Customer Obsession Will Remake App-Development Tools

John R. Rymer
Application-development leaders shifting to modern techniques are like acrobats performing above a flimsy net. The tools and technologies they need to support the planning, execution, and evaluation of customer-focused applications just aren't widely available yet. The biggest gaps are in portfolio management, test-and-learn development environments, and digital application platforms. This report provides an overview of the tools and technologies application-development leaders need. 
 
Our key findings: 
 
  1. Organizing Principles For Tools: Composition, Collaboration, Continuous Delivery. An emphasis on composition, collaboration, and continuous delivery makes modern application development different from prior eras. Tools and technologies must support with equal facility apps, projects, and assets living in public clouds and private data centers. They must also foster contextual collaboration in near real time to enable rapid, continuous delivery.
  2. Tools Reflect The Needs Of Cross-Skilled "Two-Pizza” Teams. Tools for modern application development and delivery reflect the convergence of roles across the old boundaries between product management, design, development, QA, and operations. Not all market-leading products act on this reality; they still address siloed roles as before. Thus, application-development teams will look to new tools — even command-line editors — and open source projects to improve project flow.
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Start Caring About VR And 360-Degree Video

Nick Barber

At the International CES mega show in Las Vegas, virtual reality hardware makers moved the needle on both consumption and creation devices for formats like VR and 360-degree video. Specifically in the area of 360 video creation technology, we saw some impressive cameras at CES.


Insta360 Pro debuted
 an 8K camera (left) that can also shoot 4K video at 100 frames per second. Slow mo, high res VR, anyone? The Insta360 also employs new H.265 encoding, which can deliver better video quality at the same bitrate versus H.264 compression. The camera is priced at $3,000, which is steep, but much more competitive than the $60,000 Nokia Ozo.

Ricoh added to its lineup of cameras with the Theta R, which can livestream in 2K resolution at 30 frames per second for up to 24 hours.

At $800 the Vuze Camera will finally begin to ship in March. Its compact size and price point will be good for brands and businesses that want to dip their toes into new content

VR and 360 content can be a powerful tool for companies. For example, Delta used a 360 image to show off its new Delta Premium offering. It drove 2,700 shares and 16,000 engagements. Click on the post below to see it in 360.

The hardware for VR and 360 video is one piece, but the technical and production component is equally as important. When it comes to producing 360 video, remember:

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Confusion And Vendor Adolescence Stalls AI Innovation In Financial Services

Craig Le Clair

 

AI is a hot topic in financial services. And its easy to see why. Increasing margins on transactions, decimated by compliance costs and low interest rates, reaching new market segments, and automating routine tasks, makes AI innovation attractive. And in one sense, FinServ has always been about algorithmic innovation. There is no higher potential ROI than beating the market. Advanced analytics for program trading have been banging away at this goal for decades, with a rich base of advances.

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How self-service technology is changing the contact center job landscape

Ian Jacobs

Over the holidays, I was a guest on the Modern Customer Podcast, a wonderful podcast hosted by Forbes’ blogger Blake Morgan. She describes the podcast as providing “surprising and counter-intuitive insights on customer experience, social customer service and content.” No pressure there, then. During our episode, Blake and I discussed the ways that increased usage of self-service has begun to dramatically transform the jobs of customer service personnel and contact center agents.

At heart, my argument goes like this: customers have begun to use, and in some cases even prefer, non-agented interactions. They use knowledgebases, FAQs, mobile customer self-service, chatbots, and peer-to-peer communities in increasing numbers. This means that:

  • Because self-service solves many of the simpler issues that customers have, the inquiries that do make it through to contact center agents are the more complex, difficult, or relationship-dependent ones. So, contact center agents now need to be prepared for solving harder problems than in the past.
  • Because most customers that actually do reach a contact center agent will have tried to self-serve and failed, they will more frustrated than they were in the past. In a world where the phone and even chat are actually escalation channels, agents start three steps back by the time they say the word, “Hello.”
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Divide (BI Governance From Data Governance) And Conquer

Boris Evelson

Stop! Before you invest even 10 minutes of your precious time reading this blog, please make sure it's really business intelligence (BI) governance, and not data governance best practices, that you are looking for. BI governance is a key component of data governance, but they're not the same. Data governance deals with the entire spectrum (creation, transformation, ownership, etc.) of people, processes, policies, and technologies that manage and govern an enterprise's use of its data assets (such as data governance stewardship applications, master data management, metadata management, and data quality).  On the other hand, BI governance only deals with who uses the data, when, and how.

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Findings From The Forrester CRM Wave For Enterprise Organizations

Kate Leggett

The CRM market serving the large enterprise is mature. The market has consolidated in the past five years. For example, Oracle has built its customer experience portfolio primarily by acquisition. SAP, like Oracle, aims to support end-to-end customer experiences and has made acquisitions — notably, Hybris in 2013 — to bolster its capabilities. Salesforce made a series of moves to strengthen the Service Cloud. It used this same tactic to broaden its CRM footprint with the acquisition of Demandware for eCommerce in 2016.

These acquisitions broaden and deepen the footprints of large vendors, but these vendors must spend time integrating acquired products, offering common user experiences as well as common business analyst and administrator tooling — priorities that can conflict with core feature development.

What this means is that these CRM vendors increasingly offer broader and deeper capabilities which bloat their footprint and increase their complexity with features that many users can't leverage. At the same time, new point solution vendors are popping up at an unprecedented rate and are delivering modern interfaces and mobile-first strategies that address specific business problems such as sales performance management, lead to revenue management, and digital customer experience.

The breadth and depth of CRM capabilities available from vendor solutions makes it increasingly challenging to be confident of your CRM choice. In the Forrester Wave: CRM Suites For Enterprise Organizations, Q4 2016. we pinpoint the strengths of leading vendors that offer solutions suitable for enterprise CRM teams. Here are some of our key findings:

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Do EA Tools Enable EA Pros To Deliver Value To Their Stakeholders?

Gordon Barnett

As enterprise architecture (EA) practices mature and the demand for EA services grows, interest in enterprise architecture management suites (EAMS) continues to also grow. A lot has happened to the EAMS market since the September 2015 Forrester EAMS Wave, from divestures by certain major players (e.g., IBM) to takeovers (Planview of Troux, Erwin of Casewise). Before making a choice of EAMS tool, EA leaders need to take a step back and assess how they can demonstrate value, and then select the most appropriate toolset.

In Forrester’s most recent research, we have identified that although there are approximately 60 EAMS tools vendors, they can be categorized as follows:

·         Architecture modeling tools (AM). Vendors in this category aim to capture the architectural landscape and the relationships between them.

·         Technology asset management tools (TAM). This is a further evolution of the AM tools and includes additional functionality that is typically found in CMDB type solutions, but it also includes the management of technology projects.

·         IT portfolio management tools (ITPM). This category of tools is less focused on the asset management and more in line with capturing technology strategy, the associated target architecture state, and the portfolio that will deliver the strategic objectives. Additionally, there will be significant features to enable investment decisions to be made and portfolio scenarios to be analyzed.

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Do More With Less: Predictive Analytics For I&O

 

Moore’s Law was bound to catch up with us. Loosely applied, it says that technology grows more complex every year.   Human brains do not.   People can’t keep up with monitoring, debugging, and managing today’s technology.  Users’ rising expectations make it even worse:  they want features and fixes in minutes, not days or weeks.  Technology may soon get away from us.  

The American comic strip character Pogo put it this way:  “we have met the enemy and he is us.”  In this case, our enemy is also our best ally.  Surely we can harness technology’s power to help us keep it under control.   We can, we are, and we will.  Predictive analytics, common for decades in other industries, is now a growing force for monitoring and managing business technology, and has the potential to put us back in control of our runaway technology.

The least sophisticated analytics predicts what instrumentation is appropriate for a server based on what software it’s running or what kinds of network traffic is going in or out.  For example, is database software found, or are SQL queries going in and out?  This analytics drives automation that reduces manual administrative work.

Moderately sophisticated analytics predicts trouble based on simple trends like CPU utilization rising, memory consumption rising, or free storage declining; and drives capacity planning before a resource crisis occurs.

Really sophisticated analytics watches multi-variate trends such as cycles of high user demand (for example monthly sales campaigns) coupled with performance expectations and resource constraints, to drive automated resource scale-up (to sustain best performance) or scale-down (to reduce over-provisioning costs).

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Open Source APM Gains Momentum

Operations teams value stability.  Uptime is golden.  So it’s no surprise that operations teams buy finished, complete, documented, supported tools from vendors they can hold accountable.  Ops people already have their hands full dealing with complex apps, infrastructure, and users – they don’t need to be hassling with flaky do-it-yourself tools.  Even so, most operations teams still wind up with a mixture of tools from multiple vendors plus home-built integrations and scripts.

Development teams, on the other hand, are developers.  If they need a tool to do exactly what they need, they’ll build one – and share it with their friends.  As agile development has grown into continuous integration and continuous deployment, developers collaboratively created tools to automate tedious tasks and accelerate the application lifecycle.  Customer obsession relies on speed, and speed relies on automation.  The open source collaborative model has been very effective at creating the tools that support high frequency agile releases.   

The DevOps phenomenon brings together these two teams and their divergent cultures.  Yes, stability still matters; but what matters more in the age of the customer is agility through the entire software lifecycle, including the ops portion of release, deployment, and support.  The success of collaborative open source tools in development suggests that operations may be headed the same way.   And in the last year a lot more of my clients are asking about open source APM tools as an alternative to commercial solutions.  I’m also seeing APM vendors more involved in contribution, participation, and use of open source.  As Sam Cooke sang, “a change is gonna come.” 

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DevOps The Code To Delivering With Velocity, Quality And Agility

Robert Stroud

Every business today is under pressure from a startup that is disrupting their traditional market. We have seen this in the taxi industry with Uber[i], ATOM Bank is revolutionizing banking[ii] and Airbnb the hotel industry.[iii] The overused statement that today every business is a software business, is resonating in every industry and we are all under pressure to not only deliver faster, we must do so with quality and add value to our respective businesses.

To achieve velocity, organizations are turning to DevOps in their cultural and technology transformation. In my recent report, “How To Deliver Services With Quality, Agility, And Value,” I look at these issues and discuss how to pragmatically assess your DevOps journey.

CALMSS A Model For Success.

Delivering faster requires a new model, one which features smaller changes driven through faster high-quality release cycles that leverage end to end automation. To guide the transition, infrastructure and operations (I&O) pros should employ the CALMSS  competency model (Culture, Automation, Lean, Measurement and management, Sharing, and Sourcing). All team members who are engaged in the product life cycle – from individual contributors to the executive team – must master these competencies. I&O pros must also use benchmarks to assess their progress and to maintain or adjust their current DevOps competencies accordingly.

Automation: “The Weakest Link” To DevOps Success

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