What Qualities Do Great Enterprise Application Developers Possess?

Mike Gualtieri

What are you doing on October 16th and 17th? That's when Forrester's Forum for Application Development & Delivery Professionals will be held in Chicago. Join us this year for lively session, networking, and discussions about building software that powers your business. The agenda is hot including a session from me on The Unstoppable Momentum Of Hadoop and guest speaker from McDonald's on How McDonald's Plans To Leverage Its New Digital Platform To Revolutionaize Customer Experiences.

We have lots of fun at these events too. Check out this video of last year's event where we grabbed both clients and analysts and asked them an important, and to some, philosophical question: What Makes A Great Application Developer? See if you'd answer the same way.

Lose The RFP Mindset When Selecting A CRM Solution

Kate Leggett

The traditional RFP-driven vendor selection process is heavyweight and often has undesirable outcomes:

  • The RFP process it time- and resource-consuming. Forrester estimates that CRM vendor selection projects take six to 12 months to complete. The effort involved to compile detailed requirements often produces something resembling a programming specification rather than a concise statement of business process needs.
  • Outcomes are often undesirable. The more onerous the RFP process, the more likely it is that some of the more viable candidate vendors will opt out  after determining sales considerations costs and reading the tea leaves of the competitive situation. When this occurs, mediocre or unqualified vendors may be the only ones left to choose from.
  • Failure to differentiate among mature products or identify innovators. RFPs only include requirements that buyers can envision now and generally look quite similar to capabilities that vendors can deliver in current releases rather than more visionary features that don't exist in many products today.
  • Vendors gain the upper hand. Vendors often have much more experience with RFPs than the buyer. A cagey vendor will look to circumvent the formal process by influencing executive decision-makers informally or disrupting the process if it is not going its way. Slick sales presentations and RFP responses often gloss over product weaknesses.
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Developers Hold The Key To Your Business’ Brand

Stephen Powers

By now, you all know that in order for your company to win, it needs to be customer obsessed. But how do you support that obsession from a technical standpoint? It takes innovation, and the key to innovation is software. In the 21st century, successful brands will rise and fall based on software. Because of that, developers have never been more important than they are today, which is why we’re so excited about the theme of this year’s Forrester Forum For Application Development & Delivery Professionals Build Software That Powers Your Business. 

This Forum will help you identify brand new software opportunities and run with them. It will hit on the must-have competencies that will empower application development and delivery leaders to execute on their company’s engagement strategies. This includes accelerating development processes, creating digital experiences, reaching mobile customers, and exploiting analytics and big data. Forrester analysts will deliver forward-thinking content while industry specialists – from companies such as McDonald’s, Mastercard, and GE Capital - will provide insight into some real and revolutionary new business approaches that are relevant to you right now.

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Nginx And Mobile Are Marching Together Into Internet History

Ted Schadler

[This is an update from a June 2013 post. Also see the new book I wrote with Julie Ask and Josh Bernoff, The Mobile Mind Shift.]

The techologist in me (still) loves getting the monthly Web server report from Netcraft.com. Astounding statistics like the number of registered public Web sites (998 million in August, up from 23,000 in 1995) and active Web sites (179 million) put into the context of history shows simply and directly just how deeply the Internet has penetrated our lives over the last 19 years.

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My Three Assumptions For Why The Next Generation Of SW Innovation Will Be Cognitive!

Diego Lo Giudice

I am just back from the first ever Cognitive Computing Forum organized by DATAVERSITY in San Jose, California. I am not new to artificial intelligence (AI), and was a software developer in the early days of AI when I was just out of university. Back then, if you worked in AI, you would be called a SW Knowledge Engineer, and you would use symbolic programming (LISP) and first order logic programming (Prolog) or predicate calculus (MRS) to develop “intelligent” programs. Lot’s of research was done on knowledge representation and tools to support knowledge based engineers in developing applications that by nature required heuristic problem solving. Heuristics are necessary when problems are undefined, non-linear and complex. Deciding which financial product you should buy based on your risk tolerance, amount you are willing to invest, and personal objectives is a typical problem we used to solve with AI.

Fast forward 25 years, and AI is back, has a new name, it is now called cognitive computing. An old friend of mine, who’s never left the field, says, “AI has never really gone away, but has undergone some major fundamental changes.” Perhaps it never really went away from labs, research and very nich business areas. The change, however, is heavily about the context: hardware and software scale related constraints are gone, and there’s tons of data/knowledge digitally available (ironically AI missed big data 25 years ago!). But this is not what I want to focus on.

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The Good The Bad And The Ugly Of Enterprise BI

Boris Evelson
Unified information architecture, data governance, and standard enterprise BI platforms are all but a journey via a long and winding road. Even if one deploys the "latest and greatest" BI tools and best practices, the organization may not be getting any closer to the light at the end of the tunnel because:
  • Technology-driven enterprise BI is scalable but not agile. For the last decade, top down data governance, centralization of BI support on standardized infrastructure, scalability, robustness, support for mission critical applications, minimizing operational risk, and drive toward absolute single version of the truth — the good of enterprise BI — were the strategies that allowed organizations to reap multiple business benefits. However, today's business outlook is much different and one cannot pretend to put new wine into old wine skins. If these were the only best practices, why is it that Forrester research constantly finds that homegrown or shadow BI applications by far outstrip applications created on enterprise BI platforms? Our research often uncovers that — here's where the bad part comes in — enterprise BI environments are complex, inflexible, and slow to react and, therefore, are largely ineffective in the age of the customer. More specifically, our clients cite that the their enterprise BI applications do not have all of the data they need, do not have the right data models to support all of the latest use cases, take too long, and are too complex to use. These are just some of the reasons Forrester's latest survey indicated that approximately 63% of business decision-makers are using an equal amount or more of homegrown versus enterprise BI applications. And an astonishingly miniscule 2% of business decision-makers reported using solely enterprise BI applications.
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Introducing a new Senior Analyst

Hello, world. Welcome to my first blog as a new Senior Analyst serving Application Development & Delivery professionals.

I come to Forrester after working in the Solution Marketing and Corporate Marketing groups at a large customer service software provider. That role put me in touch with contact center technology buyers and the overburdened folks responsible for actually making great customer service happen every day. I saw close up the impact of the age of the customer on the thinking, processes, behavior, and technology choices of contact center professionals around the world. They are facing a world in which consumers are much less willing to settle for mediocre and impersonal experiences when dealing with customer service organizations. As consumers we all want effortless service delivered via whatever channel is most convenient at the moment, and we want companies to know just the right amount of information about us, but not too much, at the moment of the interaction.

That is a very tough nut to crack for contact center managers, supervisors, and agents. My research coverage will primarily focus on two areas that can help contact center pros begin to address these issues:

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Planning Your Big Data Strategy: Five Keys To Success

Martha Bennett

To compete in the age of the customer, it’s essential to make the most of the data you have access to, whether it’s from internal or external sources. For most organizations, this implies a need to review and challenge existing approaches to how they capture, process, and use data to support decision-making. But it’s important first of all to move beyond a technology-centric view of big data. This is why at Forrester, we define big data as:

The practices and technologies that close the gap between the data available and the ability to turn that data into business insight.

Moving beyond a technology-centric view doesn’t mean, however, that a bottom-up, technology-led approach to big data strategy won’t work. After all, it’s often the case that business executives can’t see the potential of a technology until they’ve seen it in action. A bottom-up approach also provides the opportunity to acquire technical skills, and gain an understanding of what needs to be done to integrate new technologies with existing systems (even if it’s just at the level of getting the data out – often easier said than done). But a pilot project or proof-of-concept demonstrating the “art of the possible” in a business context is different from implementing a Hadoop cluster and expecting the business side to start asking for projects.

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Closing The Experience Gaps Requires A New Technology Architecture And Philosophy

Ted Schadler

Forrester’s Customer Experience Index (CXi) research reveals a shocking business result: Over five years, CXi leaders outperformed the S&P with 43% stock growth, while CXi laggards had negative returns of -34%. (See this Forrester report to learn about our new customer experience index.)

As a result, firms are in an arms race to mobilize their services, deliver new digital capabilities, and delight customers on every step of their journey. eBusiness, marketing, and customer experience teams are eagerly adopting new software to deliver these digital experiences. At times, they chose a conscious uncoupling from the CIO’s team in order to move quickly and stay ahead of customers’ expectations.

Unfortunately, the mismatch of customer-facing teams scrambling to build new digital services while CIOs and their teams hunker down to cut cost and risk has caused a disconnect on the role of technology management in delivering great experiences. In a new Forrester report, Closing The Experience Gaps, my colleague John C. McCarthy and I interviewed more than 35 companies and analyzed survey results from 3,502 US consumers, we uncovered this misalignment and identified the four experience gaps that result (see Figure 1).

Figure 1 Experience Delivery Requires A New Architecture And Philosophy

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Lost In Data Translation? Forrester's Data Taxonomy To The Rescue

Boris Evelson
  • When it comes to data technology, are you lost in translation? What's the difference between data federation, virtualization, and data or information-as-a-service? Are columnar databases also relational? Does one use the same or different tools for BAM (Business Activity Monitoring) and for CEP (Complex Event Processing)? These questions are just the tip of the iceberg of a plethora of terms and definitions in the rich and complex world of enterprise data and information. Enterprise application developers, data, and information architects manage multiple challenges on a daily basis already, and the last thing they need to deal with are misunderstandings of the various data technology component definitions.
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