Monday, May 18, 2015

Keeping MA at the forefront of IoT

April 29, 2015
IoT Roundtable: Keeping MA at the forefront of IoT

Back in February, MassTLC’s IoT Steering Committee met to develop a mission, which is bringing together everyone within the Massachusetts’s IoT ecosystem to make us THE global hub of IoT. And on April 29th, roughly 50 IoT enthusiasts joined MassTLC at Pegasystems in Cambridge for an open forum to start the conversation on how to make this a reality.

Lead by Setrag Khoshafian, Chief Evangelist and VP of BPM Technology at Pegasystems, the forum kicked off with a landscape – highlighting that is beyond technology. It is about adding value and changing lives.

 View Presentation

Setrag discussed some of the ‘things’, spanning from watches to shopping carts to lightbulbs to windmills to engines, robots, or any piece of machinery at any home, factory, hospital, or other institution.  And interestingly the social networks highlight that IoT’s strongest in the wearables and connected home markets, but the real markets in terms of revenue include manufacturing and transportation.

While there are many reference models to build an IoT strategy, Setrag focused on the IoT World Forum’s which top-down approach starting at Collaboration and Processes – the people and business process) and ending at the Physical Devices and Controllers – the things.

In the end, we know that IoT does have hype, but it’s not just the hype. It’s real, it’s happening.

Below is a list of questions, answers, insights that came from the forum. Rather than summarize, I’ve done my best to synthesize. The bold subheadings are the topics for each discussion block.

I urge all of you reading this to reach out to me if you have any insights you’d like to share.

Why Boston?
  •           We have dense segregated stake holder tech communities.
  •           Our strong educational system around we have here.
  •            It’s a financial hub. MA leads in investments in IT infrastructure. Some of the largest investments in M2M and IoT space have been here in Boston.
  •            We have the main IoT infrastructure players located in region.
  •            IoT is a comprised of different technologies: software, networking, ALM, etc. and Boston has all of these.
  •           The environment is right because we have the financial, operational, technology all here.
  •            Robotics is huge in Boston. And robotics and IoT and data go together perfectly. When you put IoT and robotics together you can take a leap to another level.
  •          Can Massachusetts just become the global hub of IoT generically? Does having all of the key sectors here make us stand out more than other areas? How do we really bring all of these things together and then showcase them together?
  •           We need investments on the backend to support IoT.
  •            In terms of vertical industries the medical industry here could provide a huge lab to work on IoT.
  •            We are in close proximity to Europe and other international regions where IoT/M2M is prevalent.
  •            Innovation happens at the boundaries. We have a lot of multifaceted businesses that are all on the boundaries of innovation (healthcare, robotics, etc) so we have a unique foundation to start this.

What are the industries or domains we should be focusing on? Or should we?
  •          Wearable and ingestibles are both areas to watch out for in the healthcare industry.
  •           Boston is such a center of healthcare both on the research and practitioner side it is an obvious place we can focus.
  •            A question from an audience member to the group: What is the objective of there being focus? - -  All innovation happens when a company or group of people or an entrepreneur takes a lead and does something. It’s about going after an opportunity. It’s not about choosing a focus.- - Opposing view: We can certainly influence the focus by providing direction in the incubators, accelerators, investments, in certain areas.
  •             MassTLC can help be the petri dish to help drive focus areas and ID the huge opportunity markets such as healthcare and robotics.
  •             We need to spur discussion between big industry and government - such as they are doing in Singapore and Dubai – where they are building smart cities from scratch. We in the US are retrofitting cities w/ IoT. But the government needs to make investments. If we’re an innovation hub then the government needs to be part of the ‘it takes a village’ group. It should not take four years to deploy smart meters.

How can we effectively work together? How can such a diverse group be effective together?
  •           One way is to make sure we all understand what each other does. And then we need to know what we are asking from one another. Getting a deep understanding of how we can work together is critical.
  •           ID some areas that everyone agrees on. What are the common areas?
  •           The success is knowing and making all the parts of the ecosystem available. VCs and entrepreneurs to technologists, customers, partners. You need to bring everyone together.
  •           We need to create an ecosystem for idea sharing.
  •           Gain an understanding of the technology landscape both horizontally and vertically. Then assess where we are strong and where we have gaps. If we want to really have leadership in that area we need to play to our strengths and/or fill in the gaps where we aren’t strong.
  •           Put together a series of discussions with vertical leaders (from DoT or healthcare institution) to provide insights on the problems they are facing.
  •           It is important that Boston itself become a showcase of this technology to actually be the leader of the technology.
  •           Can we have a focal point, such as gathering around the Olympics in Boston? And then bring stakeholders together to collaborate on how to create a smart city in time for the Olympic Games. You need a focal point if you really want to bring together to work effectively.

What are customers asking for and how can we support them as a team? And what aren’t they asking for? This can be B2B, B2C, internal enterprise, partners, government, etc.
  •          Customers want to know how to monetize. You monetize the service that the IoT provides.
  •          They want to know what investments they can make today that won’t be obsolete in a couple of years. So what platforms they can invest in that enables them to build on top of it and continue leveraging the platform for some time.
  •          What people want are ways to get things done. Technologists can use their resources to make that happen for them.

What have you seen in IoT disruptions/innovations? Trends you have seen?
  •        It’s about coming up w a platform to leverage the data that people can make money off of.  - - One obvious example is jet engines. The guys that own the airplanes don’t own the engines.  - - The cities don’t own the parking meters.  - - The houses w/ the solar panels don’t own the panels.

What are the most serious challenges?
  •                Security
  •                Privacy / governance
  •                Skills gaps
  •                Who owns the data? What happens when the company goes under and the information is stored in the cloud. We need to work w/ the govt to create the laws for the owners.
  •                Understanding what infrastructure, societal, or governmental situations that will impede progress. Can we get ahead of this?

Thursday, April 30, 2015

The New Era of Robotics Summit: Identify. Commercialize. Fund; April 29, 2015

Our April 2015 Robotics Summit brought together over 100 attendees from industry and academia to state and government/military representatives. The summit was kicked off by Kaigham Gabriel, President & CEO of Draper Laboratory sharing his thoughts on breakthrough innovation teams:  performing in Pasteur’s Quadrant à the intersection of a science/technology inflection point and a driving application.

Our keynote was followed by a diverse Industry Panel of thought leaders who discussed current and future robotic applications – more specifically smart factory automation and industrial IoT, autonomous vehicles and medical/surgical technology.  The group was moderated by Linda Thayer, Partner at Finnegan and longtime supporter of the MassTLC Robotics Cluster. 

(left to right)
Tony Lennon, The MathWorks, Industrial Automation Specialist; Garry Ritter, Director Technology & Strategy at the Volpe National Transportation Systems Center spoke about the future of autonomous vehicles; Scharukh Jalisi, M.D., FACS Director Boston University School of Medicine, Head and Neck surgical Oncology and Skullbase Surgery; Lt Col Matthew Woolums, Commander, 1st Weapons of Mass Destruction Civil Support Team, MA National Guard

After a short networking break, Christina Chase, Entrepreneur in Residents for the Martin Trust Center for MIT Entrepreneurship, engaged in a Fireside Chat with Arron Acosta, young entrepreneur and co-founder and CEO of Rise Robotics.  They discussed the challenges startups face in gaining access to funding.  Arron walked thru his efforts in the hopes that he could help provide lessons learned to others in similar situations.

There was no lack of audience participation and questions on the topic of investor funding for robotics technology and companies!

Christina then moderated a panel of investors with diverse business models and investment criteria.

(left to right)
Christina Chase, Entrepreneur in Residents, Martin Trust Center for MIT Entrepreneurship (Moderator); Anders Bialek, Director of Corporate Development, iRobot; Jerry Bird, President, MassVentures; James Geshwiler, Managing Director, CommonAngels Ventures; Rudina Seseri, Partner, Fairhaven Capital  

James Geshwiler has a few words of advice for Arron.

Thank you to all who attended and participated in our lively discussion.  A special thanks to our summit sponsors:

As well as our Cluster Sponsor:

15 Things Learned From the 2015 MassTLC Sales & Marketing Summit

On April 7, 2015, MassTLC gathered 55 of the top sales and marketing professionals in New England to discuss “Building a High Performing Sales & Marketing Organization.” These were our takeaways, what were yours?

  1. Get rid of the “Gobbledygook” on your website. No one cares about your innovative, next generation, new and improved, world class, innovative product. Just tell me what it does.
  2. Be agile and respond in real time, it is no longer about marketing at a time that works for you, it’s about marketing to the customer when it works for them.
  3. Don’t be boring. Create content that connect your product to what’s happening. Newsjack!
  4. Hire journalists to create your marketing content.
  5. Tear down the sales silo and the marketing silo and build it all under the Smarketing roof!
  6. You need to clearly define what a lead is and what an opportunity within your organization is and make sure there’s an agreement on that definition.
  7. Although there is a debate of where BDRs should sit, the majority believe it’s a sales function.
  8. The best way to recruit top sales & marketing talent is through your top sales people and marketers, leverage their networks to find new hires.
  9. Advocate marketing plans can help your message get to the consumer during the 70% of the buying cycle before they speak with a sales rep.
  10. Responses from advocates on social media resonate better with consumers than direct company responses.
  11. Engaging customers as advocates enhances the post-sale experience.
  12. Have a post-sale touch plan, don’t wait until it’s time to renew.
  13. Understand the “Why” in everything you do, don’t run a new campaign just to run one, determine what the value should be if you get the results you expect.
  14. All good ideas are outside the office, get outside and talk to the people that are consuming your products.
  15. MassTLC events are a great opportunity to learn and network!

What others were picking up:

Wednesday, April 15, 2015

MassTLC Mobile Disruption & the Future of Work Roundtable Recap

On April 15, 2015, MassTLC hosted a mobile roundtable at Cambridge Innovation Center, with presenters from Mobiquity to discuss what role mobile plays in the workplace.

As times and devices have changed there has been a huge disruptive shift in how companies do business, manage their workforce, and secure their data. Mobile isn’t a technology, it’s a state of being.

Many people think of the bleeding of work into their home life, but what about home life bleeding into work? Texting and G-Chatting with friends, responding to personal emails and calls, what’s happening on Reddit, and everything that needs to be ‘gramed throughout the day? The common thred to these things are mobile devices. Salesforce, outlook, and classified/proprietary data are stored side by side with Tinder, Candy Crush, Facebook, and banking apps.

How do you go about building a mobile toolbox for your employees that protects sensitive information without commandeering their personal property? Are there ways to make collecting your employee’s personal information off their devices benefit the company? Tracking where they are selling by looking at Maps? Using their fitness apps to lower insurance costs?

There are far more questions than answers at this point but you can listen to the discussion on SoundCloud or view Mobiquity’s presentation in the video below.  

MassTLC Robotics Cluster Participation in National Robotics Week: April 4-12th

There were SO many activities going on in the Boston area during National Robotics week.  Here are just a few highlights:

WPI hosted an evening with Warner sponsored by INCOSE New England Chapter.  Michael Gennert, WPI Professor of Computer Science and Director of Robotics Engineering, discussed how systems engineering played a role in the development of Warner during the international DARPA Robotics Challenge and what systems engineering means to an entrepreneurial robotics team.  Attendees were treated to a demo of the Atlas robot performing one of the tasks for the upcoming DARPA competition. 

New England Robotics Validation and Experimentation (NERVE) Center held an open house with many fun demonstrations:

The Vecna Cares Human 5K Race and Robot 100m Robot Sprint Challenge brought out hundreds to celebrate and cheer on both runners and robots!  There was quite a variety of robots, as well as activities – there was even a robot playpen.

And supporting the race from MassTLC (Pictured left to right - Joyce, Clare, Mackenzie, Rachael, Ruth, Leah, and Mike):

Tuesday, March 31, 2015

Guest Blog Post: Flipping the Lens on Sustainability Disclosure Frameworks

Written by: Nick Martin and Michael Rieger, Antea Group (MassTLC Member)

It seems that every day there is an article about the ‘Internet of Things’ or ‘Big Data’ and while we have yet to fully grasp the magnitude of this shift in technologies, it is a clear indication of where we are headed in terms of access and sharing of information.  This new operating environment with transparency and disclosure expectations is bound to increase given the state of technology, social media, and access to information.

The last decade has demonstrated the importance of transparency within the business world and we believe most companies, either through voluntary or mandated response, have embraced this as a fundamental requirement of success. The renewed calls for transparency have been amplified by simultaneous technological advancements and opportunistic stakeholders ranging from investor representatives (e.g., CDP, Ceres) to major corporations such as Walmart. The result has been an explosion of disclosure requests and expectations being placed upon companies in the United States and abroad. Many companies are feeling overwhelmed by survey requests, requiring a significant and seemingly endless allocation of resources.

Companies are increasingly being pushed into a precarious position of either declining sustainability disclosures outright or picking and choosing which surveys to respond to. Branded companies with a complex and diverse stakeholder base have increasingly begun to question the ongoing business value of disclosures compared with redirecting resources to other company investments and partnerships.

While the question of ‘do’ or ‘do not’ disclose will remain, in this blog we offer a different perspective on the business value of utilizing disclosure frameworks and requests. If you ‘flip the lens’, you can find an invaluable resource that we believe is underappreciated.    

Disclosure frameworks have completed significant research and ‘leg work’ to define the most critical and effective elements of Corporate strategies. They have engaged leading experts and companies, facilitating a rigorous development and maintenance effort to accelerate Corporate adoption of sustainability-related initiatives. The business value is that surveys and associated scoring methodologies can be utilized by companies as comprehensive gap analysis tools for developing an effective, holistic strategy and/or validating efforts to date. Furthermore, these methods are absolutely free and include a wealth of guidance information and resources (e.g., reports, webinars, diagnostic tools, etc.).

Making This Real
The following are three examples of disclosure frameworks that are primed for extracting meaningful insights and utilizing these as a gap analysis process to enhance company standards:

§ CDP (Water, Climate Change, and Forests) – an exceptionally transparent organization with surveys, methodologies, and scoring publicly available:
Ø Questions to ask: is our strategy well aligned with the associated CDP questionnaire?  Can we answer questions affirmatively?  What are the gaps, especially for elements that CDP applies a higher scoring weight? 

§ Global Reporting Initiative (GRI) – the G4 Standard outlines a process for completing Corporate annual reports, including clear guidance on individual indicator definitions and a quality rating methodology. In addition, GRI provides a search tool to see real examples of Corporate reports at varying quality levels, which provides valuable benchmarks and examples to utilize in developing your company’s annual report.
Ø Questions to ask: Which of the GRI indicators is our company able and comfortable reporting? If not able or comfortable, why not (e.g., insufficient data, not material, not a compelling story or performance level, not previously considered)? How do we compare to sector or peer leaders? Are there elements of the GRI guidance that would help our other disclosures (e.g., website material, supplier or customer communications, materiality assessment)?

§ Sustainability Accounting Standards Board (SASB) – a unique initiative that is focused upon defining the materiality of social and environmental issues for up to 80 unique sectors.  The ultimate objective is to embed the outputs of the SASB Standards into financial disclosures (e.g., 10-K, SEC Filings). The website provides: 1) Industry Briefs; 2) Industry-specific Standards; and, 3) a Materiality Map.
Ø Questions to ask: has our company acknowledged the same materiality issues as proposed by SASB for our sector?  If not, what are the differences and why? How prepared are we to align with the SASB Standards if they are integrated into financial filings?  Is there additional data we should consider collecting now to be prepared? 

In addition to these examples, there are many others that could be utilized in a similar manner such as: ISO 14001; ISO 50001; USGBC Leadership in Energy & Environmental Design (LEED); UN Global Compact and CEO Water Mandate; and Ceres Aqua Gauge and the Ceres Roadmap for Sustainability.  There are also a variety of industry and material sourcing-specific guidelines.  
While disclosure frameworks and standards will likely continue to proliferate in at least the short-term, companies can ‘flip the lens’ and extract added value by using these well thought-out resources. This approach will benefit companies to define cutting edge strategies, drive business value and prepare the organization internally, regardless of ultimate disclosure decisions

Nick Martin is Sustainability Practice Lead ( and Michael Rieger ( is a Consultant in the Boston area with Antea Group

Tuesday, March 17, 2015

Guest Blog Post: How to Sidestep Automation, Augment Technology, and Keep your Job

Written by Scott Etkin of Data Informed, click here for original post.

BOSTON—Concerns about the impacts of technology on jobs are nothing new. Fears about automation replacing assembly line workers, for example, have been around almost as long as technology itself, and to a large extent, those fears have been realized. The advent of big data raises concerns that technology might be threatening the jobs of knowledge workers. But can automation have the same impact on a workforce that trades in knowledge and creativity rather than physical skill?

Tom Davenport, professor at Babson College, Research Fellow at the MIT Center for Digital Business, and a Senior Advisor at Deloitte Analytics, addressed this question today in a keynote address at an event hosted by Massachusetts Technology Leadership Council titled, “Big Data and the Knowledge Worker: Impacts on Workforce and the Economy.”

“(Knowledge workers) have had a pretty good run over the past few decades, said Davenport. “It’s been pretty tough for factory workers, before that farm workers. It’s been pretty tough for service and transactional workers. Now that same automation is coming close to home. We always thought that whenever technology took over a type of job, that humans just moved to higher ground. When farming started to go away, people moved into factories. When factories started to go away, people moved into cities and did service and knowledge-oriented work. But this time, there is no higher ground.”
Davenport said automation has progressed from manual labor to administrative and service jobs, and that knowledge worker jobs might be the next step in that progression.

“One could argue that just as we automated manual labor jobs in the 18th and 19th century, administrative and service jobs in the 20th century, that the 21st century is where knowledge worker jobs really start to take it on the chin,” he said. “I think there is some sense of historical inevitability about this that we have to address seriously.”

Davenport identified several technologies that are driving knowledge work automation, including analytics and big data, machine learning, artificial intelligence/deep learning, and cognitive computing. He said that as analytics has evolved, it has become more recommendation oriented.

“Now I think it’s important to add a set of automated analytics at the top that says we are not just going to help you figure out answer, we are going to take action on it,” he said. “We are going to make a decision and we are going to forge ahead with the action related to that decision. There are all sorts of spheres in which that is already taking place.”

Davenport identified 10 knowledge work jobs that he called automatable: lawyers, accountants, radiologists, reporters, marketers, financial advisers, architects, teachers, financial asset managers, and pharmaceutical scientists.

Augmentation Instead of Automation

As another possible result of the ongoing evolution of technology, Davenport offered augmentation – humans and computers working together to make better decisions – as an alternative to automation, in which technology simply takes over the jobs of humans.
“Augmentation means humans are helping computers make better decisions, and vice versa,” he said. “People do this by aiding automated systems that are better at a particular task or by focusing on tasks at which humans are still better. It’s an ever-changing domain.”
Currently, this cooperation of humans and machines can produce results better than either computers or humans alone. Davenport offered the classic example of freestyle chess and a 2005 freestyle chess tournament in which two amateur players using three laptops defeated both grand masters and supercomputers.

Five Possibilities for Augmentation

Davenport offered five steps to augmentation in jobs:
Step in. Learn the system, how it works, its strengths and weaknesses, and how and when to modify it.
Step up. Monitor the big-picture results of computer-driven decisions, and decide whether to automate new decision domains.
Step aside. Focus on areas that people do better than computers, such as the creative and interpersonal.
Step narrow. Focus on areas that are too narrow to be worth automating.
Build the steps. Create the automated systems.

Davenport also offered advice for knowledge workers who are concerned about being displaced by automation and how to become an augmenter.
  • Understand the ins and outs of how computers do your tasks, and try to improve them.
  • Specialize in a component of your job that can’t be done well by a computer, such as sales.
  • Write computer programs and algorithms yourself.
  • Find a narrow job niche that no one would bother to automate.

Davenport ended by implying that understanding what it takes to become an augmenter – learning, changing what you do, and a lot of work to make it happen – may determine whether you keep your job.
“There’s always the artisanal plumber route,” he said. “All those knowledge workers could get some really artistic plumber’s helpers and go to work.”

Scott Etkin is the managing editor of Data Informed. Email him at Follow him on Twitter: @Scott_WIS.

Big Data and the Knowledge Worker Summit - Feb. 27th Recap

Written by: Udi Dotan

Some of the best and brightest in the Massachusetts data and technology space gathered on the last Friday in February to discuss how the world of big data and computers might impact knowledge workers in the 21st century keynoted by esteemed author Tom Davenport.

Tom spoke on the displacement of workers over time.  In the 18th and 19th centuries, it was farm workers, in the 20th century, it was service jobs, today, it's knowledge workers that are being displaced by technology.  Artificial intelligence is growing and taking over roles that humans used to do and they will take over more work.  Computers can do many tasks faster and more efficiently than humans and computers are cheaper, easier to manage, and don't complain about the cost of healthcare. 

Should we welcome these changes as another in a string of technological revolutions that have enabled humans to flourish, or fear our new computer overlords?  Some technology leaders such as Elon Musk and Bill Gates have voiced concerns about these changes positing that AI is the most dangerous development in history and should be looked upon with skepticism.

Where do these fears come from and how did we get here?
Since the dawn of the age of the internet 20 years ago (yes, it's been more than two decades since you saw your first AOL CD), information has been generated and has flowed more freely.  With more data, they has been more desire to analyze which led to enormous growth of analytics.  Early analytics were descriptive, utilizing simple graphs and charts to understand our world. 

Today, companies are utilizing predictive and prescriptive analytics to help make better decisions (think Amazon's recommender engine).  Going forward, more and more companies are leveraging larger stores of data, more compute power, and sophisticated algorithms to automate analytics.  One such example was given by Ed Macri, Senior Vice President of Marketing and Analytics at Wayfair.  They are using analytics to personalize one million emails a day based upon their prior visits, versus a single email carbon copied to one million people.  

Another example given by a member of our keynote panel, Bruce Weed, Program Director, Global Watson and Big Data Ecosystem Development at IBM, is how Watson, who through the use of its massive library, is helping medical doctors diagnose in a much faster and efficient manner. 

What jobs are computers doing that have or will displace humans and how do we service our new masters?
Of course, no human is capable of personalizing a million emails.  But these aren't the only roles that are ripe for computerization.  According to Tom Davenport, here are some "at risk" jobs that computers can and will do better than humans:
  • Lawyers: e-discovery - combing through thousands of documents to find the nuggets of truth for specific court cases.
  • Accountants: audits, taxes - using intelligence to improve tax preparation (think TurboTax).
  • Radiology: cancer detection - using machines to read radiology reports and highlight areas of concern.
  • Reporters: automated story generation - computers can used data to generate articles for publishing (like this one? - not yet).
  • Marketing: online ad buying and personalized emails as with Wayfair
  • Financial Advisor: "robo-advisors" - generating customized portfolios for clients based on factors such as age, income, and tolerance to risk.
  • Teachers: online content and automated student evaluation - companies such as Kahn Academy, Coursera, and EdX are delivering content online.  Next generation companies such as Dreambox and Knewton are delivering adaptive learning that modifies the material in response to student performance.

Have the machines already won or is there a role for us yet?
Some companies are already leveraging intelligent machines, has this turned their offices into a wasteland where tumbleweeds are rolling through giant data centers?  In short, no, there are still plenty of things that computers can't do without us.  Davenport refers to this work as augmentation.  Computers are good at computationally complex and repetitive tasks, but they can't see the bigger picture.  Humans will be needed to identify the strengths and weaknesses of the analytics systems and algorithms.  Humans will be needed to determine the business problems to solve.  And humans will build and maintain the systems to solve those problems.

As highlighted at the conference, big data technology enables much of the analytics innovation as companies can manage with larger and more varied data stores.  Jeff Kelly, Principal Research Contributor at Wikibon believes that we are moving from early stage adoption of big data implementations built around cost savings to a second generation whereby companies with big data strategies are now focused on revenue generation and operational efficiency.  P. Gary Gregory, SVP & GM, Database Servers and Tools at Rocket Software illustrated that to be successful with such data initiatives, you need to start with a business problem and build data systems to support solutions.  Those systems don't need to include hadoop, but the purpose of the data and the definition of the data sources should be clear, otherwise you end up with a data landfill, not a data lake.

Several of the panelists illustrated that the analytics revolution has led to a greater need for humans, not a lesser need.  Ivan Matviak, Executive Vice President and Head of Data and Analytics Solutions at State Street Global Exchange says they are hiring more people, not fewer, to help build and maintain its advanced analytics capabilities.  In particular, they are aggressively seeking to hire the sexiest workers, data scientists.  EMC's data science practice spends a great deal of effort investigating and rebuilding messy data for analytic purposes. And Wayfair is augmenting automated ad purchases with targeted human buys of online ad space.

Iran Hutchinson, Product Manager & Big Data Software/Systems Architect at InterSystems led a lively panel discussion illuminating success stories at companies leveraging big data and human augmentation to gain remarkable insights.  Joe Dery, a Senior Data Scientist at EMC relayed how EMC increased revenues by mining internal contract data to optimize contract renewals.  The key to optimization was not in the volume or veracity of the data (although there certainly were large volumes of data), but rather in clarifying data definitions and educating the sales team.  According to Joe, the model generation was the simplest part of the two year project.

Gary Sloper, VP of Sales Engineering and Operations at CenturyLink uses big data to proactively monitor network activity and utilize machine learning algorithms that can detect anomalies.  Such techniques can be employed to prevent hacks such as Sony and Anthem have recently experienced.

At, Co-founder and CTO, Dave Krupinski and his team has focused analytic attention on optimizing the match rate between jobs posted and caregivers seeking jobs.  This has given them guidance on the optimal flow of applications into a job posting, the optimal number of applications per job, and the key terms that are more likely to get a caregiver hired.  The insights have led to an increase in match rate from 70% to over 80% with more opportunity to improve in the pipeline.


As the volume, velocity, variety, and veracity of big data grows and the analytics become more complex and the opportunity for a cooperative relationship between machines and humans will continue to grow and we will continue to find ways to employ technology to advance society.

Tuesday, February 17, 2015

Creating a Repeatable, Sustainable, Valuable, and Predictable SaaS Business: The Value Prop at the IBM Innovation Center in Cambridge, MA with Michael Skok

Approximately 75 intrepid attendees braved freshly falling snow (again!) to join MassTLC’s Cloud Cluster and Sales & Marketing Community in their joint program, Creating a Repeatable, Sustainable, Valuable and Predictable SaaS Business: the Value Prop. This event was the first of a three-part interactive workshop series with entrepreneur and investor Michael Skok. Special thanks to our event host and MassTLC Global Sponsor IBM and Cloud Cluster sponsor CenturyLink!

Next up: The Business Model and Turning Products into Companies.

Highlights of the Value Prop workshop included:
  • Michael led attendees through his Value Prop template with help from Co-Founder and CEO George Adams of ViziApps and Co-Founder and CEO Shantanu Dhaka of Modit as case studies
  • Many companies don’t have a good idea of what their true Value Prop is
  • Understand the problem you believe you are solving before you get too excited about your idea
  • Try to solve a problem that cripples businesses - problems needing to be solved should be: Unworkable, Unavoidable, Urgent, and Underserved
  • Customers want you to solve their problem first, then make it better - avoid using “Solution,” “Faster,” “Better,” “Cheaper” in your Prop
  • Big problems are big opportunities – it takes as much energy to tackle a big market as a small market, so why not go in for the big fight?
  • Realize that when you pitch that you are asking people to change their budget and make your solution a priority

Check out Michael’s recap of the event here.

Being Agile in a Value Prop Framework – Modit Case Study

Crystallizing our Value Prop and Fundamental Benefits for Customers – ViziApps Case Study 

Complete Event Recap

Every business needs a Value Prop. Chances are that your business was based around an idea that you believed was your Value Prop. As time passed, your idea evolved, the product started to come together, and now your sales deck is a bloated, incoherent mess that only you can understand and the true Value Prop is buried or completely lost somewhere between slide 1 and 60.

According to Michael Skok’s Value Proposition template, if you can clearly and concisely answer five critical questions, you can build a successful Value Prop:
  • Who is your product for?
  • What are they dissatisfied with?
  • What is your product?
  • What is the key problem solves?
  • Why is your product is better than anything else in the space currently?

To answer those questions he suggested following a three-step process:
  • Define the problem you are solving
  • Evaluate your solution
  • Build your Value Prop.

Simple, right? However, tackling each step of the process is going to be a bit of work.

Is your product solving a real problem? What defines a real problem? A real problem can be identified by 4Us:
·         Unworkable – If this problem happens, someone loses their job or the company goes under.
·         Unavoidable – Everyone in your market will encounter a time where your solution will be beneficial.
·         Urgent – The problem is currently causing issues and the customer will be able to benefit quickly.
·         Underserved – Don’t compete in a flooded market, your resources are finite.

After you’ve defined the real problem, look back at your idea and determine the real solution. Is it a breakthrough opportunity? Look for the 3Ds - it should be Discontinuous Innovation, Defensible Technology, and have a Disruptive Business Model.

With the solution now in hand, it’s time to evaluate it. Are the client’s gains from using your product going to outweigh the pains of trying it and implementing it? Could they get by with a competitors’ cheaper product, or even without doing anything at all? If there’s not a large enough gain to pain gap (gain >10x pain) you will have a difficult time getting clients to adopt which tosses you into the unworkable problem category! Focus on disruptive innovation with non-disruptive adoption.

Now – with all these insights in mind - take another look at your Value Prop to fill in the template:
  • Who is your product for?
  • What are they dissatisfied with?
  •  What is your product?
  • What is the key problem solves?
  • Why is your product is better than anything else in the space currently?