Pick The Best Video Platform For Customer Or Employee Engagement

Philipp Karcher
To capture, manage, and deliver live and on-demand video you need a video platform. Selecting the right platform helps companies maximize the impact of video on customer and employee experiences. 
 
Enterprises looking at applications for video across marketing, corporate communications, and training need to consider products in multiple categories. Our just-published Forrester Wave on Enterprise Video Platforms and Webcasting evaluates the 16 leading providers focused on live presentations with slides and publishing video on demand. We included BrightTALK, Cisco, InXpo, Kaltura, Kontiki, Kulu Valley, MediaPlatform, Nasdaq, On24, Panopto, Polycom, Qumu, Ramp, Sonic Foundry, TalkPoint (PGi), and VBrick in the evaluation.
 

 
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Beyond Big Data's Vs: Fast Data Is More Than Data Velocity

Michele Goetz

When you hear the term fast data the first thought is probably the velocity of the data.  Not unusual in the realm of big data where velocity is one of the V's everyone talked about.  However, fast data encompasses more than a data characteristic, it is about how quickly you can get and use insight.  

Working with Noel Yuhanna on an upcoming report on how to develop your data management roadmap, we found speed was a continuous theme to achieve. Clients consistently call out speed as what holds them back.  How they interpret what speed means is the crux of the issue.

Technology management thinks about how quickly data is provisioned.  The solution is a faster engine - in-memory grids like SAP HANA become the tool of choice.  This is the wrong way to think about it.  Simply serving up data with faster integration and a high performance platform is what we have always done - better box, better integration software, better data warehouse.  Why use the same solution that in a year or two runs against the same wall? 

The other side of the equation is that sending data out faster ignores what business stakeholders and analytics teams want.  Speed to the business encompasses self-service data acquisition, faster deployment of data services, and faster changes.  The reason, they need to act on the data and insights.    

The right strategy is to create a vision that orients toward business outcomes.  Today's reality is that we live in a world where it is no longer about first to market, we have to be about first to value.  First to value with our customers, and first to value with our business capabilities.  The speed at which insights are gained and ultimately how they are put to use is your data management strategy.  

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Embrace Shared Services To Improve Outcomes–Not Only For Cost Savings

Jennifer Belissent, Ph.D.

The perennial call for public sector reform has not slackened. The pain of austerity measures and the pressures for increased efficiency heighten that call.  And, the hype around “smart cities” amps up the pressure for municipal leaders faced with decisions about which problems to attack first, and which tools are most appropriate.  But most organizations are not starting from a clean slate. That’s exactly the issue. In most cases we’re talking about reform, about doing things differently, not starting from scratch. 

When we asked government leaders what their top priorities are, improving the customer experience comes in on top: 68% report the customer experience is either a high or critical priority.  But reducing costs is right up there with it. That’s the age-old do-more-with-less mantra.  And, from a technology perspective their top priority is to upgrade or replace legacy systems, which might not sound like the wiz bang “smart” technology we’ve been hearing so much about.  But it’s likely the smartest thing these governments can do; and when they do, they should do it together. 

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Which Private Cloud Solution Provider In China Suits You Best?

Frank Liu

Chinese organizations should leverage the benefits of private cloud to address emerging requirements such as more agile technology services to improve customer engagement. However, determining which private cloud solution your company should choose is not a matter of size or market share. What’s most important is fit for purpose — your purpose. And that’s exactly what our The Forrester Wave: Private Cloud Solutions In China, Q1 2015 report helps you determine.

Charlie Dai and I spent the past six months identifying and evaluating the leading vendors in the private cloud space in China by scoring them against 24 criteria, grouped into three high-level buckets:

  • Current offering. A vendor’s position on the vertical axis of the Forrester Wave graphic indicates the strength of its current product offering. The key current offering criteria are cloud management and self-service access, service management and creation, automation capabilities, heterogeneity, contract terms and support, and cost.
  • Strategy. A vendor’s position on the horizontal axis indicates the strength of its go-to-market strategy. Forrester evaluates strategy with planned enhancements, strategic vision, third-party ecosystem, partnerships, and customer experience.
  • Market presence. The size of a vendor’s bubble on the chart indicates its market presence in China. Forrester evaluates market size via installed base and revenue.
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Forrester's Top CRM Trends For 2015

Kate Leggett

CRM is the foundational building block that allows empowered consumers and connected employees to do business in ways we could not imagine just a few years ago. Historically, CRM strategies have focused around operational efficiency gains like reduced marketing costs, increased revenues from salespeople, shorter sales cycles, or better customer service productivity. Its no wonder that CRM is widely deployed in all companies – both big and small.

 

Today CRM is evolving, and companies are using it to support their customers in their end-to-end journeys. This customer obsession delivers business results that far exceed productivity and efficiency measures.CRM, used the right way, delivers higher levels of revenue and company profitability through winning, serving, and retaining customers.

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My Top Ten And What It Means For Getting Your Own Metrics Right

Nigel Fenwick

Every so often I check my blog stats to see what you, the reader, find most interesting - my goal is to continue to bring you great content in both my blog and my research. While I was looking back over my blog stats I thought you might like to see the top ten blog posts in case you missed any of them. But just how should I assess the top ten? Like all outcome metrics, this one is open to interpretation. 

I could take the simple route and just count which posts have the most reads (Table 1a). But that would fail to take into account how many days it has been since the blog was published - it stands to reason that older blog posts might garner more reads. So a ranking based on the number of reads divided by the number of days the post has been online would yield a more accurate result in terms of most read post (See Table 1b - Top ten most read posts)*.

Table 1a - Top Ten Most read Posts


1 Unleash Your Digital Business
2 The Secret Of Successful Social Communities: 4 Social Needs
3 Why Customer Experience Will Become The #1 CIO Priority
4
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Categories:

Rethinking Analytics Infrastructure

Richard Fichera

Last year I published a reasonably well-received research document on Hadoop infrastructure, “Building the Foundations for Customer Insight: Hadoop Infrastructure Architecture”. Now, less than a year later it’s looking obsolete, not so much because it was wrong for traditional (and yes, it does seem funny to use a word like “traditional” to describe a technology that itself is still rapidly evolving and only in mainstream use for a handful of years) Hadoop, but because the universe of analytics technology and tools has been evolving at light-speed.

If your analytics are anchored by Hadoop and its underlying map reduce processing, then the mainstream architecture described in the document, that of clusters of servers each with their own compute and storage, may still be appropriate. On the other hand, if, like many enterprises, you are adding additional analysis tools such as NoSQL databases, SQL on Hadoop (Impala, Stinger, Vertica) and particularly Spark, an in-memory-based analytics technology that is well suited for real-time and streaming data, it may be necessary to begin reassessing the supporting infrastructure in order to build something that can continue to support Hadoop as well as cater to the differing access patterns of other tools sets. This need to rethink the underlying analytics plumbing was brought home by a recent demonstration by HP of a reference architecture for analytics, publicly referred to as the HP Big Data Reference Architecture.

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Mobile BI Success: Having The Right Technology Helps, But Isn't Enough

Martha Bennett

Between 2012 and 2014, mobile BI adoption shot up: Forrester survey data shows that the percentage of technology decision-makers who make some BI applications available on mobile devices has nearly quadrupled, and the percentage who state that BI is delivered exclusively via mobile devices has risen from 1% in 2012 to 7% in 2014. While this clearly demonstrates that mobile BI is gaining traction, the actual mobile BI adoption picture is rather more nuanced. Our ongoing research and client interactions show that mobile BI adopters fall into three overall groups; some organizations

  • Really ‘get’ the transformational potential of mobile BI. They are the ones who understand that mobile BI is about much more than liberating reports and dashboards from the desktop. They focus on how data can be leveraged to best effect when in the hands of the right person at the right time. If necessary, they’re prepared to change their business processes accordingly. For those companies, mobile BI is an enabler of strategic goals, and deployment is a journey, not an end in itself.
  • Make mobile BI available because it’s the right thing to do, or they’ve been asked to.  Many of these organizations are reaping considerable benefits from their mobile BI implementations, and the more far-sighted of them are working on how to move from the tactical to the strategic. Equally, many are trying to figure out where to go from here, in particular if the initial deployment doesn't show a clear benefit, let alone return on investment. 
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Time To Reset Your Knowledge Of Big Data Ecosystems In China

Charlie Dai

At the China Hadoop Summit 2015 in Beijing this past weekend, I talked with various big data players, including large consumers of big data China Unicom, Baidu.com, JD.com, and Ctrip.com; Hadoop platform solution providers Hortonworks, RedHadoop, BeagleData, and Transwarp; infrastructure software vendors like Sequotia.com; and Agile BI software vendors like Yonghong Tech.

The summit was well-attended — organizers planned for 1,000 attendees and double that number attended — and from the presentations and conversations it’s clear that big data ecosystems are making substantial progress. Here are some of my key takeaways:

  • Telcos are focusing on optimizing internal operations with big data.Take China Unicom, one of China’s three major telcos, for example. China Unicom has completed a comprehensive business scenario analysis of related data across each segment of internal business operations, including business and operations support systems, Internet data centers, and networks (fixed, mobile, and broadband). It has built a Hadoop-based big data platform to process trillions of mobile access records every day within the mobile network to provide practical guidelines and progress monitoring on the construction of base stations.
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Testing Pit Stops In Three Seconds

Diego Lo Giudice

Formula One has gotten us all used to amazing speed. In as little as three seconds, F1 pit teams replace all four wheels on a car and even load in dozens of liters of fuel. Pit stops are no longer an impediment to success in F1 — but they can be differentiating to the point where teams that are good at it win and those that aren’t lose.

It turns out that pit stops not only affect speed; they also maintain and improve quality. In fact, prestigious teams like Ferrari, Mercedes-Benz, and Red Bull use pit stops to (usually!) prevent bad things from happening to their cars. In other words, pit stops are now a strategic component of any F1 racing strategy; they enhance speed with quality. But F1 teams also continuously test the condition of their cars and external conditions that might influence the race.

Source: uae-f1-grand-prix-2011-race-preview-feature-mgp.

My question: Why can’t we do the same with software delivery? Can fast testing pit stops help? Today, in the age of the customer, delivery teams face a challenge like none before: a business need for unprecedented speed with quality — quality@speed. Release cycle times are plummeting from years to months, weeks, or even seconds — as companies like Amazon, Netflix, and Google prove.

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