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

Cloud, Data, Analytics and Process for SMB

Brought to my attention,  In The Financial Express, from Jyothi Satyanathan, director Mid-market & Inside Sales, IBM India/South Asia.  I much agree with his opening statement:

" ... Small and mid-size businesses (SMB) are some of the fastest adopters of IT, as they clearly see the immediate benefits in growing their business and becoming more efficient. IT solutions providers recognise the opportunity in the market to accommodate SMBs in a big way among customers. Today the world is experiencing another sweeping change—powered by big data analytics, mobile, social and cloud. These foundational technology shifts are inspiring forward-thinking leaders from smaller businesses to drive change in how decisions are made, redesign how their teams work, and reassess how to serve the individual consumer. ... " 

He goes on to say that big data and analytical techniques are now available to Small and Medium sized Businesses (SMB).   Yes, this is revolutionary.  The Cloud allows the use of these technologies for any sized business.  Adding a strong flexibility capability.   In the past SMB's could not spend what was needed to buy the servers, license the software, and deliver the results to its people.   Now they can also pay for only what they need. The maintenance and security can be outsourced.  All of these capabilities are there, at a bargain.

A good example:  In a recent project we were asked to deliver analytical methods to tablet based systems.  The Small business was not ready to license multiple seats for visualzation software, or the analyical packages needed to test their efficiency ideas.  But the use of R, a free open source system that readily links to databases, Big Data and other platforms, could be readily be used to test out ideas, and then migrate these ideas to their core systems.

He goes on to discuss the key element of efficiency and some good examples:   " ... the use of cloud technologies is enhancing efficiency manifold as it enables the placing of marketing assets such as digital files of campaigns, videos in the cloud so that all involved parties can create, modify, use and share as needed. Marketing data on the cloud makes it easier for marketing staff to access information anytime and anywhere on the field. ... " 

And ultimately the use of Big Data.  Here I think there is need for some caution.  Start with small and less complex data.  Place your data in a 'sandbox' to test new ideas.  Find some real wins you know you can make happen.   Determine what kind of data you need, have or can acquire.  Make sure you really understand the business decisions being improved ...   Make sure the small scale experiments you complete provide real value, and then scale up.   Along the way,  set up the architecture to repeat this, and then do repeat it!    I agree there is a big contribution potential for Big Data here, as he says:

" ... The major contribution cloud makes to the SMBs ecosystem is big data analytics. Like larger enterprises, SMBs stand to gain from understanding the importance of big data. Big data can arm small businesses with insights and capabilities by analysing data surrounding their business, creating new ways to operate more efficiently, find new customers and more importantly improve bottom-line results. ... "

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.

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.