Open Data And Trust Play An Important Role In Emerging Digital Ecosystems

Dan Bieler

Open data is critical for delivering contextual value to customers in digital ecosystems. For instance, The Weather Channel and OpenWeatherMap collect weather-related data points from millions of data sources, including the wingtips of aircraft. They could share these data points with car insurance companies. This would allow the insurers to expand their customer journey activities, such as alerting their customers in real time to warn them of an approaching hailstorm so that the car owners have a chance to move their cars to safety. Success requires making logical connections between isolated data fields to generate meaningful business intelligence.

But also trust is critical to deliver value in digital ecosystems. One of the key questions for big data is who owns the data. Is it the division that collects the data, the business as a whole, or the customer whose data is collected? Forrester believes that for data analytics to unfold its true potential and gain end user acceptance, the users themselves must remain the ultimate owner of their own data.

The development of control mechanisms that allow end users to control their data is a major task for CIOs. One possible approach could be dashboard portals that allow end users to specify which businesses can use which data sets and for what purpose. Private.me is trying to develop such a mechanism. It provides servers to which individual's information is distributed to be run by non-profit organizations. Data anonymization is another approach that many businesses are working on, despite the fact that there are limits to data anonymization as a means to ensure true privacy.

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Big Data, Welcome To Those Awkward Teenage Years

Brian  Hopkins

Just a few years ago, when big data was associated primarily with Hadoop, it was like a precocious child…fun for adults, but nobody took it seriously. I’m attending Strata in San Jose this February, and I can see things have changed. Attendance doubled from last year and many of the attendees are the business casual managers – not the blue jeaned developers and admins of days gone by. Big data is maturing and nobody takes it lightly anymore.

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Start Planning To Provide Social Customer Support Beyond Twitter and Facebook

Ian Jacobs

Industry analysts travel—a lot. It is, therefore, no surprise that I care deeply about airlines’ frequent flyer programs and track the changes to those programs as closely as baseball obsessives track star players’ slugging percentages. When I want information on what these changes mean practically in my situation (Will the new loyalty program make it harder for a 75k+ elite member looking to book a companion ticket’s upgrade on an alliance partner airline, for example), I typically do not turn directly to the airline. Instead, I log on to Flyertalk, a forum that bills itself as “the largest expert travel community.” The forum—populated by thousands of frequent fliers far more obsessive than I will ever be—consistently houses discussions of exactly the thing I want to know.

The lion’s share of people answering questions on Flyertalk and other forums like it—Cruisecritic for the cruising fans, TripAdvisor for travel and hospitality broadly, AutomotiveForums for car enthusiasts, etc.—are other consumers, albeit well-informed ones. But these non-brand controlled communities provide opportunities to brands to differentiate themselves through service.  Because affinity communities have barriers to entry, including registrations and jargon, community members are usually deeply interested in the topic at hand. In communities that regularly discuss brands, these customers are also more likely to be exactly the type of high-value customers that companies want to provide with great customer experiences. But brands need to decide when and how to engage customers in these forums they do not control.

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Big Changes In Information-related Roles And Processes -- Evolution Or Apocalypse?

Gene Leganza
It’s not news that business user self-service for access to information and analytics is hot. What might not be as obvious is the overhaul of information-related roles that is happening now as a result. What’s driving this? The hunger for data (big, fast, and otherwise) to feed insights, very popular data visualization tools, and new but rapidly spreading technology that puts sophisticated data exploration and manipulation tools in the hands of business users. 
 
One impact is that classic tech management functions such as data modeling and data integration are moving into business-side roles. I can’t help but be reminded of Bill Murray’s apocalyptic vision from “Ghostbusters:” “Dogs and cats, living together… mass hysteria!” Is this the end of rational, orderly data management as we know it? Haven’t central tech management organizations always seen business-side tech decision-making (and purchasing, and implementation) as “rogue” behavior that needed to be governed out of existence? If organizations have trouble now keeping data for analytics at the right level of quality in data warehouses, won’t all this introduction of new data sources and data lakes and whatnot just make things worse?
 
Well, my answers are “no,” “yes,” and “no” in that order. The big changes that are afoot are not the end of order and even though “business empowerment” translates to “rogue IT” in some circles, data lakes/hubs and the infusion of 3rd party data have actually been delivering on their promise of faster, better business insights for the organizations doing it right. 
 
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This Time, AI Is Truly Here To Help Build Intelligent Applications

Diego Lo Giudice

What’s taken artificial intelligence (AI) so long? We invented AI capabilities like first-order logical reasoning, natural-language processing, speech/voice/vision recognition, neural networks, machine-learning algorithms, and expert systems more than 30 years ago, but aside from a few marginal applications in business systems, AI hasn’t made much of a difference. The business doesn’t understand how or why it could make a difference; it thinks we can program anything, which is almost true. But there’s one thing we fail at programming: our own brain — we simply don’t know how it works.

What’s changed now? While some AI research still tries to simulate our brain or certain regions of it — and is frankly unlikely to deliver concrete results anytime soon — most of it now leverages a less human, but more effective, approach revolving around machine learning and smart integration with other AI capabilities.

What is machine learning? Simply put, sophisticated software algorithms that learn to do something on their own by repeated training using big data. In fact, big data is what’s making the difference in machine learning, along with great improvements in many of the above AI disciplines (see the AI market overview that I coauthored with Mike Gualtieri and Michele Goetz on why AI is better and consumable today). As a result, AI is undergoing a renaissance, developing new “cognitive” capabilities to help in our daily lives.

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Analyst Spotlight Podcast With John Kindervag

Stephanie Balaouras

It's February: time for another S&R Analyst Spotlight Podcast! This month, Forrester VP, principal analyst, and Zero-Trust creator, John Kindervag, joins us. Listen in to learn more about John and his research. While you're at it, be sure to check out our First Look newsletter, which contains an interview with John along with links to his most recent and upcoming research. If you are not already signed up for our First Look newsletters, please email srfl@forrester.com. 

New to the podcast and want to hear more?  Check out our past interviews with analysts Ed Ferrara, Heidi Shey, Renee Murphy, and Tyler Shields.

Click below to listen to the podcast!

John Kindervag Image

To download the mp3 version of the podcast, click here.

Five Shades Of Grey (How software buyers and license managers should be compliant without being submissive).

Duncan Jones

Any procurement or asset management professionals who have seen the new movie based on E.L.James’ best selling novels may have noticed the similarity between the eponymous antihero and a license management services consultant.  Mr. Grey will use charm and threats to persuade you to run his audit scripts on your network. You have an obligation to demonstrate your compliance with the software license terms, but that doesn't mean that you have accept his opinion about what those terms actually mean.

Sources inside some large software companies tell me that license audits generate 20% to 30% of their license revenue. Although a lot of that will represent deliberate or reckless under-licensing, many of the disputes that I hear about involve software salespeople abusing some licensing shades of grey to pressurize customers into paying them money. It is difficult to predict how a court will interpret nineties contract language in the current technology context, so many companies pay up rather than risk a compliance lawsuit. Here are five questions of interpretation that no lawyer can answer:

  1. Who is really using my software? I continue to hear risible interpretations of ‘use’ and ‘access’, such as the software company that claimed motorists were users because they saw output from its database when they drove past an electronic road sign. I’ve previously suggested a standard interpretation of use in my report Let's Clear Up The "Indirect Access" Mess based on the concept of interaction - i.e. both input by a user and output by the software. Enterprises need to persuade their vendors to accept this interpretation urgently, otherwise the Internet Of Things will bankrupt you.
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Cognitive Computing Is Changing Healthcare, Slowly

Skip Snow

Artificial intelligence’s (AI's) reputation is having a significant reputational uplift. We have an Academy Award-nominated film, The Imitation Game ( http://theimitationgamemovie.com/), about arguably the father of AI, or even modern computing, that advocates passionately for the power of AI. We have IBM founding a new division, "Watson," based on the premise that cognitive computing can in fact be a profitable cloud-based business service that IBM offers.

Looking at my own domain of punditry "software for healthcare," I have to ask what, if anything, does all of this AI thaw means to the technology, operational, financial, and marketing executives in Forrester’s client base? To answer that we have to look what products or solutions have entered the marketplace that are capable of changing the core models of healthcare.

After over a year of research, we are capable of saying that cognitive computing is important to healthcare and is more than a science project. What we have found is that there is a divide between big health care business and smaller ones. The big businesses, the ones that are true centers of excellence in the provider, payer, and drug research arena are using the advances of cognitive computing machine learning and big data to innovate in fundamental ways.

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Ensure Brand Longevity With A Sustainable (Technology) Strategy

Sophia Vargas

While green and sustainable initiatives haven’t traditionally been a high priority for business technology decision makers, the growing urgency of climate change continues to place scrutiny on large resource users. In today’s hyper competitive marketplace, your customers, employees, partners, and possibly regulators are demanding more transparency in company operations and products.

In reaction to this trend, many organizations have already started to embrace sustainable initiatives as an opportunity to showcase creativity, technological achievement, as well as their brand’s commitment to the environment and broader community. In order to investigate this trend, my colleague and principal analyst Jim Nail and I set out to better understand the technology, processes and marketing strategy behind corporate sustainability initiatives.

The resulting report “Bolster Your Brand With A Greener Technology Ecosystem” outlines the buisness case and technology roadmap for sustainable initatives, intended to help your organization achieve and communicate operational excellence, while simultaneously providing further differentiation for your brand and organization.

The unexpected appendix

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3 Ways Data Preparation Tools Help You Get Ahead Of Big Data

Michele Goetz

The business has an insatiable appetite for data and insights.  Even in the age of big data, the number one issue of business stakeholders and analysts is getting access to the data.  If access is achieved, the next step is "wrangling" the data into a usable data set for analysis.  The term "wrangling" itself creates a nervous twitch, unless you enjoy the rodeo.  But, the goal of the business isn't to be an adrenalin junky.  The goal is to get insight that helps them smartly navigate through increasingly complex business landscapes and customer interactions.  Those that get this have introduced a softer term, "blending."  Another term dreamed up by data vendor marketers to avoid the dreaded conversation of data integration and data governance.  

The reality is that you can't market message your way out of the fundamental problem that big data is creating data swamps even in the best intentioned efforts. (This is the reality of big data's first principle of a schema-less data.)  Data governance for big data is primarily relegated to cataloging data and its lineage which serve the data management team but creates a new kind of nightmare for analysts and data scientist - working with a card catalog that will rival the Library of Congress. Dropping a self-service business intelligence tool or advanced analytic solution doesn't solve the problem of familiarizing the analyst with the data.  Analysts will still spend up to 80% of their time just trying to create the data set to draw insights.  

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