And Vijay Says…

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 🙂

To begin with , I am so tired now ! I thought I had an easy schedule but between lack of sleep and walking around OCCC , I am exhausted . I skipped the concert , ordered in some food and thought I will post this blog before sleeping

It was great to meet friends from all over the world . It’s absolutely an annual pilgrimage for many of us . Steve Wozniak on the ASUG keynote stage was a great bonus – what a great guy !

First off – SAP needs to be congratulated on tremendous customer focus this year . Having an iconic customer like Nestlé on keynote stage with a strong endorsement – that was huge!

I did have a chance to talk to several SAP customers this year accross the event , the various parties and at the Hilton bar . Now I clearly know why SAP leaders hit on the “empathy” theme on their keynotes – customers are looking for more action (perhaps less talk too) from SAP on implementation management , integration etc . Surprisingly no one said anything about SAP support . Maybe 3rd party support is not as big a deal now as I expected it to be .

The “surprise” for me honestly was that SAP leaders themselves seemed to be surprised by what they heard from the CIOs they spoke to. This frustration has been there for a while amongst customer ecosystem .

Integration is a complex topic for SAP for many reasons like

1. SAP has a bloated portfolio . How many ERP versions are there today ? Three S4 things , A1, B1, BByD , Anywhere … And some probably overlapping with each other . Sure it can be argued that the customer base can be segmented in a way that makes a case for each ERP product . But that is mostly an excuse in my mind . If they don’t rationalize portfolio – real integration will remain a dream

2. SAP has a complex organization , which is matrixed . It’s not always easy to find one owner for any integration . Someone at executive board level will need to be a task master to pull this off and this will take some time to get it done

3. There are way too many acquired products – which don’t have similar technology or metadata to core SAP products . It won’t be trivial to build meaningful and seamless integrations

Nevertheless , I think SAP absolutely needs to be congratulated for taking on this challenge heads on . I wish Bernd and others the best

Just as integration is a challenge , so is tackling customization . SAP has had many different ways to customize and enhance its products over time . If the engineering team can find a way to extract those into an abstract layer in an automated way – SAP can move its entire ERP customer base to cloud in one shot without any of them losing their supposedly unique differentiators . It will be a moonshot R&D project for SAP and I am not sure if that is something they will take on now or in future

I spent some time with Nayaki Nayyar on IOT . It’s probably the first time I heard a clear articulation of what SAP wants to do in this space . Good start and I will be keeping an eye on it to see what unfolds

Carsten Thoma , the president of SAP Hybris , was impressive in his vision and his pragmatic approach . Integrating legacy CRM , SD etc with SAP Hybris is not trivial. New channels keep cropping up and this team has a lot on its hands . For those of you who understand pricing engines – think of the effort to rationalize three or four disparate approaches ! What impressed me the most was the idea of a customer profile that SAP Hybris can generate on the fly across channels . Carsten confirmed they use SAP HANA and MongoDB for it in back end.

Alex and Dinesh hit it out of the park with what they showed me about Ariba . Brilliant UX and probably the product that convinced me that SAP can deliver on simplicity . The guided buying scenario , triggered by a free form search – I loved it . Dinesh showed us how the APIs are exposed – and I hope they open it up to every developer in the world , and not just the registered SAP partners . My other wish list was that suppliers be allowed to push campaigns and promotions to their catalogs .

Talking about UX – I did not get as big a kick as I expected out of the digital boardroom solution . Granted it looks very pretty – but seemed like more of visualization and less about insights and action . Also , if you are showing cross enterprise data – should it not have search as primary interaction medium ? Also – it seemed like there were a lot of “clicks” on the touch screen when I saw the demo – instead of “touch” . I really think SAP should rethink the design from ground up

I absolutely loved the web tool to help plan S4 migrations that was presented during Hasso’s keynote . Excellent investment by SAP !

Talking about overlapping products – BI portfolio is a classic example of SAP historically resisting rationalization . This year , Steve Lucas announced they are going to categorize everything into two bundles . One for cloud self service and other for enterprise . That is a good logical move .

And they are bringing back “BusinessObjects” brand in a big way! I thought it was a bit odd to double down on BOBJ brand to fight the likes of tableau – but we will see how that plays out in the market . Irrespective of branding , I hope these two buckets are a good start in streamlining the portfolio . Success can be declared when in future we don’t see sold out sessions on “how to pick the best SAP BI tool” at events like sapphire 🙂

I miserably failed in my quest to visit every single booth on the show floor this year . I visited 12 on Tuesday , 8 on Wednesday and 2 on Thursday . I was not exactly thrilled with what I saw in the 20 that I did manage to visit . Way too many power points , and the few demos that were there – it was mostly about dashboards . Clearly SAP’s design thinking philosophy hasn’t yet caught up with several partners .

Many thanks to SAP for having me – it was great to be back here after a gap of few years !