But those databases need extra fittings to make that data available to be analyzed in real time . There are others that can do sophisticated analysis , but they don’t always allow data to be put into it at the speed it arrives . Essentially a lot of compromises and data duplication are still daily struggles for many of us . Granted it is getting better – but it’s not there yet . 

In many of my customers – even after all the software puzzles are solved , we hit a wall on network bandwidth . Cloud is sexy and all – but every hop takes a toll . 

After we figure out the right way to put all the data into the places we need – then starts the analysis pieces . Between COTS and opensource , there is no shortage of software that can do the job . But the idea of democratized advanced analytics is still a distant dream .

There are many aspects to this problem 

1. There just isn’t enough talent who understand statistics ( err data science I mean)to begin with 

2. Generic data scientists won’t cut it . Sales data  from an automobile company cannot be analyzed the same way as sales data for an aerospace company . Industry knowledge is key . That makes it even harder to get the right people on the job – and hence you need teams that have data scientists and industry experts for foreseeable future . 

3. There is hardly any consistency in legal matters across the world . Now we also need lawyers in such teams to make this work in a way that no one goes to jail 😉

4. Legal does not mean ethical always (there is a surprise) . So now we need an ethicist (such people do exist) to help answer some questions on what data and what analysis is ethical . Then you might need an MBA to figure out the solution with all the constraints applied 😉

5. Even if you have all these people and all the right software , you still need to convince the customer that it’s a big production and it comes at a price , although for all the right reasons . Then you need to explain why it is not a good idea to get two data scientists from the body shop to create a model 

6. Even if the customer sees the value , and spends the money – after the team shows the model , it could look really simple and customer will again ask “why didn’t I just hire two junior data scientists to get it done ?” . (The sausage making ( fitting the models) is not fun – it usually is darn tiring grunt work- to watch unless you are a data scientist yourself )

7. Neither Models nor data stay static . Unforeseen things can come up and there might not be a way to predict meaningfully using past data and analysis . For example – lookup why Nate Silver could not predict Donald Trump becoming GOP nominee 

8. Every prediction comes with caveats – some trivial and some complex . Trivial ones can usually be ignored and an automatic action triggered ( like for example ABS kicking in a car when some conditions are met) . The complex ones need significant explanation – and that is not easy unless the recipient of the information understands some basic statistics . There are software vendors who claim their wares can make predictive analytics available to lay users . What they don’t do is explain what caveats apply when those users see results of their analysis . 

9. Like with everything else, things go wrong all the time in analysis too . Complex analysis is really difficult to debug today 

10. Even if all these challenges are over come , and you tell the customer there is a 90% chance of door 1 being the one to open to find the pot of gold , it could still be that door 2 was the right answer that time . So now you have to explain why that happens 

I can go on , but I am sure you get the rough idea already . If not – buy me a beer and I will give you some examples of real life situations I have dealt with 🙂