And Vijay Says…

But for facebook and whatsapp, I would not have had a chance to reconnect with so many of my old friends from school and college times. Nothing beats the fun of recollecting and virtually reliving “good old days” . I religiously check whatsapp for messages from both my school and my engineering college days. Sadly, the group we have for our Business school class mates never became active. Its a lot of fun to be a teenager again in virtual world – and prove that the kid in us has not died .

When we run out of topics, the more “adult” topics come up for discussion. We move from teenagers to 40 year olds in a hurry and a fairly homogeneous group shifts gear to being heterogeneous . And while good debates do happen , common ground is seldom to be found. Good thing is that the worst that will happen is that we take a time out and then go back to teenage times where it is all fun and light hearted.

I often compare this to the alumni meetings that my dad goes to – and many that I have attended with my wife and daughter as guests. The bond they have amongst their friends need to be seen to be believed . 100% respect for each other, hardly a topic where they disagree, accomplishes a lot and every one has fun – including their families. Granted they have had 30 years more time to get to this state – but is that all there is ? I think there is another factor at play – their interaction is via phone, physical meetings and the most advanced amongst them email each other. They don’t meet virtually 15 times a day on whatsapp !

The irony is that my dad and his buddies have told me a hundred times how much they envy my generation for being so tech savvy. They believe we are better off with all the technology we have access to and that they too wish they were as hyper connected as we are. And here I am thinking that they are the blessed ones with just enough technology .

The general tendency in any online community is that 80% of conversation is between 20% of members. Rest are silent readers who won’t say a word in public – for whatever reason. Some of those who remain silent – they do privately mention their opinions to one of the vocal ones. So the 20% who are vocal , they occasionally think they voice the opinion of several others. This is a slippery slope – because a lot of nuances of individual opinions get lost when aggregated. The end result is that strong disagreements happen and feelings get hurt.

In theory, social media is a great equalizer. After school. we have all charted our own ways. And when we meet in virtual world – we are equals . But we are also grown up men who have our own insecurities. The mix of physical world with virtual is like oil and water in many cases and that is kind of sad. It cannot be denied – we are all individuals and have different tolerance thresholds.

One benefit of having instant access to friends from every corner of the world is the ease of organizing in-person meetings . I have been part of a handful of those meetings and loved every minute . But of course not every one can make those meetings. So then the information from those meetings flows back to the virtual world via second and third hand accounts and there we go on yet another slippery slope that lead to hurt feelings, time outs and resets.

This makes me wonder what is the best purpose of reuniting old friends ? Is it just for fun of reliving old times ? Should it be doing something in terms of “pay it forward” , like scholarships, charity etc ? Is it to improve the institution that is the common ground for all of us to be friends in the first place ?

There are no easy answers. If it is for fun – on the good side, every one has common ground. On the flip side people run out of topics after initial excitement and the group dies a natural death .

What about “pay it forward” ? On the good side, it is a good cause and some common ground can be found in principle.  On the flip side – there are many ways to do it and not everyone agrees on best way in practice. There is also a question on who funds and who executes. Given how global the world is – the ability to contribute money varies from the ability to execute something with the money collected. This is the “adult” world and there it is common to run into differences unlike the “fun” world where everyone is a school kid again.

Should it be broad based or focused narrowly ?  When it comes to “adult” topics, I think broad based is the only realistic option. If there is only goal- obviously there is a chance for a binary split in any group of grown ups, and being virtual does not make it easy to resolve.  But a broad agenda has the chance that we learn to prioritize, have some healthy tension and everyone sacrifices a little for common good. It is only a hypothesis – I haven’t the slightest idea whether it will work .

Lets just say – social media giveth, and social media taketh away 🙂

 

 

 

 

I firmly believe the future of consulting is all about outcomes based work. In principle, this is easy to understand and there are several examples of projects where this has been successful. A welcome change in these contracts is that the actual paperwork is significantly lighter than the paper monsters we have all dealt with in the past.

In its most “unsexy” extreme – think of a maintenance contract. Customer wants a certain number of trouble tickets every year for a certain amount of money from an outsourcer. Whether the vendor solves it by automation, by offshoring or by whatever means should not matter to the customer as long as the SLA is met . Simple as it gets on paper – but it is not simple in practice.

The CIO who signed the contract gets it. But the order entry clerk whose printer stops working can no longer walk over to end of the hall and find Joe, the printer guy, to fix it. He needs to raise a ticket and wait for 4 hours to get it fixed. Result “our vendor sucks”, low NPS scores , CIO getting all kinds of hate mail and so on. Experts on twitter will say “Big Outsourcer screws over customer with poor service”.

Lets also look at the “sexy” extreme – think of a business KPI like inventory turns as the metric that defines the outcome. A baseline is made today and vendor pays a penalty when turns decrease, and vendor gets a share of the gain when turns increase. Sounds like a fair deal on paper. What can go wrong when both parties share risk and return ?

End of the year customer and vendor are sitting together to compute turns and voila – turns increased by 20% and according to contract the customer needs to pay a lot of money now to the vendor.

Scenario 1 – was all 20% of the goodness due to the Vendor’s work ? What was the contribution of the new store manager Jane who introduced more discipline in the warehouse? .

Scenario 2 – ok ok, so it was all due to the vendor’s good work. But there were so many returns . So the customer did not really get the business benefits. What now ?

Lets also flip this situation and say turns decreased by 30%. Customer wants a big fat check as penalty.

Scenario 1 – well you fired all the experienced managers and hired cheaper inexperienced folks. What did you expect? But for the vendor, turns would have been 70% lower instead of 30%.

Scenario 2 – This would have worked like a charm, except for the flood in India causing disruption. You never signed up for the extra location we begged you to sign for just a little more money.

You get the drift – this gets complex in a hurry on both extremes, and results in all kinds of unpleasantness. What was done to move away from rewarding effort and complexity to rewarding outcomes and simplicity just did not pan out.

Is there a way out ? Of course there is a way out. That needs each side to have some trust in each other to begin with . It also needs these contracts to be in place for a long period of time to make sure that both sides get a fair shake. Contracts need to stop being about “average price per hour” to benchmarks that measure outcomes across the industry. And this needs a lot of “change management” initiative to set and reinforce the right expectations. The order entry clerk needs to know that his performance metrics should be adjusted to reflect the fact that a broken printer takes four hours to fix now – he should not be punished for a decision he did not take.

I can say first hand that this works quite well when you find the right sponsors on both sides of the table. But it is anything but the “walk in the park” that it looks like from the outside.

 

 

There isn’t a company out there that doesn’t want to see a full view of customers across all channels . I have done large and small implementations of those in a variety of technologies . Several ISVs – Hadoop companies , NoSQL companies and traditional data warehousing companies – have all built big chunks of their businesses on the idea of Customer 360 . 

For structured data and with sources that don’t change a lot , doing a 360 view in a traditional data warehouse is adequate and in fact has significant performance and maintenance advantages . As data becomes more and more multi-structured and prone to frequent change , a NoSQL database starts to become a great choice . When large datasets come into play in these situations – especially on the multi structured side , Hadoop has advantages . 

There are trade offs too – everything that works with standard tooling (BI, administration , ETL) etc don’t work in NoSQL and Hadoop the same way as it does in relational systems . The licensing models have a big impact on decisions too . And while interoperability is much better today – it is not yet at a level that relational, NoSQL and Hadoop all work together happily . I am sure it will get there in some time – but not today or tomorrow .

That is just the back end story – the data management side – where decisions are made on the 3V model . The 3V model is splendid , but it is not sufficient once we look beyond the data management side towards the insights side of the equation . There I think of two other Vs – Veracity and Value of the data . 

The universal truth about data – especially big data – is that it is usually not clean . For insights to come out of that data – we need more tools to cleanse and govern . And then for getting value we need to rely on BI tools . If you think the job of a data scientist is sexy – you haven’t been in their shoes . Vast majority of real data scientists spend most of their time cleansing and rearranging data before they can model scenarios effectively . It’s grunt work and mostly not fun . There are great tools which can do cleansing and help with some governance – but it’s an uphill battle 

On the value side – there are many different types of BI tools depending on what you want to do with the data . For the most part , these tools need a human user to define what needs to be reported on . Various things like massively parallel processing across multiple cores , cheaper memory , more push down of functionality to databases all have helped tools become more efficient . A whole category of visualization vendors have made BI pretty exciting too . 

So between all the data management and BI options – we can already have a pretty good view of customer 360 today . So what is next ? 

Enter Cognitive computing !

  

Some of the existing visualization products support the idea of exploring elementary correlations of a given data set , and that is great. The idea is to have a human user then look at them , try different combinations and see what makes sense . Cognitive goes a few steps further and helps formulate questions that the average users hasn’t yet thought of asking . It can find and surface a lot more hidden relationships across data from all channels . For example – by analyzing news and social media , a customer can be flagged as a credit risk even though inhouse CRM and ERP data show them as having good credit . 

What about making sense of voice and pictures and video to enable better customer service ? What if a robot can converse with you and give you all the answers you need based on its cognitive abilities ? I am not kidding – take a look at this video of a cognitive robot dancing when it is asked to. 

Even if we discount robotics (which we really shouldn’t discount )  , Figuring out a customer’s intent via voice and facial recognition and responding based on data analysis takes customer care to a whole different level . Imagine calling your favorite cell provider with a question “when is my contract ending” and software figuring out from your tone and historical data that you have abysmal coverage in your office and hence you are a customer who will potentially churn quickly. It can also figure out that in your area there are several other customers who have the same issue . The system can then alert the field services team to fix coverage issues , as well as offer you an incentive to stay loyal to your provider . Or the system can decide that you need to talk to a human agent and transfer your call with all this intelligence to the best service rep to take care of you . That is the power of cognitive customer care. 
Responding by voice and touch is great , but it is becoming a given in modern UX. What Cognitive adds to make the UX even better is asking questions about the rationale behind the system’s decisions . You can also ask the system what confidence it has on its decision and explain to you other possible solutions . Imagine engaging in a customer chat about your phone heating up. A cognitive system can help you trouble shoot by yourself . The same system can help a service engineer trouble shoot the network and offer different solutions and the odds for each . The picture below is such a cognitive trouble shooting  and debugging app !

  
Another interesting aspect is helping trade off decisions for a customer when there are several options to choose from – like choosing a phone , the right rate plan and maintenance options .

The one last aspect to consider is about reuse of existing customer information systems . There is good news there too – Watson can query those at run time to make decisions . And if there is an API to commit a transaction in a system , Watson can trigger it too (like say update your billing plan) . Not all data needs to be physically persisted in Watson for it to work .

It’s an exciting new world of possibilities that cognitive opened for us . Plenty of customer projects are already in progress too. Let’s just say I am in geek heaven 😉