Midmarket Business and the Cloud: Reshaping the World of Business

Participated in this conference call yesterday. Reshaping the World of Business  Nicely done.  The speakers brought their experiences forward.   I followed with a number of tweet and retweets at #SMB4cloud which were spread through my network. Key benefits of Cloud to the Midmarket:  Improved efficiency, quick links to external resources and expertise, Ability to prototype and quickly develop from shared data and methods.  The authors give some excellent examples.  Hosted by former colleague: Paul Gillin. Worth listening to for anyone in the midmarket with uncertainty about the value of the cloud.

See the whole video and follow through the twitter stream, see below.

" ... IBM is hosting an intimate, virtual event via Spreecast convening a select group of about 15-20 influential leaders from the business, entrepreneur, technology, academic, business partner and developer communities to discuss how cloud can enable SMBs to build businesses from the ground up, level the playing field to compete with multi-billion dollar companies, build brand loyalty, and increase sales. Panelists include IBM GM, Midmarket Business, John Mason and Entrepreneur Samar Birwadker, the CEO and Founder of Good.co among others.

The goal of the event is to foster insight sharing, brainstorming, and engagement while stimulating provocative thinking and discussion about short and long-term opportunities for SMBs in the cloud.

Spreecast link: http://www.spreecast.com/events/cloud-reshaping-the-world-of-business
Hashtag: #SMB4cloud

Spreecast prep: http://about.spreecast.com/additionalresources/spreecast-101-for-audience/

Replay for Cloud: Reshaping the World of Business  bit.ly/1rEaB09 #smb4cloud #ibm

Full video: http://www.spreecast.com/events/cloud-reshaping-the-world-of-business  ..." 

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.

A Look at an Analytics Solutions Cloud Marketplace

The medium size business always needs help with choices.  They need easy to make choices that are as inexpensive as possible, and link directly to their current infrastructure.  That's what makes the choices less expensive and effective for them.  Analytics makes these same choices essential for making the modern business efficient.

" ... This week IBM announced a number of new offerings on the cloud, one of which being the IBM Cloud Marketplace. It was designed to be an easy access, technical shopping mall for all users (business through IT and development) to access solutions and technologies on demand. ... " 

Empowering the modern business.  Much more about that here.  I have started to look at the cloud market place.. Its a good start, but will need some additional work.  In particular a more direct link between specific problems and solutions.  That's the effectiveness part.  The small to medium size business does not have the resources required to do a great deal of tailoring of solutions.  The solution need to be quickly adaptable to their infrastructure, without large changes in what they do today.

Having a store to go to is a good start. It also includes some short explanatory pieces about the technology involved, making this store a good place to browse.  I would further suggest a glossary of terms that may also not be familiar to the browser.   Finally some broad statements of value by industries, likely via surveys, to show a company what their competitors are doing.  Giving incentive for browsing the offerings.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.  #MidsizeIBM

Is AI Changing Business?

A piece in Smart Data Collective, makes some useful points.   I think it is no longer a question.  I was actively involved the last time we rode the AI hype in the late 1980s,   We spent millions on it then, derived more millions in results, but did not get the billions that management was expecting at the time.   Once again I am following it closely, and I think there are indications that real value is starting to emerge, like in the IBM Watson effort, that the world may finally be ready for this.

One reason this is more likely to work this time around is the Big Data explosion.  More data is available in more forms than ever before.  Artificial Intelligence methods are essentially predictive analytical methods.  Our own intelligence works this way.   We have memory that we search, operate on it with our business logic, which uses pattern recognition,  and predict some future state.

We then take that prediction and envelop it some decision we want to influence.  Failures can occur at each of these steps.  We can lack the data to search,  search it poorly,  have inadequate logic or not know how to link it to the actual decisions made in the business.

My own observation was that the failures in AI work occurred for two reasons.  First, we did not have adequate or complete data to understand the process, and secondly, we did not take sufficient care to blend the results into the decision process.

We are ready to address both failures now, the data is there.  The decision process aspect needs to be solved with more care in understanding the connection between prediction and useful decision. We have all the parts to do this now lets put them together.

Am still a believer that this will be useful for any size business.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines  of a smarter planet. More here.  

Real time Cloud Retail Data Analysis

This site was recently brought to my attention.  I am currently in the process of helping a retail marketing operation better understand how well it is doing when doing promotions under varying conditions.  IBM Digital Analytics Benchmark Hub: Your source for real-time cloud-based online retail data and analysis.  As they describe it further:

IBM Digital Analytics Benchmark
View performance benchmarks for your peers and competitors to help you uncover opportunities to grow your digital marketing and web properties. ... 

In general, the small to medium size business has a more difficult time in getting the data to understand how their business is operating.   In the enterprise we had  many sources of data and expertise. In the small to medium sized firms you track your own sales, but suppose you are trying to understand how well your promotional activities are working.  What promotions should you use in the future, what are your competitors doing, what are the demographics of your buyers? All key questions to ask.  New analytics exist to measure each of this questions, and the site includes tools and articles about them.   They point me to a study:

Read the study: How Marketing is Taking Charge: Leading the Customer Experience
Learn what leading marketers are doing to differentiate themselves in a perpetually shifting omnichannel world. .... 

Which highlights the fact that we are heading toward a very multi channel world.  Also a world where it is not about which channel we use, but how many channels we use to support a purchase and even what order we use them in.

This is all about leveraging data and analytics.   In rapidly changing conditions.   Benchmarking the results against your business sector, and helping you plan for the future.

An interesting place to start.  I plan to give it a try.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.  #MidsizeIBM

Questions for the C-Suite

The earliest experiences I had with the global enterprise were working directly with the CEO.   He had built a system that ran on an early desktop, I helped with its expansion.   In that early work I learned that even back then the C-Suite cared about the direct use of computing power to help their decision making.  They also much cared about the data that would drive these systems.  There was a big gap in time before executives cared as much again.

IBM, as part of their Institute for Business Value asked a lot of executives about how they interacted with technologies. And also with each other about technology. And where they thought the opportunities and challenges existed.   This was the first attempt to study the entire C-Suite, and it was interesting to see how this fragmented with C Suite responsibilities. That had changed much since my first work with them.     ....  The scale was impressive:

" ... We now have data from more than 23,000 interviews stretching back to 2003.

Our latest study draws on input from:
Chief Executive Officers (CEOs) 884 Chief Finance Officers (CFOs) 576 Chief Human Resources Officers (CHROs) 342 Chief Information Officers (CIOs) 1,656 Chief Marketing Officers (CMOs) 524 Chief Supply Chain Officers (CSCOs) 201 ... " 

In an interesting aside, IBM's Watson AI system was used to analyze the interview data.  I look forward to hearing more about that.

It is a remarkable study.  Which also emphasizes the current opinions and their forecasts for the near future.  While it probably means most for the complexity of the large enterprise, it gives lessons to Mid Market firms as well.  In one paragraph they provide a good summary:

" ... How do you view the world?

CEOs consider technology the single most important external force shaping their organizations. Other CxOs also see it as one of the top three factors. The members of  the C-suite are likewise united in believing that an entirely new set of dynamics is emerging. 

Customers and citizens expect to be treated as individuals, which means knowing what makes each of us “tick”:  our values, beliefs, habits and quirks. That, in turn, requires much closer collaboration between organizations and  the people they serve.

Most CxOs recognize that what applies to customers  and citizens applies to employees and partners, too.  They envisage that organizational boundaries will become far more porous, enabling greater collaboration with employees and partners to accelerate innovation. They  also anticipate sourcing more of that innovation from outside. Where once an enterprise could go it alone, and  be successful doing so, it must now collaborate. .... " 

There is much detail beyond that, each using a small pie chart to indicate the changes over time.   I don't think the pies where necessary, but they were often joined by bar and time charts that indicated change that had occurred.

I attended the preview of the study, a good overview,  it would have been better to add a few case studies about C-Suite communications of data and responsibilities.   I was also surprised that little was said about funding, is it more of an issue in a world where we are automating more interactions?   How do changes in the economy change investment in digitization?   A nod to investment, which could have helped understanding how different size organizations would behave.

In particular I liked the statement about the future of these interactions:

" ... Pioneer digital-physical innovation:

The emergence of social, mobile and digital networks has played a big part in democratizing the relationship between organizations and their customers. It’s also forcing them to rethink how they work. Some 60 percent of CxOs now look to partners who will have an equal hand in creating business value (see Figure 4, foldout). And almost half are sourcing innovation from the outside .... "

Overall a good study.  provocative read.  You can get to the whole study (with registration) here.  

 Also , see their Android, IOS App: IBM IBV which covers the study and on Twitter:  @IBMIBV  I have found their stream quite interesting.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.  #MidsizeIBM

Focusing Effort with Data, Leveraging it with Analytics

In preparation now for a talk to local executives on the use of analytics in the enterprise I reviewed some of the work done with Business Sphere.   Its been some thirty years since I arrived at a global soap company, degree and government experience in hand,  to see how I could help them with improving their manufacturing and supply chain.  I finished my direct work there thirty years later, with a three year hiatus in a startup.

Analytics then was called Operations Research, and we applied the mathematics and the principles of the approach in many places.  Early on we were introduced to the concept of focus, and how systems could provide that ability at every level of the company.  One of the first examples we explored was how the top executives used computing power.  At the time it was unheard of for executives to have computers available directly to them, it was their admin people than ran their email, made sure they got the right reports, and were altered to key issues by phone call.

In those first efforts, we worked with the CEO to develop a method by which he would get information he needed for specific tasks.  We had not yet reached a world where we could organize information to make it easily and directly usable by the decision maker.  Make it as easy as possible to do their job with the right data.

Then, years later, as software and hardware became pervasive and mobile, a key extension was understood.  People work as individuals, and in multiple groups.  So why not give every person, every group, of any size, from new hire to CEO, the right data to do their job?  This gives you the advantage of doing their job, with the right data, as efficiently as possible.  It was also discovered that this would also focus their jobs in new ways.   Data can drive the work.  Analytics can be added to sculpt and leverage  the data.   The work is not done, it continues to move on under new names and implementations.  Stay tuned for new progress.

For more about this see my previous writings about what is now called Business Sphere.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.

Big Data Myths and Misconceptions

I am in the midst of preparing an executive presentation about the use of analytics for companies in our region.    Our group consists of experienced practitioners from academia and industry.  As part of our preparation we have been gathering examples from dozens of years of applications.   I have noticed something interesting, all of the people involved are avoiding the term 'Big Data'.    We all preferred to talk about the improvement of business, then about the data, big or small,  that will make that possible.   Analytics.

But you can't avoid the term, its heavily hyped.    And it makes sense.  If you are gathering huge quantities of volatile data, it makes sense to mine it to find leverage points for your business.  But you have to understand your business process first, or else you are finding solutions for problems you do not have.

The small and medium sized business has a particular dilemma.  They don't have the funding to experiment with their data.   So they have to be focused before they start.   Expensive consultants to carve through the hype is not an option.

I recently heard a 16 minute podcast by Tom Deutsch ( @TomDeutsch) , program director of big data and analytics at IBM.   He also writes in  IBM's IBM Data Mag   In this podcast he addresses recently emerging myths.

I liked his presentation, well done and nontechnical.  I like the content of the talk, and like him I am also a skeptic on hype driven claims for Big Data.   Rather than state the myths, below are the contrary facts as I would state them.

- Although much Big Data work has been on unstructured data like text, video, etc.  It can certainly be used with structured data as well.  Consider it a test bed for trying analytics ideas on any data.

- Big Data does not inherently have quality problems.  Any data must be verified to determine if it is the required quality.  Garbage in, Garbage out.

- Machine learning, often a goal of Big Data efforts, does not eliminate human bias.  Humans still select data,  implement the results of the analytics, etc.  So human bias remains.

- Machine learning does not occur in real time.  These kinds of analytics need to be iterated on, adjusted and ultimately implemented.  Its possible that the results may be implemented in real time systems, when verified.

It seems all of these hyped claims from misunderstanding marketing types.  It also stems from the term 'Big Data' itself, which has magical capabilities attached to it.  That can sell consulting,  I will state it again, if we are completely honest, we should change the term used and call it Analytics.   Analytics that can now be done more efficiently for larger and more varied kinds of data.  Driven by improvements in hardware, software and connectivity.

I further like his statement, always good advice, even when talking to big consulting companies:
"Anyone who makes assertions and is unwilling to engage in a discussion or provide evidence for what they say, is probably someone who doesn't really know what they're talking about. Be very skeptical."

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.

Interview on Big Data and Analytics for MidMarket

Friend Paul Gillin runs a Big Data Google Plus Hangout on the use of Big Data methods for Midmarket and beyond.  The 37 minute stream brings together current users of these ideas.    As a practitioner myself it has always been intriguing to see how this is now playing out at all levels of use.  In the past it was companies like Procter & Gamble and IBM, who could make these solutions work, now the possibilities have increased considerably.

The interview brings together three practitioners  of the use of analytics for improving business. Two areas of often mid market applications are discussed.  Biometric data in hospitals and marketing data to improve sales operations.

I mostly deal with is commonly called advanced analytics, so it was good to see the examples discussed here that use relatively simple, often just visual methods to get to solutions.   And emphasize the understanding of how companies make decisions.   Again I emphasize starting with the most simple methods.

Another topic discussed was how the Internet of Things is starting to create large amounts of data, in particular in health systems, and leading to big and complex data to be mined and leveraged.  In the case of hospital systems, the Internet of Things can include patients, monitors and diagnostic devices and a complex array of data types including imagery and quantitative measures.   Part of this system would be unstructured data such as text, such as doctor's observations that need to be assembled and attached to more structural data.

Once the data has been captured and simply presented  you can start to consider specific mining techniques to look for deeper points of value.  Every business has value opportunities.

In the final part emphasis is made of getting away from the need for data specialists.   Instead using tailored systems for particular industries, and then selling the analysis as a service.  Even suggesting that intelligence systems like Watson could drive the analysis,

Good piece to listen to to see what is happening in the field today that is important to the small and mid market company.  With pointers to the future.    This blog also covers the topic.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.  #MidsizeIBM

Open Innovation: Heart of Small Business

In Free Enterprise: John Mason GM of IBM's Midmarket Business writes:

" ... The drive to innovate is alive and well within the hearts of small businesses. But as most successful small business leaders know, it's not enough to have a great idea.   In fact, half of all new small businesses fail because they can't turn their promising concepts into a profitable business reality, according to the Small Business Administration. For the most part, the survival of these smaller firms relies on factors that remain unrecognized until it is too late. Markets shift, pushing customers to find new places to spend their money. Technologies shift, enabling the latest products to be offered through other channels. Even demographics shift, with one group’s position of “favorite brand” losing its appeal and seemingly overnight becoming “has-been”. ... " \

As part of my role in our innovation centers I often had to work with small businesses that had new ideas in retail.    These varied in size from very small businesses to very large. We worked with them to define, develop and deliver their new innovations in our simulated retail environments ad demonstrate them to retailers.    These innovations were delivered under the umbrella of open innovation.   One thing I saw more than and other was the need to adapt to agile environments.

In addition companies were often closer to the retail environment than we were, and had to be able to changes as their market changed.    Most of what we did was before social technologies were widely available to consumers, but the new realm of the social, mobile and local connections make this form of innovation more agile even more important.

" ... The small business often has the advantage of proximity to their customers, but this proximity also means that it may be difficult to "see the wood for the trees". Yet thanks to new social, mobile and connected technologies, there is much a small business can do to identify new areas of value in their products and services. Open innovation is fast becoming the heart and soul of a new, more dynamic small and midsized enterprise. The opportunity is greater now than ever for smaller competitors quickly to develop actionable insights, collaborate with others to turn innovative ideas into real business opportunities and be a truly disruptive force in their market ..." \

John Mason is the GM of IBM's Midmarket Business.
This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.

Going Global Faster with Cloud and Mobile

I have been in the midst of looking at how companies use mobile, focused data, cloud and ultimately analytical support.  So have developed interest in how all these elements work together.

An article by IBM Midmarket General Manager John Mason recently published “When Small Businesses Use Cloud and Mobile to Go Global” on IBM’s Smarter Planet Blog was pointed out to me.  It suggests that the Cloud and Mobile were causing company globalization at a faster rate than every before.

I knew that focusing data could speed agility, and that it was natural to deliver it with mobile solutions,  Especially when data was changing rapidly due to context or domain volatility.  Added analytics with the right cloud access can result in value added solutions.

But I had never considered that cloud and mobile would lead to faster globalization.  That was a provocative thought I had to consider.   Agility is the key.  Managers traveling into new areas, gathering new data, but constantly needing information and analytical methods to support their
needs.

I had seen an example where a retail compliance system linked images taken on site could be quickly transmitted to experts at headquarters, analyzed and questions sent back to the aisle.   In another example presentations based on demand volumes were developed by artists and shipped to people on site.  Agility and the ability to transfer analytical solutions to the field based on data from the field.   In another proposed project, construction of local buildings by contractors was checked by distant engineers.  International compliance examples are common and ache for this integration of methods.  This is agility and speed by linking distant expertise.   Available now to all sizes of businesses.

Besides the software provided, the social constructs are also invaluable.  To quickly determine the answer to key questions, local needs and communications methods.   I find this mobile agility useful when traveling even for my personal needs.  Imagine its value when focused for a business.

So I much like the idea and if we prepare for global and agile integration using cloud, mobile and analytics methods, we can progress in the right direction.    Faster and with fewer errors. I will think of  this for future applications.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.

Data Mining for the Midsize Business

In the large enterprise we constructed a number of datamining efforts that looked to classify solutions based on measurements we had gathered.   One popular technique, called Regression Tree Classification, made it easy to create and adapt decision trees based on small amounts of data.

Decision trees are very easy for management to understand.   I would often be approached with a data set that would be much smaller than the 'Big Data' being gathered today, and quickly construct a model that could be tested against future data.

We used this method against many applications.   Many other such modeling methods exist and are available in systems like R.  I am now in the midst of addressing such a datamining problem for a midsize startup.

I see in a recent IBM Midsize Insider article about how to think about setting up and utilizing a data mining program.    The piece covers the issues very broadly.  I would suggest also to include an expert consultant in data mining, at least for the first few examples.  Also, make sure to start simple and to start with problems that are likely to provide quick results.

Further, include business decision makers in the selection of the data, ensuring that it is correct, and in the use of the decision recommendations in the real world.

The article linked to above also provides a good list of application ideas that are good to examine for initial applications.   If you gather information about how you are doing your business, and seek methods that will make it operate better, take a look at data mining methods.  I often cover data mining in this blog.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.

Customer Engagement Analytics for Cultural Venues

Its all about engaging the customer.   All companies, large, small and midsize need better ways to engage with and retain  their customers.  And as the context of engagement varies over time, how they engage will have to be adapted to new customers and their needs.

I was recently sent some information from the IBM Midsize smarter commerce group that addresses exactly these issues.   How do millennials use and engage with cultural venues, typically midsize enterprises?    Two excellent examples here: The Point Defiance NY Zoo and Aquarium, and  The Colorado History Center.   In each link there are embedded videos which describe their experiences using big data.  These examples are also good general useful case studies of the general use of data mining of experience in data.    Recall also the example  I wrote  about the Cincinnati Zoo.  Above an infographic expressing the relationship beween Big Data and Cultural Venues for Millennials.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.

Cincinnati Zoo is a MidMarket Engine

In an interesting development our local Cincinnati Zoo has been declared IBM midmarket engine of  the week.   I have been there many times, its a haven for things zoological and also botanical.  Both interests of mine.  It is always fascinating to see how the backroom of any operation works.  And Zoos are no different than others.  They are complex in many different ways.  They are a business, an enterprise with customers and assets, a research facility and scientific repository.

So it is natural that they have to deal with complex data challenges, and have a desire to utilize analytics to make predictions about their systems.  They would also like to be able to market to their loyal customers by tailoring services to them to ensure that the community will continue to visit and support.  You don't typically think of a zoo this way, but in these times all enterprises need to be smarter.

It is a great example of the midmarket enterprise.   All of which have similar challenges.    IBM has worked with Brightstar Partners to build a data warehouse and utilize that data to perform predictive analytic  operations to better solve their problems.  This has led to a 35% increase in food and retail sales.   And an expected increase of 50,000 visitors a year.  Very good for a midmarket operation that has been around since 1873.  I look forward to visiting it again.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.

Mobile Employees Driving Cloud

Makes sense.   Which also increases the need to make sure that the connections are secure and reliable.

Compost Analytics for the City

This is a classic example of vehicle routing using analytics.  I have worked on problems as disparate as ambulance routing in semi rural counties and routing log trucks to pulp mills, to minimizing the travel of fork lifts in product warehouses.  We called these methods 'operations research'.  They are about doing things smarter, by being faster and cheaper.

Examples where the profit margin of an operation is small to begin are particularly interesting. This video outlines the example of gathering trimmings and cast offs from San Francisco restaurants and efficiently getting the resulting compost to vineyards to use for fertilizer.  How should I route trucks though complex city streets, do pickups and then get the result to far away vineyards while minimizing costs? It is all about becoming smarter using analytical methods.

The company doing the work to take trimmings from recycle bins to composting center to vineyard is done by Recology Inc  with data and analytics help from IBM Partner Key Info Systems. More on that collaboration.

Problems like routing are combinations of data, timing, resource and goal management.  With the data often changing based on the dynamics of streets, labor and schedule.  All needed to ultimately feed the smarter city.  Mining data for doing something effectively is not unlike mining minerals. Or mining compost for its value in agriculture.

More about the analytics dimensions of these problems.  Also this blog often covers the topic of analytics for any size company.  Posts about that here.   #Midsize

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.