Executive Interview: The Future According to Microsoft Cloud Visionary Mike Opal

So how will this happen?  Mike Opal likens what we are seeing in the world of information technology  to The Perfect Storm, the 1991 "No Name" storm in which the convergence of several weather events unleashed 30 foot walls of sea water and hurricane force winds on unsuspecting fishermen and inhabitants of the New England coast.  Sebastian Junger's book The Perfect Storm outlines the monster's origins while he tells the story, later a movie starring George Clooney and Mark Wahlberg,  of the crew of the Andrea Gail, the Gloucester fishing boat lost with all hands on George's Bank.

It's beyond Moore's Law, because the multiplication of devices - tablets, computers, phablets, Smart phones and sensors, is generating data faster than most humans or companies can assimilate and act upon it, even with good exception reporting.  This is not a task that fits well in spreadsheets or the average legacy MRP system.  Rather, warns Opal, the storm of data - and its detritus - currently exceeds our data storage

and manipulation capabilities.  Here's why:  

In 2003 there were 10 human beings for every connected device.  "And," says Opal, " in terms of devices, we'll have 50B by 2020 and data will go from .8 ZB in 2009 to 35 ZB in 2020 -  that is insane (Note:  1 Zetabyte = 1B Terabytes); the .08 ZB in 2009 is ALL OF THE DATA CREATED BY MANKIND SINCE THE FIRST WRITTEN WORD and that will increase 44x by 2020."  Certainly more than computer pioneers Ken Olsen and Gordon Moore envisioned, although Steve Jobs knew - and directed - where we are headed.  "I really think it's the challenge of our time."  With the devices and the data growing, well... exponentially,  the data generators are getting more personal - in our clothing, our cars, our appliances.  We've got refrigerators that tell us when we need milk; we've even got devices monitoring bovine nutrition farther up the food chain!

So that data is here, but The Cloud is Everywhere... And what do we do with it?  For manufacturing Opal sees big changes ahead - "The converging and explosive forces of Devices, Data and Cloud are altering our long accepted business models - with Additive Manufacturing the 4th Manufacturing Revolution is upon us and those who fail to establish what makes them special and then build their business around it will be left behind, they will quickly become the next generation of abandoned New England Mills." 

 Opal cites Microsoft's eight cloud data centers, with another 20 under construction at a cost of $500M each to build.  Companies will find no shortage of consumer and marketplace data.  Opal leaves us with the challenge of mining the bits and trends to answer what he believes is the key - and only - question:

                                                                         WHAT MAKES YOU SO SPECIAL?

Dorian Shainin, Shewhart Award winner and Rath and Strong statistics guru pounded into us, "Let the data lead you."  What Dorian was telling us was to first gather the data, and then sit with it, live with it, get a sense of what it's trying to tell you.  Look for the outliers, the exceptions that just might highlight a special trend, an unknown event or requirement, or just a  bleep. 

Then look at The Pumpkin Field.  It seems that Opal's son on Halloween weekend walked into a two-acre pumpkin field.  "So ahead," said his Mom, "pick one... pick a good one."  The boy looked over the field - there were bright orange perfect pumpkins, there were small baby pumpkins, there were orange gourd-shaped pumpkins, and pumpkins hidden by leaves and vines.  There were tiny yellow pumpkin buds hoping to grow up before the frost came, and there were some smashed and half rotting pumpkins being gored by crows.  But the boy walked directly and purposefully through the field of thousands of pumpkins, stopped and picked up the one perfect pumpkin because he knew which pumpkin he wanted - he wanted the perfect pumpkin, the one whose shape and color and skin was ... well, perfect.  His perfect pumpkin was yellowish - not orange - and it bore a scaly black wart on one side, and it wasn't perfectly round, or big enough for a Jack-o-Lantern.  But to the boy, this was The Perfect Pumpkin.

Do you know what makes you so special?  Do you know why you lost those last four deals, and what you could have done to recapture those customers?  Do you think it's being the lowest price in the Mall?  Or is there something else - is there something out there in the field that calls to your customers, that makes them pick your product, your idea, out of the all the low-cost offerings out there on the web?  Are you The Perfect Pumpkin? 

Banking regulations lead IT development, but unlike ISO, Baldrige, Shingo and other manufacturing awards, financial institutions are bound by various regulations governing data management.  And that, according to Opal, has made all the difference.  “For instance, six or seven years go in the global banking market we had Basel II, a regulatory attempt to better understand the banks customer positions and safeguard  adequate cash reserves, Ultimately Basel II wasn’t fully enacted  so Basel III is coming and will attempt to learn from the financial crisis of 2008.”  

One important objective of Basel II that carries on to Basel III is the requirement  to develop a 360 view of every customer.  “An  important mandate of Basel II was intended to eliminate all the separate silos of data that had grown in banks and  allow managers to fully understand the risk associated with the financial system.  The solution was to bring all the data together.  It was an enormous technology challenge -  many large consulting firms  made a fortune by proposing to build a single data warehouse that would hold it all in one spot where managers would have a 360 degree view, and where they could slice and dice and market and message to customers.  “It didn’t work out,” recalls Opal – “because of the  complexity of moving all data bases, disparate systems, etc.  Banks that had completed big acquisitions would have multiple silos so the challenge of getting one data warehouse was ultimately too immense. Fortunes were spent.  The idea of not being Basel II-compliant brought unlimited mandates from CEOs.  ‘Do whatever it costs,’ they said.  And they did!”

One Boston banking giant spent $21M, 11/2 years on their first ECN, with no mandated completion in sight.  Naturally, the consulting firms were only to happy to help.

Understand – it’s a fact - the data is bad. 

In manufacturing, “the forecast is always bad,” but in banking, one wonders, how can a bank not know exactly what its positions are at any given time?  But remember, in the consumer trading environment, when a trade is transacted in half a click– a security is sold – versus when it is settled in 1 – 3 days, there is a gap.  It takes several days for all the associated paper to catch up with the on-line transaction.  Think about the currency and price shifts that could take place during that 1 – 3 day window and its clear why aggregating the financials is, as Opal says, “problematic.”

Given all these limitations – the difficulty of capturing layer upon layer of snapshots from the financial databases, the problems of multiple disparate database integration, human factors and

geopolitical differences, it is any wonder that Basel II’s well-intentioned policies ran afoul of technology limits?    

If not warehouses, then what?  “The current solution is not data warehouses – it’s too complicated and there is too much risk in trying to rip out what we currently have and replace with something new  What if something bad happens?” warns Opal. “The new thought is wrappers – that’s right, wrappers built around disparate systems. The current solution  is a wrapper that connects to multiple data silos while not interfering with any of them.  It’s the wrapper that gently pulls off data as needed.  I call it intelligent data mining!”

Lessons from Retail 

Opal uses a Target retail illustration that clarifies this approach to data capture, mining and analysis and illustrates what is possible in world of analytics and data.  “Target,” he says, “has a phenomenal organization with tremendous information on customers.  The company has extended its reach with on-line stores and messaging that allows marketers to see where the consumer lives, whether he acted on an offer, but no more than a good manufacturing operation or a bank should know about its customer...”

Here is where things get interesting.  Sure, every click is another bit of information for retailers, “but,” says Opal, “apparently in retail patterns don’t change much.  We’re pretty boring!”   The challenge to retail growth is to understand when people come out of their routines to launch a new buying pattern.

Target’s research uncovered critical data patterns indicating three points when consumers open to a new pattern:

1.    When they move

2.    When they divorce

3.    The birth of a child, the most dramatic and risky milestone when many consumers move on and never return.

It’s interesting to note that even in cases of a move or divorce we try to return to our prior buying habits if possible, so it is the birth of a child that Target wanted to focus on.

Although Target wants to be there at the shift, their research proved that being in the delivery room was already too late – the expectant parents would have already furnished a nest and registered their gift preferences with Babies R Us, for example, at which point Target has lost an entire family of consumers – for life.  The solution?  More lead-time! 

Target planners knew that meant they needed to message women, almost, in fact, the moment when they become pregnant!  The databases, however, are deep and rich enough to identify what we buy and when.  With the baby due date, within two weeks of actual birth date, they can back up nine months to understand what was this consumer buying at that particular point.  They’re looking for a tip-off to guide future campaigns directed toward women. 

Shewhart Award winner Dorian Shainin always said, “Let the data lead you,” and Target was no different following their leads.  And what the data told them is that pregnant women buy unscented hand lotion.  Bingo, that data triggered Target offers around babies and children. After the unscented hand lotion, women will buy different nutritional supplements.

Bam, a sixteen-year old woman in Target’s data base bought unscented hand lotion. Weeks later her dad discovered an email offering directed toward pregnant consumers.  Dad is naturally outraged, flies down to the local Target demanding to see the store manager, “this is unethical, you’re sending this kind of stuff to a high school girl, etc. etc. “  After apologizing in store the store manager followed up with the father three days later.  When he called he began buy apologizing again but he was met with silence.  Finally the father said “I’ve actually been thinking about calling you to apologize, it turns out my daughter is pregnant.”  The system was right, the high schooler was pregnant -- proof that intelligent data mining has arrived.

Although there may be many lessons in this illustration, for retailers and manufacturing operations the big lesson is to get ahead of the data, to mine it, look for patterns, analyze the event, and then create tools to make the trigger event actionable.  In Target’s example, the goal was to get ahead of the father, and if possible ahead of the woman as soon as she bought the trigger, unscented hand lotion.  Systems that wait for the second trigger – vitamins – are too late for the kind of lock-in retailers want. The same lesson applies to manufacturing operations looking to be more sensitive to demand changes.  In fact, in our upcoming piece on a powerful data mining and analysis tool used by electronics, automotive, and pharmaceutical producers to understand demand patterns, we will show how ready manufacturers are for this type of powerful assist.

For both manufacturing and financial services the very powerful tools now available appear to offer sharp contrast to the way information was traditionally gathered and captured in our “old school” institutions.  Take your old hometown bank, for example. 

In the central Massachusetts mill town where I grew up, the bank manager of Nashua Five Cent Savings was a VIP whom everyone in town knew.  Mr. Pillsbury knew everyone’s employment status.  My parents cashed their checks at his bank; they financed a car through the Nashua Five and after our move to a bigger home, they made monthly mortgage payments at the teller’s window.  Mr. Pillsbury knew his customer base well enough to not make the right offer at the wrong time; he was up-to-date on life events and watched for firsts that would continue to consolidate his bank’s relationship with a growing family. 

But if you were to ask the name of the bank manager at the most popular bank in my hometown now, I could not answer.  The consolidations and acquisitions and branch downsizing have eliminated most of the human contact that sustained the community.  The biggest bank I know is Bank of America and the accepted judgment around town is “We hate Bank of America.  Hate them.”  In fact if they opened a drive up window we’d still drive to Lowell for an alternative, a small credit union even – anything to get out from under the burden of Bank of America’s onerous lending and credit card policies. 

There is a difference, at least in the consumer’s mind, between “helping” and “selling,” a distinction that the big consolidated consumer institutions have conveniently forgotten.  But remember, if Target had treated its customers the way some banks manhandle consumers today, they would have gone the way of Bradlees – great at low prices, but not very clear on exactly what people wanted and were projected to need throughout their buying lives. 

Opal believes that big banks need to learn more about how consumers buy.  If any sane comments could be taken from the Occupy movement, one of them would be how uniformly people have come to hate banks.  But the tools for a turnaround are at their fingertips.  “Honestly,” observes Opal, “banks can use the data they have and start messaging, just like Target, selling consumers the right thing at the right time.  Think about it!  Banks would cease to be pariahs!  People would love them again!  And it would be best for the financial future of everyone, because banks are like the town square, uniquely positioned to understand the life milestones, needs of their community and help guide them through the complex financial system to get to the unique financial future each of us wants to get our family to

The Cloud – Good, Bad, Scary?

We asked Mr. Opal to comment on where he sees Cloud vs. local strategies going given the clear parallels in manufacturing and supply chain between financial services operations.  Just as we suspected, he confirmed that “people get very hung up on the so-called security aspect.  It’s an emotional, a gut reaction.”

There are enormous costs associated with maintaining and upgrading traditional IT.  “The other cost,” says Opal, “is the cost of NOT being a flexible agile business.  If a company wants to ramp up the traditional way, they’ll have to buy hardware and software, install it, beta test, etc., etc.  The time required is immense, but The Cloud is instantaneous.  There is no question that we are all going to get there - it’s going to happen.”

Microsoft walks its own talk.  With everything on The Cloud, the company has already done done a lot of thinking about security.  Their product is the code they create, and we know that pretty much any IP can be stolen.  But for Microsoft to become a cloud company given the way they use the Cloud internally, they had to rethink how they protect and access information.  What they came up with changes the way consumers work with their own data.

When people think cloud security now, they defer to their at work or mobile interface.  But for many workers the line between inside the office and out on the road is no longer a hard distinction that doesn’t reflect the way people will work in five years because the workforce is infinitely more mobile.

“Let me give you an example,” says Opal.  “I use my mobile device as an alarm clock.  When it goes off, I roll over and scroll through emails, and I decide right now what to respond to.  Europe is already ramped up, so I’ll probably respond to a couple messages before I get out of bed.  Then I’m off to the train or my car, or my home office.  The old approach of relying on a firewall won’t work anymore, because I’m everywhere.  The firewall is an outdated mindset like the locked drawer or the locked door of an office.  But the way Microsoft handles security, it’s about access. 

Microsoft protects data two ways – the sensitivity of data and the way it arrives.  Information is classified into three levels – high, medium and low business impact. Microsoft sorts all IP, including email, this way.  “We can read the very highest level information, but our security system might, for instance, block that same critical information from being forwarded.  And in fact the Microsoft system, which “knows” which devices are engaged, specifies which devices are authorized to read different types of messages.  Rather than thinking firewalls and locked drawers and boarded windows, the company uses a smarter system that recognizes levels of access for devices, users and information type.  This approach,” says Opal, “is much more geared for mobility, in fact it leverages the mobile device to create a layered and more secure system “

Cloud Adoption in Manufacturing and Supply Chain

Manufacturers may find added cost savings in The Cloud.  For low business impact information that they may find more expensive to store and maintain, such as expense reports, it’s a no