Research Report: Inside The 2015 Boardroom Priorities (Parts 1 & 2)

R "Ray" Wang

Principal Analyst and Founder
Constellation Research

R “Ray” Wang is the CEO of Silicon Valley-based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and blogs at www.raywang.org. His ground-breaking best-selling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015. Ray's new book about Digital Giants and the future of business, titled, Everybody Wants to Rule The World was released in July 2021. Wang is well-quoted and frequently interviewed by media outlets such as the Wall Street Journal, Fox Business, CNBC, Yahoo Finance, Cheddar, and Bloomberg. Short Bio R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley-based Constellation Research Inc. He…...

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Boardrooms In Market Leader And Fast Follower Organizations Rapidly Take Action To Address the Digital Chasm Ahead

Constellation Research surveyed over 200 CXO’s and identified 10 board room priorities for 2015. As anticipated, digital transformation has emerged as a significant board room topic and market leaders and fast followers seek guidance on what elements are required in the design to support digital business.

Digital Transformation is defined as methodology in which organizations transform and create new business models and culture with digital technologies. The driver for digital transformation stems from the fact that since 2000, 52 percent of companies in the Fortune 500 have either gone bankrupt, been acquired or ceased to exist.

These market leaders and fast followers surfaced a theme of ten priorities heavily skewed towards the higher end of the Constellation Corporate Hierarchy of Needs (see Figure 1)

Figure 1. The Constellation Corporate Hierarchy Of Needs

Download a free snapshot of The Elements of Business Architecture for Digital Transformation

Boardroom Priorities Reflect An Urgency For Change At Digital Speed

After categorizing boardroom priorities according to the Constellation Corporate Hierarchy of Needs, 10 trends emerged across all five categories.  Of note, a greater number of priorities for 2015 emerged in the higher level of needs.   This changed from previous surveys indicate a desire to shift strategy or embark in business transformation.

Brand Priorities Support the Delivery of Authenticity in Both Analog and Digital Worlds

1.      Investment in digital presence.  Digital personas must not only reflect the brand, but also expand upon the analog experience.  Brand conscious leaders invest in the digital experience with an eye towards mass personalization at scale.  While advertising plays a key role in carrying out the message, investment in the design of digital experiences emerges as the hot area of investment.

2.      Consistent delivery of customer experience (CX).  Board members in highly competitive markets emphasize the need to improve and expand customer experience in order to grow lifetime customer value.  They realize these initiatives require both a sustainable engagement model through communities and a loyalty dimension through gamification and value exchange.

Strategic Differentiation Focuses On Proactive and Reactive Digital Transformation Techniques

3.      Digital transformation of the business.  Leaders are scrambling to create new business models through disruptive technologies.  One trend includes the introduction of new unit – cost business models.  These business models seek to deliver the smallest unit of product or service to a customer and then seek subscription models for longer-term predictability.  In addition, leaders are hoping to take advantage of the scale of digital to deliver on the long-term goal, which are customer segments of one.

4.      Rapid response to non-traditional competitors.  With the rise of non-traditional competitors to almost every market segment, boards are asking their management teams to create SWAT teams to proactively identify potential market competitors. The goal – create potential responses to likely market scenarios based on start ups business models and disruptive technologies.

5.      Creation of insights driven business models.  Expect organizations to deliver 20% of their revenue growth from big data business models by 2020.  The brokering of insights as a content provider, network, or arms dealer emerges as new source of competitive differentiation and also revenue stream.  Organizations must create the ability to deliver insights on their own and feed information brokers such as Thomson Reuters and Bloomberg.

Preorder Disrupting Digital Business, published by Harvard Business Review Press In Q2 2015.  Learn more.

Revenue and Growth Strategies Prepare for Highly Skilled And Inorganic Fueled Strategies

6.      Prioritized development of a high performance culture.  The war for talent continues at the high end of the hiring spectrum.  In fact, the market is highly competitive for the top 10% of the workforce.  Why? Despite hiring fewer workers, most organizations prioritize quality over quantity.  In addition, the pending retirement of a highly knowledgeable and experienced generation creates a vacuum of skilled workers in not only the top ranks, but also the middle of the employee base.

7.      Readiness for inorganic growth.  Cheap capital, patent portfolio accumulation global growth ambitions, war for talent, and declining margins drive organizations towards mergers, acquisitions, and joint ventures.  Moreover, the elusiveness of organic growth challenges boards to consider mergers and acquisitions as an accelerant for intellectual property, talent, customer base, and partner networks.  The goal is to create platform ecosystems and attract partners to co-create and co-innovate.

Cost and Operational Efficiency Remains An Important Pillar Through Automation And Post Merger Integration

8.      Mass automation of work and thought.  Automation expands into both the low end and high end of the market. Leaders invest in robotics, internet of things, and augmented humanity.  The hallowing out of jobs in the middle will expand as machines get smarter and regulatory costs from healthcare to safety increase.  Decision management systems gain favor in making more consistent and smart recommendations based on machine learning and algorithms. From supply chains to customer experience, automation advances at a rapid pace of change.

9.      Efficiency in post merger integration.  With inorganic growth a priority for 2015, boards will measure management teams on their ability to not only complete a merger and acquisition, but also drive out cost, merge product lines, improve up-sell and cross-sell, grow market share, and improve profitability.   Experienced leaders plan for scale by building direct and platform capabilities for core and leveraging outsourced services providers for non core requirements.

Regulatory Compliance

10.    Cost reduction of regulatory and security compliance.  As regulatory compliance proliferates and security threats mushroom, organizations seek capabilities to drive down the cost.  Solutions include creating shared services among competitors to address regulatory requirements and common core processes.

The Bottom Line: Digital Darwinism Is Unkind To Those Who Wait

Unfortunately, in almost every segment, the top three competitors control 43 to 71 percent of the market share and 53 to 77 percentage of the profits. In the technology space only 80 companies since 2000 have made the billionaire’s club.  Meanwhile, intense competition, short-term shareholder and management thinking, and minimal investment hamper the pace of investment and innovation required by business leaders to survive today’s competitive landscape.

While boards have not been complacent about addressing change, the past five years have shown the difference between those who invested in digital transformation and those who have not.  The corporate digital chasm is massive among market leaders, fast followers, and everyone else.  Astute board members realize they must invest in transformational change for face a vicious Digital Darwinism.

Your POV.

Ready for digital disruption by starting with mobile?  Add your comments to the blog or reach me via email: R (at) ConstellationR (dot) com or R (at) SoftwareInsider (dot) org.

Resources

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Ten Ways Big Data Is Revolutionizing Manufacturing

McKinsey & Company recently published How Big Data Can Improve Manufacturing which provides insightful analysis of how big data and advanced analytics can streamline biopharmaceutical, chemical and discrete manufacturing.

The article highlights how manufacturers in process-based industries are using advanced analytics to increase yields and reduce costs. Manufacturers have an abundance of operational and shop floor data that is being used for tracking today.  The McKinsey article shows through several examples how big data and advanced analytics applications and platforms can deliver operational insights as well.

The following graphic from the article illustrates how big data and advanced analytics are streamlining manufacturing value chains by finding the core determinants of process performance, and then taking action to continually improve them:

Big Data’s Impact on Manufacturing Is Growing

In addition to the examples provided in the McKinsey article, there are ten ways big data is revolutionizing manufacturing:

• Increasing the accuracy, quality and yield of biopharmaceutical production.  It is common in biopharmaceutical production flows to monitor more than 200 variables to ensure the purity of the ingredients as well as the substances being made stay in compliance. One of the many factors that makes biopharmaceutical production so challenging is that yields can vary from 50 to 100% for no immediately discernible reason. Using advanced analytics, a manufacturer was able to track the nine parameters that most explained yield variation. Based on this insight they were able to increase the vaccine’s yield by 50%, worth between $5M to $10M in yearly savings for the single vaccine alone.

• Accelerating the integration of IT, manufacturing and operational systems making the vision of Industrie 4.0 a reality. Industrie 4.0 is a German government initiative that promotes automation of the manufacturing industry with the goal of developing Smart Factories. Big data is already being used for optimizing production schedules based on supplier, customer, machine availability and cost constraints. Manufacturing value chains in highly regulated industries that rely on German suppliers and manufacturers are making rapid strides with Industrie 4.0 today.  As this initiative serves as a catalyst to galvanize diverse multifunctional departments together, big data and advanced analytics will become critical to its success.

• Better forecasts of product demand and production (46%), understanding plant performance across multiple metrics (45%) and providing service and support to customers faster (39%) are the top three areas big data can improve manufacturing performance.   These findings are from a recent survey LNS Research and MESA International completed to see where big data is delivering the greatest manufacturing performance improvements today. You can find the original blog post here.

• Integrating advanced analytics across the Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) framework to fuel continuous improvement.  Getting greater insights into how each phase of a DMAIC-driven improvement program is working, and how the efforts made impact all other areas of manufacturing performance is nascent today. This area shows great potential to make production workflows more customer-driven than ever before.

• Greater visibility into supplier quality levels, and greater accuracy in predicting supplier performance over time.  Using big data and advanced analytics, manufacturers are able to view product quality and delivery accuracy in real-time, making trade-offs on which suppliers receive the most time-sensitive orders.  Managing to quality metrics becomes the priority over measuring delivery schedule performance alone.

• Measuring compliance and traceability to the machine level becomes possible. Using sensors on all machinery in a production center provides operations managers with immediate visibility into how each is operating. Having advanced analytics can also show quality, performance and training variances by each machine and its operators.  This is invaluable in streamlining workflows in a production center, and is becoming increasingly commonplace.

• Selling only the most profitable customized or build-to-order configurations of products that impact production the least.  For many complex manufacturers, customized or build-to-order products deliver higher-than-average gross margins yet also costs exponentially more if production processes aren’t well planned.  Using advanced analytics, manufacturers are discovering which of the myriad of build-to-order configurations they can sell with the most minimal impact to existing production schedules to the machine scheduling, staffing and shop floor level.

• Breaking quality management and compliance systems out of their silos and making them a corporate priority.  It’s time for more manufacturers to take a more strategic view of quality and quit being satisfied with standalone, siloed quality management and compliance systems.  The McKinsey article and articles listed at the end of this post provide many examples of how big data and analytics are providing insights into which parameters matter most to quality management and compliance. The majority of these parameters are corporate-wide, not just limited to quality management or compliance departments alone.

• Quantify how daily production impacts financial performance with visibility to the machine level. Big data and advanced analytics are delivering the missing link that can unify daily production activity to the financial performance of a manufacturer.  Being able to know to the machine level if the factory floor is running efficiently, production planners and senior management know how best to scale operations.  By unifying daily production to financial metrics, manufacturers have a greater chance of profitably scaling their operations.

• Service becomes strategic and a contributor to customers’ goals by monitoring products and proactively providing preventative maintenance recommendations.  Manufacturers are starting to look at the more complex products they produce as needing an operating system to manage the sensors onboard. These sensors report back activity and can send alerts for preventative maintenance. Big data and analytics will make the level of recommendations contextual for the first time so customers can get greater value.  General Electric is doing this today with its jet engines and drilling platforms for example.

Additional sources of information on Big Data in Manufacturing:

• Attitudes on How Big Data will Affect Manufacturing Performance. Posted by Greg Goodwin on Thu, Mar 06, 2014. LNS Research. http://blog.lnsresearch.com/blog/bid/194972/Attitudes-on-How-Big-Data-will-Affect-Manufacturing-Performance-DATA From Value to Vision: Reimagining the Possible with Data Analytics, David Kiron, Renee Boucher Ferguson and Pamela Kirk Prentice, MIT Sloan Management Review, March 2013. http://sloanreview.mit.edu/reports/analytics-innovation/introduction/
• Merck Optimizes Manufacturing With Big Data Analytics, Information Week, Doug Henschen. April 2, 2014. http://www.informationweek.com/strategic-cio/executive-insights-and-innovation/merck-optimizes-manufacturing-with-big-data-analytics/d/d-id/1127901
• Takeaways from the MIT/Accenture Big Data in Manufacturing Conference. Posted by Greg Goodwin on Wed, Nov 27, 2013. http://blog.lnsresearch.com/blog/bid/190482/Takeaways-from-the-MIT-Accenture-Big-Data-in-Manufacturing-Conference
• The Internet of Things and the future of manufacturing. McKinsey and Company.  Executives at Robert Bosch and McKinsey experts discuss the technology-driven changes that promise to trigger a new industrial revolution. June 2013 | by Markus Löffler and Andreas Tschiesner. http://www.mckinsey.com/insights/business_technology/the_internet_of_things_and_the_future_of_manufacturing
• The Rise of Industrial Big Data: Leveraging large time-series data sets to drive innovation, competitiveness and growth — capitalizing on the big data opportunity, GE Intelligent Platforms White Paper, April 2012. http://www.ge-ip.com/library/detail/13170
• When Big Data Meets Manufacturing. Stephen Chick, Serguei Netessine, INSEAD Professors of Technology and Operations Management and Arnd Huchzermeier, Chaired Professor of Production Management at WHU-Otto Beisheim School of Management  | April 16, 2014. http://knowledge.insead.edu/operations-management/when-big-data-meets-manufacturing-3297

Complements to Leadership: A Culture of Data

Terri Griffith

Professor/Author/Speaker
Simon Fraser University

Terri Griffith holds the Keith Beedie Chair in Innovation and Entrepreneurship at Simon Fraser University’s Beedie School of Business. She spent two decades in the Silicon Valley and, in 2012 was honored as a Woman of Influence by the Silicon Valley Business Journal. Terri helps her students and their organizations accelerate performance and prepare for the futures of work. Through her speaking, writing, teaching, and research, she brings evidence-based leadership and innovation to high-tech, education, and global agribusiness organizations. She inspires and coaches groups on negotiating change and uniquely mixing existing and new capabilities. Her most recent work uses a “bottom-up” approach to automation, including artificial intelligence. Her award-winning book, The Plugged-In Manager:…...

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I’ve had the opportunity to do a couple of workshops on the value of data in support of leadership -- especially leadership without formal authority. A key issue is that the environment is changing such that we have less face-to-face time for leadership. This increases the value of complements to interpersonal leadership, things like training, tools, and feedback from the work itself. A culture of data can also be an excellent complement to leadership. (Slides from the most recent workshop: Notes are available if you download the slides).

In these workshops, I use a John Trumbull painting of George Washington resigning his commission and position as commander-in-chief. I love how the golden light shines down on Washington. Washington resigned as a signal that power should be in civilian hands - he led by letting go. The point of the image in my presentation is to contrast traditional face-to-face leadership with the next image in the presentation, that of shifts in population density before (diffuse) and after (dense) the industrial revolution. Our moves to more global and virtual work are the swinging of the pendulum again -- though not everywhere as noted by San Francisco Bay Area housing prices. But even in the dense Bay Area, leadership needs to work from afar.

Data is a language understood across a global organization. Data is beautiful. Data is actionable. Data is (often) apolitical. And, yes, I understand the important differences across data, information, knowledge, and wisdom, but data is the starting point.

Data is the starting point for decisions to be made via evidence rather than formal authority. Scott Cook, founder and chair of the executive committee at Intuit, describes “leadership by experiment” (see too, this article by Bryan Eisenberg). Bob Sutton and Jeff Pfeffer highlight similar issues in their book, Hard Facts, Dangerous Half-Truths and Total Nonsense: Profiting from Evidence-Based Management .

In the workshop, I then switch to a micro course on lightweight experiments for management decision-making. For my last audience, it wasn't a big leap from their scientific and engineering backgrounds to the idea of prototypes and experiments focused on anticipation, visioning, creating flexible alternatives, and initiating change - leadership behaviors identified by Ireland and Hitt (1999). They have a culture of data already and I expect this is just a new tool in their toolbox.

Data has a special power for situations where you have little other authority. Think about a negotiation: You both are and act (!) more powerfully when you have a good BATNA (Best Alternative To the Negotiated Agreement). Data is what helps you find and develop that great BATNA.

How has data benefited you in situations where you have little or no formal authority? Please add to the comments here. As I tell my audiences, when I walk into an organization, I generally have no formal authority. I don’t have a strong network inside their structure. All I have is my data and what I’m able to do with it. Hopefully I have enough data underlying this post to trigger a few lightweight experiments.

Thank you to Lucie Newcomb of NewCommGlobal for the LinkedIn comment that got me rolling with this.

For some wonderful and sometimes free resources around lightweight experiments, see MovesTheNeedle’s page.

How Mobile is Disrupting Traditional Loyalty Programs

Partner, Sensei Marketing
Partner, Sensei Marketing

Sales & marketing veteran with almost 30 years’ experience and now 1800 digital projects to his credit for clients including Morgan Stanley, AOL, Hyatt Gaming Management, Snyder's of Hanover, Hitachi, the Home Depot, Kraft Foods, Drees Homes, American Idol, and hundreds more, including leading agencies around the North America.     ...

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My last post here on Sensei blogs shared some statistics that demonstrate the disruptive effect of smart phones on the photography habits of consumers.  Mobile technology and devices have had a disruptive influence on many aspects of our lives beyond digital photography, which, in turn, has disrupted how businesses must engage consumers.

Mobile is Disrupting Traditional Loyalty Programs

Another example of mobile disruption is the effect that our proclivity for mobile communications has had on how loyalty programs operate.  Did you know that, according to Colloquy research, the average U.S. household now takes part in 21.9 loyalty programs every year? Consumers’ fascination with loyalty program continues to grow, despite the overabundance of programs, many of which overlap in functionality, rewards, cards, and/or retailers.

The loyalty card was once a great way for consumers to feel important and recognized, while receiving some form of monetary or status reward. From the company’s perspective , the increased frequency of consumer purchases combined with  advanced data analytics made the loyalty card the perfect tool with which to capture consumer data and help sway purchase decisions.  Brands used direct mail, email marketing, and in-store promotions to reach out to consumers in a more direct and personal manner.

Mobile Phones Replacing Loyalty Cards

More and more consumers are opting out of direct mail or email marketing subscriptions with their favorite brands in favor of RSS feeds and social media engagement.  There’s yet another shift, which has taken longer to establish than most analysts had predicted:  Mobile phones are quickly replacing all other forms of brand-customer communications as the consumer’s preferred communication method.  For example, large retailers such as Walmart are having great success with apps that allow it to make more personalized and real-time offers to consumers while they’re physically present in the store.

Starbucks’ mobile rewards card is another shining example of how mobile loyalty interfaces are changing the way consumers adopt and use loyalty programs (a program that is being quickly emulated by other national retail chains). The Starbucks widget – which provides a mobile desktop glimpse at members’ status, rewards earned, and number of purchases required towards the next reward – is combined with gift card functionality that allows users to upload unlimited dollar amounts to use as credit in the store.

Mobile Device Penetration

Data, data, data…businesses are joyously swimming among this sea of consumer data and being rewarded because they’re front and center on the device that consumers have adopted as human appendage.  A study by Kleiner Perkins Caufield and Byers found the average user checks his or her phone close to 150 times per day. Its annual Internet Trends report found that the average person looks at his or her phone 110 times per day, and up to every six seconds in the evening.  During peak times this equates to once every six or seven seconds, with some users unlocking their devices up to 900 times over the course of a day.

And this is just the beginning. According to eMarketer, the number of smartphone users worldwide will surpass 2 billion in 2016, representing over one-quarter of the global population. “Inexpensive smartphones are opening new opportunities for marketing and commerce in emerging markets where many consumers previously had no access to the internet. Meanwhile, in mature, established markets, smartphones are quickly shifting the paradigm for consumer media usage and impressing the need for marketers to become more mobile-centric”

Leveraging the Mobile Trend in Loyalty

Lars Albright reported on this growing trend in an article published in AdAge, which offered the following advice for marketers who wish take advantage while the opportunity is still growing.

1. Personal choice is critical. Know what your users really want to receive and experience. A coupon for a purple sports drink is not a reward if the recipient likes coconut water to stay hydrated. Offer your users engaging rewards that suit their changing moods and needs from day-to-day and location-to-location.

2. Outline the rules of engagement. It’s clear that many people like some “surprise and delight” in their loyalty program — like a free upgrade when they check in to their favorite hotel. However, we’ve found that the majority of consumers don’t want their rewards program to be a 24/7 surprise. Communication is key. While you’re making your program easy, also make the rewards clear.

3. Understand the numbers. Besides those happy customers, the biggest win you’ll receive from your loyalty program is the rich data it provides. Respect it. And use what you learn to drive better business decisions.

Sensei Debates

Have mobile devices and mobile loyalty marketing finally come of age in North America? Or is it all still hype?

Demand – it is a fickle beast

pending

Guy Courtin was formerly Vice President and Principal Analyst at Constellation Research covering Matrix Commerce and how the Internet of Things drives the evolution of commerce.  Guy has over 15 years experience in the technology space and specifically in the supply chain space. Most recently he was the Vice President of Research at SCM World. Where he focused on the service providers that empowered supply chains. Prior to SCM World, Guy held numerous senior positions. He was responsible for product marketing at RSi, a retail supply chain solution provider. There managed RSi’s go to market strategy around their leading cloud based supply chain solutions. He also spear headed Progress Software’s supply chain group. Where he was responsible for driving revenue and market share as well…...

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Understanding customer taste and their buying patterns remains a tricky exercise. The story of L.L. Bean and their snow boots is a great example of how challenging it is to accurately predict demand. The Maine clothing and outdoor company is already sold out of their iconic boot. According to the Yahoo report, click here, there is already a 100,000 name long waiting list for the boot. Wow. Talk about a good problem to have, well maybe.

L.L. Bean cannot just ramp up their manufacturing, well in the long run they might be able to, but not fast enough to meet this pent up demand. Based on their meticulous manufacturing process, it takes half a year to train someone to manufacture the product, you cannot just bring on seasonal labor or outsource to a contract manufacturer to bolster your assembly line. So what should L.L. Bean do? It isn’t as if these shoes are a new product that vastly exceeded the expected demand. These shoes have been around, for what seems…forever.

No…you can’t wear this LL Bean boot

Their popularity is clearly back. I remember my classmates wearing these when I was in high school…and that was a long time ago. I never looked at them as a trendy item, not like what UGGs did or other brands. But clearly the product has regained popularity with the “younger people.” Meaning it is appealing to the 15 – 23 year old segment where trends can truly go viral. When you do a Google search for “L.L. Bean boots” you get sub searches “women,” “men,” “frat,” and “preppy.” Clearly it has mass appeal for the kids!

Should L.L. Bean have had better demand sensing? Could they have anticipated this upswing in orders months ago? Granted, based on the lead time they need with regards to adding manufacturing capacity, it might not have mattered. And how should they monitor this demand moving forward? Will there be this level of demand next winter? Or will some other brand become the cool footwear on campus next winter? This is one area of Matrix Commerce that calls for a high degree of digital sophistication as well as some good old fashion intuition.

Clearly this season is over capacity and there is very little L.L. Bean can do to accelerate the production. Moving forward, L.L. Bean needs to apply some savvy digital monitoring to better gauge the demand for 2015 and beyond. For example – what is the reaction of the shoes? Are they trending on social channels? How are they being discussed on social channels? Are the returns on pace with historic returns? Or are there more or less? L.L. Bean should monitor the fake and knock off products – imitation is the sincerest form of flattery. Companies that can produce a similar product will rush into the market if they believe the pent up demand cannot be met or if there is another layer of demand at a lower price point. These are all digital data points that L.L. Bean will have to pull back into their planning and forecasting engines to better manage their supply chain. Of course there is the other strategy of potentially keeping the supply low, to create exclusivity of the product. Hmmm makes one wonder.

But this latest Christmas season and fashion trend story reminds all of us, that accurately predicting future tastes and demands remain a fickle beast. The digital world allows us to cast a wider and more detailed net of what is going on, but we are far from being able to create an precise map for demand.

Now where are my boots…we are having a Nor’Easter here in Boston!

Weekly Recap - Weeks of November 28th and December 5th 2014

Holger Mueller

Vice President and Principal Analyst
Constellation Research

Holger Mueller is VP and Principal Analyst for Constellation Research for the fundamental enablers of the cloud, IaaS, PaaS and next generation Applications, with forays up the tech stack into BigData and Analytics, HR Tech, and sometimes SaaS. Holger provides strategy and counsel to key clients, including Chief Information Officers, Chief Technology Officers, Chief Product Officers, Chief HR Officers, investment analysts, venture capitalists, sell-side firms, and technology buyers.  Coverage Areas: Future of Work Tech Optimization & Innovation  Background: Before joining Constellation Research, Mueller was VP of Products for NorthgateArinso, a KKR company. There, he led the transformation of products to the cloud and laid the foundation for new Business Process as a…...

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Here are my takeaways of the two weeks:

And here is the content:

• IBM Datapower - now embedded in the BlueMix PaaS
• Continuent (now VMware) - good integration process, now looking at adding BigData capabilities
• BetterWorks - New approach to Performance Management
• Paycor - SMB focused HCM, Talent Management and Payroll provider
• HR Acuity - Looks at when things go back in an enterprise - what does HR need to do track, record  monitor and ultimately avoid.
• Ralllyteam - Addressing the challenge to find the right talent, a mix of Learning, Performance Management and Career Planning / Succession Planning.
• HashiCorp - Then under NDA - just releases now - Project Atlas - DevOps using 4 open source projects, the founders have launched in the last 3 years 
• KeyNexus - Key Management Service when working with Amazon AWS
• Sphere3D - MicroVisory VDI vendor, closed the storage vendor acquisition with Overland
• BigPanda - Applying BigData and Analytics to IT Ticket Management in the age of IoT - interesting approach.
• Progress Software - A UI briefing, good progress and bridging the both the Admin UI and the ultimately created product.
• Message Systems - Moving their systems to the cloud, new email automation product with SparkPost, using cloud, BigData and analytics.
• Informatica - Caught up on the Cloud Analytics product, interesting value add on top of the transformation capabilities
• IBM STG - Quarterly update with Tom Rosamilia, 2015 will be key with a mainframe refresh cycle and the dynamics around Power8
• Raet - Originally Dutch HR vendor, going more global starting with Europe and Latin America. 
• IDG Roadmap in Washington D.C. - I spoke about cloud and next generation applications.
• Jibe - Delivered what they had on the roadmap for 2014 - nice visualization of recruiting performance. 
• Infor - Attended the CIO Summit, was on a panel on IT trends and presented about People Science (or HCM) trends.

Google Hangouts: Too smart for privacy?

Steve Wilson

Former Vice President and Principal Analyst
Constellation Research

Steve Wilson is former VP and Principal Analyst at Constellation Research, leading the business theme Digital Safety and Privacy. His coverage includes digital identity, data protection, data privacy, cryptography, and trust. His advisory services to CIOs, CISOs, CPOs and IT architects include identity product strategy, security practice benchmarking, Privacy by Design (PbD), privacy engineering and Privacy [or Data Protection] Impact Assessments (PIA, DPIA). Coverage Areas: -  Identity management, frameworks & governance-  Digital identity technologies-  Privacy by Design -  Big Data; “Big Privacy”-  Identity & privacy innovation Previous experience: Wilson has worked in ICT innovation, research, development and analysis for over 25 years. With double…...

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An Engadget report today, "Hangouts eavesdrops on your chats to offer 'smart suggestions'" describes a new "spy/valet" feature being added to Google's popular video chat tool.

"Google's Hangouts is gaining a handy, but slightly creepy new feature today. The popular chat app will now act as a digital spy-slash-valet by eavesdropping on your conversations to offer 'smart suggestions.' For instance, if a pal asks 'where are you?' it'll immediately prompt you to share your location, then open a map so you can pin it precisely."

It's sad that this sort of thing still gets meekly labeled as "creepy". The privacy implications are serious and pretty easy to see in objective terms.

Google is evidently processing the text of Hangouts as they fly through their system, extracting linguistic cues, interpreting what's being said using Artificial Intelligence, extracting new meaning and insights, and offering suggestions in response. 

We need some clarification about whether any covert tests of this technology have been undertaken during the R&D phase. A company obviously doesn't launch a new product like this without a lot of research, feasibility testing, prototyping and testing. Serious work on Smart Suggestions would not start without first testing how it works in real life. So I wonder if any of this evaluation was done covertly on live data? Are Google researchers routinely eavesdropping on hangouts to develop the 'smart suggestions' technology?

If so, is such data usage covered by their Privacy Policy (you know, under the usual "in order to improve our service" justification)? And is usage sanctioned internationally in the stricter privacy regimes?

Many people have said to me I'm jumping the gun, and that Google would probably test the new Hangouts feature on its own employees. Perhaps, but given that scanning gmails is situation normal for Google, and they have a "privacy" culture that joins up all their business units so that data may be re-purposed almost without limit, I feel sure that running AI algorithms on text without telling people would be par for the course.  Let's not forget the company culture's carefree attitude to data as raw resource revealed by the way that Google engineer wrote a routine and loaded it into StreetView cars to collect unencrypyted home Wi-Fi traffic. 

In development and in operation, we need to know what steps are taken to protect the privacy of Hangouts data. What personally identifiable data and metadata is retained for other purposes? Who inside Google is granted access to the data and especially the synthtised insights? How long does any secondary usage persist for? Are particularly sensitive matters (like health data, financial details, corporate intellectual property etc.) filtered out?

This is well beyond "creepy". Hangouts and similar video chat are certainly wonderdful technologies. We're using them routinely for teaching, education, video conferencing, collaboration and consultation. The tools may become entrenched in corporate meetings, telecommuting, healthcare and the professions. But if I am talking with my doctor, or discussing patents with my legal team, or having a clandestine chat with a lover, I clearly do not want any unsolicited contributions from the service provider. More fundamentally, I want assurance that no machine is ever tapping into these sorts of communications, running AI algorithms, and creating new insights. If I'm wrong then Google could do what Apple did and publish an Open Letter clarifying their data usage practices and strategies. 

Come to think of it, if Google is running natural language processing algorithms over the Hangouts stream, might they be augmenting their gmail scanning the same way? Their business model is to extract insights about users from any data they get their hands on.  Until now it's been a crude business of picking out keywords and using them to profile users' interests and feed targeted advertising. But what if they could get deeper information about us through AI? Is there any sign from their historical business practices that Google would not do this? And what if they can extract sensitive information like mental health indications?  Even with good intent and transarency, predicting healthcare from social media is highly problematic as shown by the "Samaritans Radar" experience. 

Artificial Intelligence is one of the new frontiers. Hot on the heels of the successes of IBM Watson, we're seeing Natural Language Processing and analytics rapidly penetrate business and now consumer applications. Commentators are alternately telling us that AI will end humanity, and not to worry about it. For now, I call on people to simply think clearly through the implications, such as for privacy. If AI programs are clever enough to draw deep insights about us from what we say, then the "datapreneurs" in charge of those algorithms need to remember they are just as accountable for privacy as if they have asked us reveal all by filling out a questionnaire.

Not your father’s POS system

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Guy Courtin was formerly Vice President and Principal Analyst at Constellation Research covering Matrix Commerce and how the Internet of Things drives the evolution of commerce.  Guy has over 15 years experience in the technology space and specifically in the supply chain space. Most recently he was the Vice President of Research at SCM World. Where he focused on the service providers that empowered supply chains. Prior to SCM World, Guy held numerous senior positions. He was responsible for product marketing at RSi, a retail supply chain solution provider. There managed RSi’s go to market strategy around their leading cloud based supply chain solutions. He also spear headed Progress Software’s supply chain group. Where he was responsible for driving revenue and market share as well…...

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Here is something to tickle your retail supply chain – we are under 15 days until Christmas. Avoiding the debate over the mass commercialization of the holidays, the reality is that consumers will, or already have, started their shopping engines. With so many retailers dependent on good holiday sales, for example Lego moves 50% of their sales between Thanksgiving and Christmas, the ability to properly capture orders is vital.

The POS (point of sale) systems, whether in brick and mortar or on line, are the vital touch point between the consumer and the commerce supply chain. Like with the majority of technologies, this has been impacted by the digital wave. POS systems are not longer limited to the larger systems synonymous with the corner store – remember the ones where numbers would pop up once the large typewriter like buttons were pressed. These systems have evolved into a new range of sleek mobile devices, and those large legacy systems are now smarter. POS systems are also getting into greater areas and increasing their reach – supply chains need to craft strategies about how to take advantage of the new data as well as the new places POS systems will pop up.

For example:

• The POS systems in the air. Those us that have been flying long enough remember the days when we were served a meal and drinks as part of our overall plane ticket. Today if you want a scotch on the rocks and a can of Pringles, you need to pay for these items. Airlines have put mobile POS devices in the hands of their staff to take your payment. Rather than just using these as order taking machines, airlines like Delta Airlines have made these mobile devices a much more valuable part of their supply chain. Beyond just taking payments, the mobile devices are enabled to communicate about customer and maintenance issues. So if the passenger in seat 7a voices a legitimate complaint, Delta employees can use the POS system to give that passenger 10,000 miles. If a seat is found to be broken or an overhead can’t open, the flight attendants can use the system to communicate the problem and location to the destination airport and schedule the appropriate maintenance.
• Infusing retail into other entertainment channels. We have all used to having to walk through the store when we leave a museum, zoo, aquarium or other attraction. But what about the movies? Get ready for your phone to become part of a POS system for the movie theater. I am not speaking of the POS when you are ordering your over-sized tub of popcorn, but post movie viewing. For example – you go see the Transformer movie, once the movie is over as you are leaving the theater there are QR codes on promotional posters at the exit and even pop up kiosks where you can scan your phone to find where to get the latest Transformer toy. There could potentially be a 3D printer right there allowing you to get your item made in place. If you scan the product at the movie theater you may be given a discount – incentive consumer to make transaction at that point. Your portable POS systems – aka your smart phone – will have an app that allows for this to happen and could also communicate with the closest Target, WalMart or other retail channel that carries the item. Or even tie back to Amazon and have the eCommerce giant dispatch your item immediately.

Of course there remains a continued evolution in mobile POS, companies like Square and Apple are allowing anyone with a tablet and connectivity to run mobile POS systems. Retailers can start looking at these mobile POS systems as great data sources – where do most of the transactions happen on the store floor? Are there still locations for impulse purchase displays? Can you tie these mobile terminals into the inventory systems? A prospective buyer is looking for a specific piece of cookware at William Sonoma. The item is there but the consumer wants it in sky blue. Using the mobile terminal the associate helping that consumer can instantly scan the inventory at different stores, identify where an item can be secured and ship directly to the store or to the consumer. The mobile device should also be able to pull up the consumer’s profile: are they a loyal shopper? If so the associate should have the ability to waive shipping costs or expedite the product.

Supply chains need to think of their POS systems as Point of Service, not sales. In a world of Matrix Commerce, these are the intersection points between the consumer and the commerce supply chain where the digital reality has great impact. How companies take advantage of this will determine who leads and who is a laggard.