Digital Transformation, revisited !

I don’t like the term “digital transformation” all that much – and it is no big secret . My views are fairly public on why the term is misleading . That said , the term is indeed very popular and I get asked frequently about critical success factors as they apply to digital transformation . 

My view – simply put – is that it is more about managing transformation (as in change) , and less about digital (as in technology). 

I routinely talk to leaders at my clients who proudly tell me that they have started a Hadoop initiative or IOT project to kick start their digital transformation . I share their enthusiasm – mostly because I know how difficult it is to find budget for new initiatives at many of these companies . But I also know from experience that this is only a very small first step .
I put forward a simple three question framework to get to a common understanding of whether a transformation initiative has a chance to succeed 

1. Are we solving the right problem ? Or are we solving a random problem the best way we possibly can ?

Here is an example from recent experience . Data scientists and Hadoop experts created an amazing “churn analysis” model for a business . Customer loved it – but that project never went very far . Why ? Simply because this customer already had the lowest churn in their peer group of companies . This was not the right problem for the top management to worry about . All that happened was that we found an optimum solution to something that they didn’t really care about . 

2. Why should users switch to a new solution now ?

The CEO or CIO might see the tremendous value in analyzing all kinds of data and deriving deep insights . But when an analyst who has a well developed process of preparing , analyzing and reporting data a certain way for ten years might not see any reason to switch to an unknown new process . 

It’s not enough that users will eventually use the new solution – they need to do it “now”. Are there incentives for them to switch fast ? Inertia kills !

3. Can the solution scale and stick around for a while ?

Not just about scaling technology – but can this solution work everywhere (or in most places ) that we do business ? And is it flexible enough to not need a full redo in near future as business evolves? A transformation should result in something that is both effective and efficient !

Of course there are a hundred other questions to ask and answer about such initiatives – but in my experience , these three will set the right expectations with all the stakeholders quickly and also set the stage for follow on explorations . Worst case , it will still save you time spent chasing the wrong things .

Where should transformation focus ?

A lot of transformation initiatives tend to focus on changing the technology and the processes , and not as much on people . This is also why most of these transformations fail, even though the original proofs of concept were declared a success . 

Example – This lack of focus on users is also the number one reason why self service reporting solutions don’t live up to their full potential is most cases – users just don’t see a reason to switch and suffer from a temporary loss of productivity . And very few leaders have the guts to switch off the legacy reports and “force” users to leap into the new world :) 

When there are two ways of doing something !

Technology and process will evolve faster and faster with time -but human beings won’t change that fast if they have a default option of sticking with what they know . This is why startups generally have an inherent advantage in shaking things up in the world compared to an established company . 

Why do more people rave about uber as opposed to say GE when it comes to transformation ? Disruption is always easier when you need to disrupt others without needing to disrupt yourself . 

It’s not as if larger companies have no chance to transform – it just is more painful . Many companies have successful incubation programs in place to nurture new ideas . Integrating the good ideas past incubation into mainstream business is where there are not as many success stories available today . That should change over time .

“You have to draw the lines” and some other thoughts

Jon Reed wrote an excellent article on work life balance and that prompted some thoughts in my mind based on my own work and life over the last two decades.

There are two simple principles in life that keep me sane when I follow them both religiously. And when I don’t follow them , it invariably screws me over 

1. We have to draw lines when it comes to how we want to lead our lives . If we don’t do that, someone else will draw it for us and we won’t always like it – in fact most times we will hate it .

2. There will always be some people smarter and luckier than us . We have to make peace with that quickly and not let it drive us nuts every day

Work life balance is just one example for this . I have a job that needs me to travel most weeks . If I don’t draw a line – I could easily be traveling every day of the week , all year , for my employer’s business . So I do draw reasonable lines and try to be home as much as I can . In the process of drawing these lines , I might lose out on some opportunities and the price to pay for that might be high. What often makes it hard is that we have to draw these lines without perfect data . But if I don’t draw that line – I won’t have a life outside work at all.

In my job, I spend a lot of time negotiating with customers, partners and my own colleagues . One of the  golden rules of negotiations is that “they will keep asking till you say no”. Saying no doesn’t come naturally to me . But if I don’t say no when required , then I can’t fairly complain when I am asked to do things that I don’t like . So I learned to say No and it helps a lot in managing my life on my terms . This is true outside work too.

Then there are the people who think being difficult is a badge of honor . In reality, it’s exactly the opposite . Being easy to work with is much harder than being difficult . If you want to be easy to work with, you need to make principled compromises on the fly . Being difficult is just an easy way to buy more time to make decisions . It slows things down and then no one will want to work with you any way. Being easy to work with comes at a high risk and it could be taken as a sign of weakness by some . But when you can combine being easy to work with AND the ability to draw lines when required , you will get somewhere you like .

I have always worked with a lot of over achievers . It is hard to not compare myself from time to time with them. There are many who are significantly more successful than me in any dimension I choose to compare – money , how fast they progressed in their career, how big is their house – or pretty much anything at all. It’s partly good fodder for motivating me to try harder , but for the most part it just made me miserable . Then I realized that there are two aspects that I am not considering 

1. They might be better at one dimension – like say they made it to executive ranks sooner than I did . But they have also paid a price for that – like sacrificing on quality time with family . Some chose to not marry or not have kids , unlike me . I wanted a family and when I add that to the framework, I no longer felt like an under achiever . 

2. There are always elements of luck, risk taking ability and intelligence that they may have that I have no control over whatsoever  . So why stress over that at all ?

This perspective is not something I have had all my life . I got it while I took a time out between my last job and my current job . It just made me realize that the only way to do a meaningful comparison is to see if I am better today than I was yesterday . Words cannot explain how peaceful I felt when I came to that conclusion . I just needed to get off the hamster wheel before I could get that clarity in my mind .

I will stop this with one last thought . If we don’t keep skills sharp , and keep learning all the time – our ability to say no will decrease at an alarming rate . And at a certain level , it might get to a stage where you cannot make peace with it . So it’s in our own best interests to stay relevant .

Social media and diminishing marginal utility

It was a cold evening in February 2008, and I was out having a beer with my boss in Beaverton, OR that the idea of starting a blog first came up. She and I had both read an article about social media in our intranet and we discussed the idea at length . We left the pub convinced that we should both start a blog and see how it goes . 

The only place I knew of people writing blogs at that time was SAP community network – SCN. The problem was that I had no interest in writing another “how to” blog , even though hundreds of them had helped me fix stuff in my own projects . I was already active reading and commenting on blogs at that time . So I thought maybe if I try to share my experiences on actual projects , maybe it will be interesting to a few people . So I started this in March 2008

That was a pleasant experience and pretty soon I joined Twitter , Facebook etc and started a personal blog here at for random topics . My social media habits have evolved over time – the latest being moving some conversations over to whatsapp – and has reached a stage where I need to evaluate if it’s worth my time to spend time on it . 

There are many plus points 

1. It is now my primary source of news . I scan all of them a few times a day to see if anything catches my eye . 

2. It helps me re-establish old friendships from school days . Even managed to find and meet buddies from primary school that I haven’t seen in 25+ years and that is invaluable 

3. It helps my work in many ways – customers know my POV when they google me , I find great candidates for open positions in my team and so on . Also gave me several friends whom I otherwise would not have met otherwise 

But it comes at a steep price in terms of time and noise and lost friendships

1. It’s hard to filter social media to just useful things unless you are on it all the time . Just when I thought I got rid of all the “let me post every famous quote” and “top ten list” people on Twitter feed , I found that I had a huge “I am smart and rest of you are idiots” set of people to deal with. Now I follow less than 200 and even that doesn’t fully help me – so I spend an hour every few weeks tweaking it . I know election season will make it an impossible task for almost a year :)

2. The onus is always on the receiver to decide what is of value and what is noise . I just need to look at the mirror to find a perfect example of noise creation on Facebook . I have friends from my professional world , friends from dog shows , family and school mates in my friend list . If I post my thoughts on software world , it is noise to my dog lover friends . If I write something about dogs , my class mates will find it weird . I don’t have the time or inclination to pick and choose who gets to see what – so I add to the problem that I am trying to solve for myself 

3. The best part of social media is people – and they are also the worst . People don’t always behave as adults in social media , especially in groups . I am right in the middle of one such group where 40 year olds act as 4 year olds throwing a tantrum . There is a cycle that repeats – handful of people with common interests come together and form a group , have a great time , pull in others , have a greater time , everyone gets comfortable and want to do greater things and solve world hunger ,  people take sides , smaller groups start, original group disintegrates – and so it goes over and over . Inevitably , the “founders” of the group are the ones who feel the pain the most . Moral : people are people , social media just provides a time lag for their true colors to show up . And when it shows up , social can help amplify the good or bad of it quite significantly 

4. Social media tries to be an equalizing force and it eventually fails . I have now seen this in three groups back to back in a short period of time . There is an assumption when people come together that everyone is an equal in a social media group . This falls apart as soon as the immediate goals are met and the group finds other goals . It sickens me to see people who were once great friends threaten and belittle each other in public for no apparent good reason . This is the biggest reason I sign off from many groups as soon as I smell trouble . I have enough stress as it is – why would I ever want to get more trouble voluntarily :)

5. In any population I have seen in social media , 80% of content comes from 20% of people . That doesn’t worry me by itself – it’s normal . What does worry me is that a sense of hero worship for some part of that 20% kicks in too over time and it always seem to end up in a mess . People without the guts or inclination to say something sometimes choose to live vicariously through the “holier than thou” gang  . This mindless support ( also funny that some of this is just sarcastic but gets interpreted as real support )  in turns strokes egos and a sense of invincibility apparently gets into the mind of some contributors . It’s all downhill from that point – apparently for me . There is no solution to this in a free world other than filtering out by people who find it unbearable . 

6. The interface between virtual and real worlds is not anywhere close to seamless . If your boss or your mom is in the same group as you are, you are limited in many cases in expressing what you really think . And the same is true about actually acting on decisions taken in the virtual world . For example – a group of us once decided on FB that we can pool some money and help people affected by a natural disaster in Kerala . A kind soul in the group who lived in Kerala offered to be the guy on the ground disbursing cash to the needy. At the end , he did it on good faith and then got questioned endlessly by others in the group . He quit in disgust and is still upset and I feel terrible that he had to go through it . The ease with which social gets us through decisions gives a false sense of how things work in real world . Thankfully there are many examples of thoughtful people using social media in useful fashion  – but the trouble they take should not be underestimated .

All things considered , I am still a big fan of social media . But I am also firmly convinced that it is less valuable than what I thought it once was . It adds enough value for me to stop using it , but I just need to filter way more aggressively and prioritize other things over social in many cases . 

Defining Hadoop with a straight face

Unlike datalake, I don’t think of Hadoop as a buzzword at all. It is a real thing – a real project you can touch and feel. Also, I love elephants (The one in the picture is an eighty year old Guruvayoor Padmanabhan, owned by a famous temple in Kerala)  – which might explain why I have a particular soft spot for Hadoop :) . Hadoop is perhaps not yet ready to be an elephant this size, but it is not such a little baby elephant as shown in the marketing pictures either.


By now, it is stable enough even for an obsolete programmer like me to play with it minimum fuss. In my day job, I don’t program any more (sadly – but probably a good thing for my team, and perhaps for the rest of humanity). But there is hardly a week that passes me without a need for explaining hadoop to someone. Even when I was between jobs and enjoying a nice vacation, I was pulled into “help me understand hadoop” discussions.

The primary problem for me personally is that the folks I usually have to explain hadoop to are not always conversant with open source. I get to talk mostly to people who are smart enterprise technologists, but who have very little idea of open source per se. Vast majority of them equate open source to free software. And it is not as if open source is a good all encompassing way to explain hadoop (hello MapR). And if I somehow manage to get these folks to understand open source and a few licensing models, I lose them again on the idea of what a distribution is and what is different between the distros. I think its mostly a mental block that there are commercial vendors who make money of software that is supposedly free – and they all do it in different ways. Can’t blame them – I had those questions too for a long time.

Once you get past open source, then there is a question of what constitutes Hadoop.

No one in my circles apparently cares about Hadoop common , so I no longer utter a word about that. And the few times I have mentioned it, mostly to friends who come from coding backgrounds – I have to deal with “why would anyone use java for building this?” :) . Hence no “common” – nothing but grief from that conversation.

Then I talk about HDFS and MapReduce . Enter more rat holes – why does the world need yet another file system – why not use GPFS? I have heard of Spark – so when do we use MapReduce and why not just use Spark all the time? If I get a breather, I also get to mention YARN and Arun’s explanation of datacentre operating system, and that there is a MapReduce2. People get why YARN is a good idea almost instantaneously. Everyone appreciates the vision of pluggability – but invariably someone will ask about its compatibility with stuff that came before YARN .

This is usually where I start with the idea of different kind of nodes, mechanics of replication, why 3 is a default value, and why the whole thing is built for commodity servers daisy chained together. You would think this is the easy part – but it is not. We are dealing with people who have spent their entire careers working on high end servers that have all kinds of resiliency. It is a really hard thing for them to visualize the world hadoop is built for. Usual starting questions include “if I just repurpose all my high end servers, can I just avoid replicating thrice?” or “I already have tooling that takes care of HA and DR in all my data centers. Surely there are APIs that I can use to connect my existing tools to this hadoop thing ?”. This is a game of how many times you get to say “it depends” in any one conversation without taking a breath.

Just when I am ready to wind down the conversation – impatient listener will ask “can you fill me in on hive, HBase etc”. Sure why not – so I explain how there are a bunch of other projects that play alongside hadoop. “Are they all java?” – well, they are not ALL java, but ideally you should not have to worry given they all have interfaces you can use relatively easy. I can see relief !

HBase seems to be a trigger for starting on the NoSQL part of this Odyssey. This is particularly so because my friends know I spent some time working at MongoDB. Sadly – as in REALLY sadly – 90% of my conversations include a part of convincing people that MongoDB is not hadoop. And at a minimum at that point I have to touch on Cassandra to explain there are more NoSQL options out there. Invariably this opens up the question of “does MongoDB work with Hadoop” – thankfully it does and I explain the connector. It also usually leads to my friends from ops background sigh aloud “can’t we just use a general purpose database that does all these things” ? . I no longer fight them on this topic – mostly for lack of energy.

“So you have explained how data sits in hadoop, but you have not explained how I can put it in there or how I get these awesome insights from that data”. Ah I forgot all about that. So I go on to explain even more projects ( at some point it is overwhelming to remember all the names and the right spellings ) – and also manage to get in a plug that a lot of closed source tools can access hadoop. This is usually the point at which my ops friends give up on me and say “good Lord,  it is complicated to manage all this” and my dev friends get all excited that there are so many cool new toys to play with.

Usually the final question is on security. On the bright side, Ranger and Sentry are both easy names to remember. On the not too bright side – I don’t want ( or even know fully well enough) to explain why two major distros have two different approaches. And this usually leads to other examples like impala to show that not all distros share the same implementation philosophy. I should use something other than impala in future as my example – since that goes into “how many possible ways can you do SQL on hadoop?”. My usual temptation is to say “more ways than enough for you to get a costco size jar of aspirin” :)

I have not counted, but there are certainly more than 30 projects that can somehow be called a part of hadoop. I have personally played with less than half of them. And every day more projects are starting and it is getting hard to keep up. No wonder why my friends/customers/random people all get stressed out trying to understand hadoop and how to make use of it. And yet – everyone is excited about their hadoop journey, despite all its twists and turns. Marketers like my friend Ingrid who recently joined HortonWorks as CMO should have a fun time articulating a message that makes it much simpler to understand.

Alright, so who wants to ask me about Hadoop next ?

Before you take a dip in a data lake

We all love our jargon and buzzwords, don’t we ? Off late, I get pulled into a lot of discussions on “data lakes”. People are either huge fans of the the data lake approach, or they are super negative. And that is what makes these discussions a lot of fun.

I did a google search on what exactly is a data lake and got this as the number one hit. A data lake is a storage repository that holds a vast amount of raw data in its native format until it is needed. If we stick to this definition (which I like), it also makes it easy to understand the tradeoffs of this approach.

The major benefit of this approach is that you reduce upfront costs associated transformation. Instead of ETL (extract-transform-load), we just extract and load, and leave transform for some other time. On the bright side with a data lake we can cross our hearts and honestly say “no more silos of data” and “one repository to rule them all” . This has its advantages – better deals on HW and SW costs and potential some breathing space to stagger analytics projects to make use of this data.

The whole reason for dumping all data into data lake is to analyze it at some point. For analysis, we need to know the meaning of the data that we are trying to crunch. When we try to do analysis at some point in time – we in all probability cannot make sense of what the data is anymore. Even in the tightly controlled world of datawarehouses, we spend a lot of time in rework when a new data source is introduced . We run to the people who manage the source systems and try to establish rules and governance and so on so that there is less error in steady state and data can be meaningfully combined.

So while data lakes are definitely serving a good purpose – there is an aspect of dealing with the “kicking the can down the road” that often comes with it. A data lake that is meant to prevent data silos, could just end up enabling silos at scale when there is no governance around it. This is the part of the message that marketing peeps usually don’t say out loud. Perhaps the reason they don’t say it is because once governance is established, data lakes might look very similar to the now uncool data warehouses – maybe not physically, but certainly logically.

Data lakes are quite useful as long as the expectations are correctly set. I would not shy away from it. Just keep the expectations real on the trade offs. I was joking with someone that all the fans of data lakes should be made to work in a data curation project for some time on a mandatory basis. That will give them a much more balanced perspective !

This is my second attempt at writing this blog. My (much longer) last trial yesterday night had to be deleted :)

Customer references and strategic relationships 

I had an interesting discussion with two friends on Twitter yesterday – Frank Scavo who is a well respected analyst and has advised a lot of customers on buying enterprise software and services , and Ben Haines who used to be the CIO of Box and who is now a VP at Yahoo . The topic was about customer references . I thought I will jot down my (strictly personal) views on this matter.

There is nothing more valuable for a vendor than having a customer who is willing to act as a reference to other customers and prospects.  Nothing puts a prospect at ease about a vendor like another customer who can vouch for the vendor. Customer references are also invaluable in securing favorable analyst reports for the vendor. 

References are very important for the customer too. Vendors will typically paint as bright and rosy a picture as possible to make the customer buy . It is by asking around other customers that a prospect typically gets a full picture . In most cases they just directly ask the vendor for the reference . As a seller and then as a sales leader in my career , I have been asked a zillion times to arrange such reference calls . I am greatly indebted to the customers who have provided such references.

There is a strange irony from this point forward in the story . Many customers who absolutely insist on reference calls are themselves not comfortable to be a reference for the vendors whose products and services they have successfully implemented . The most common excuse I have heard is the generic “it’s against company policy”. These same customers also often lament that their vendors have a very transactional relationship with them and doesn’t take the relationship to strategic levels . 

I am all for hard negotiations upfront . Haggle on price , payment terms , indemnity , dress code or whatever it is that both sides need to agree . But I always request my customers one thing – let’s agree on success criteria and a way to measure it . And let’s put it in the contract that if the success criteria are met – then please be ready to be a reference for a few prospects . As both Frank and Ben correctly pointed out – This is also the first clause in the contract that some CIOs and procurement folks ask me to remove . Their typical response is “we are happy to be a reference , but don’t want it in the contract”. Strangely enough I have not had a single business buyer EVER push back on me on this clause . Not one ! 

I trust my customers . If I don’t trust them , I won’t do business with them . And I earn their trust . So I am almost always sure that a customer who promises to be a reference will typically not decline at the end . But on the other hand I have been in this line of work long enough to know that people change jobs and roles . I also know that if I put it in contract , then any legal issues etc will surface upfront and get resolved one way or other . In many cases the person I am dealing with might not have the right authority to be a reference . In short – it gives me a chance to mitigate “not in policy” risk upfront . It also saves a lot of embarrassment for the customer Employees who find out after the project is over that they can’t keep their word to me . 

What does a strategic relationship mean between vendors and customers ? We both help each other to further our businesses beyond the transaction we have contracted for . As an example , I have many a times helped customers by providing them access to experts in other domains or markets that they need help with . And many customers have helped me win business elsewhere by being a solid references. If all we care about is price and budget and scope – then that is all we will get at the end . That is a fine way of doing business in some cases – but then the expectation should be appropriately set on both sides that there is no strategic nature to this relationship . 

So what is my success rate at getting referrals ? I would say maybe 30 to 40 percent at best . But I am hopeful that I can double the rate at some point . Life in enterprise software is not worth living for transactional relationships – at least for me .

Spreadsheet slaying is futile in enterprises

It would not be the first time that a friendly banter with my pal Dennis Howlett leads me to post a blog. This time it is about spreadsheets . I have a (not so) slightly difference of opinion with Den on the topic of use of spreadsheets in enterprises . The short version is Den thinks spreadsheets are evil, and I don’t :) OK that is dramatizing it a bit…but here is my (strictly personal) defense of spreadsheets for whatever little it is worth

1. If past performance is indicative, spreadsheets will thrive

Spreadsheets provided continuity for business users from early 80s till now. In this time frame, a lot of BI and EPM tools came and went away. Lotus 123 faded out, but its users just moved on to MS Excel . I don’t see this changing in near future either. Today there are more BI and EPM tools than ever before – and all the more reason for FP&A types to hold excel near to their chest to resist change.

2. BI and EPM companies use excel internally – a lot !

I know – I have worked in some of those companies, and partnered closely with others. They all use excel for BI and EPM alongside their own tools. They all market their wares as “excel killers” when it suits them – but can’t seem to convince their own planners and analysts to let go of excel.

The smart vendors all integrate excel into their products. Despite marketing hype they create, they all know that the product management rationale is solid that excel won’t go away, and recreating excel functionality elsewhere is not a good use of resources.

3. Analysts and Executives use Excel all the time too !

Not naming names – but every analyst I know who cover BI and EPM have excel on their laptops, and have an assortment of files with complex versioning schemes via naming conventions. The more modern ones use google docs instead of excel – but that is not exactly too different.

Similarly I have often seen data loaded in spreadsheets used by vendor executives in their demos . They just don’t say the backend is excel ! I am not saying this is what everyone does – just that I have seen it multiple times. I don’t blame the execs either – rarely do they know what happens behind the scenes of the demos they have on their iPads :)

What is the most common data source used by the new generation BI tools ? Excel ! People dump data from other systems to excel , add formulas etc, and put a nice visualization on top via the slick BI tool. Just that they don’t talk about excel in the scenario explicitly.

4. Convenience trumps functionality almost always – except for legal reasons.

World changes faster than BI and EPM tools can keep up with. The ability to change formulas on the fly and and rows and columns means that analysts can keep up with the changing world without waiting for the tool vendors to catchup. The only time they stick with tools 100% is if there are legal reasons to do so – like final copies of financial documents that need to be kept in a proper system of record.

I know top reference customers of pretty much every EPM vendor I know of that do plenty of work offline in excel and just upload the final copy to the tool for safe keeping. Or, they will do high level planning in the tool and then do finer details in excel. For example – they might allocate expenses to the head of a department and then let her manage it offline as long as she does not shoot over budget. How does she do it ? she uses excel !.

Den asked me if enterprises will use manual invoice processing if they have ERP. I have implemented SAP in a lot of Fortune 500 customers – and every single one of them have had a mass upload of invoices from excel !

5. Licenses, maintenance and training favors excel 

Even if someone creates a magic tool that does everything – it is still hard to beat excel . Why ? because excel is a general purpose tool needs very little additional training , and it does not need constant network uptime for usage across the company.  The incremental cost of keeping it running over time may not “appear” to be that high. True cost might be high – but as with everything else in enterprise land – perception is reality.

6. Does that mean all is good with excel and you should not use EPM and BI tools ?

No – Excel can, and does, cause grief in a lot of companies every year. A cursory internet search will provide you several horror stories. What the internet won’t tell you is that vast majority of the time, spreadsheets are a life saver in enterprises. But then, good news has no value in press . If my house gets water damage just once in 30 years , would anyone write an article called “House has not had single issue with water damage in 29 years and 11 months” ?

The goodness of spreadsheet is only apparent by first hand observation of its users. This is the same kind of shit that happens with ERP too . How many “ERP is dead” articles have we read ? And how many companies actually took out their ERP ?

When you see customers who say “we have displaced excel” , at best it means one department for one use case has been using a new tool instead of excel . What would be great to know is if there are entire companies who have completely gotten rid of spreadsheets as a BI, EPM and ETL tool. I have not seen any in the nearly twenty years I have spent in this field.

The smart thing in my opinion is to find the best co-existence strategy for excel and all the other tools. Spreadsheets are invaluable when used reasonably – please just don’t paint it evil with broad strokes.

That is it . Defense rests, your honor !