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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Anticipating Mobile World Congress 2015: Connectivity Trumps Mere Mobility

Jennifer Belissent, Ph.D.

 

infographic-imageWe are now only a few weeks away from Mobile World Congress, historically the pre-eminent event of the mobile industry and now one of the largest global events across all industries. Last year’s even attracted almost 90,000 attendees from over 200 countries.  The event draws representatives from mobile operators, device manufacturers, technology providers, vendors, content owners and governments from across the world.  Executives from all industries pay attention to products demonstrated and announcements made.  While “mobile” remains in the event title, last year’s event marked a changing of the guard:  The large presence of car manufacturers and the buzz around Facebook reflected that shift away from the event’s telecom roots.  This year that shift will be even more pronounced as the reign of mobility gives way to the new rule of connectivity.  Yes, we are mobile but the key is that while we are roaming the halls at work or the streets of a foreign city, we remain connected to the people and things we want and need to interact with. 

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Apache Spark's Marriage To Hadoop Will Be Bigger Than Kim And Kanye

Mike Gualtieri
  • Apache Spark is an open source cluster computing platform designed to process big data as efficiently as possible. Sound familiar? That's what Hadoop is designed to do. However, these are distinctly different, but complementary, platforms. Hadoop is designed to process large volumes of data that lives in an Hadoop distributed file system (HDFS). Spark is also designed to process large volumes of data, but much more efficiently than MapReduce, in part, by caching data in-memory. But, to say that Spark is just an in-memory data processing platform is a gross oversimplification and a common misconception. It also has a unique development framework that simplifies the development and efficiency of data processing jobs. You'll often hear Hadoop and Spark mentioned in the same breath. That's because, although they are independent platforms in their own right, they have an evolving, symbiotic relationship. Application development and delivery professionals (AD&D) must understand the key differences and synergies between this next-generation cluster-computing power couple to make informed decisions about their big data strategy and investments. Forrester clients can read the full report explaining the difference and synergies here: Apache Spark Is Powerful And Promising
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With So Much Commoditization In The CRM Landscape, How Do You Choose The Right CRM?

Kate Leggett

I have been working on evaluating a range of vendors for the CRM Wave which will be published in March. What I am seeing is that core CRM capabilities are very, very commoditized. Just about every vendor can check the box on core SFA and marketing automation features. There's a bit more difference if you look at customer service capabilities over social, digital and self service channels but all evaluated vendors handle core case management adequately. So what does this mean to the buyer who is looking for a CRM?

  • Choose a solution that is right-sized for your business. Some CRM vendors target the complex, global enterprise. These solutions are typically heavyweight and replete with features that are often customized to meet specific business requirements. Other CRM vendors target small to midsize organizations with a breath, but not necessarily a depth of capabilties. For smaller organizations too many features are often an overkill for organizations with lightweight needs, so make sure you understand the target user of the CRMs under evaluation.
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