US Government: Huawei Should Be Your Digital Business Partner, Not Your Enemy

Charlie Dai

Huawei Technologies started out nearly 30 years ago as a small private company with 14 employees and 140,000 yuan in capital. By 2015, its total revenue exceeded $60 billion. Huawei is already a global company, but its globalization journey has been a difficult one since the very beginning. Despite its continuous business growth in other regions, Huawei has faced critical censorship in the US since Day One — and last week the US government put Huawei under the microscope yet again.

National security is important, but using “national security” as an excuse for allowing unfair competition will only harm customers. It’s time for the governments of both countries to trust each other more. I’ve recently published a report focusing on Huawei’s continuous progress toward becoming a key enabler of digital transformation in the telco and enterprise spaces. Some of the key takeaways:

  • Huawei has holistic strategies for digital transformation. Huawei’s broad vision of digital strategy — which focuses on cloud enablement and readiness, partner enablement, and open source co-creation — has helped the firm sustain strong business growth in the telco and enterprise markets. For example, its partnerships with T-Systems on the Open Telekom Cloud in Germany and with Telefónica on public cloud in the Americas have helped carriers in local markets give cloud users on-demand, all-online, self-service experiences.
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Navigate The Crowded Enterprise File Sync And Share Market By Asking These 3 Questions

Cheryl McKinnon

Forrester defines Enterprise File Sync and Share (EFSS) as the technologies that "allow organizations to share and replicate content across multiple devices, distributing files to employees and/or customers or partners outside the enterprise".

Two Forrester Waves on the EFSS market were published recently, segmenting this crowded market into two categories: cloud solutions and hybrid solutions. Forrester clients can access them here:

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Insight Platforms Have Arrived

Brian  Hopkins

Are you lost in a confusing soup of vendor-speak about what their data analytics stack actually offers? Big data, data platforms, advanced analytics, data lakes, real-time everything, streaming, the IoT, customer analytics, digital intelligence, real-time interaction, customer decision hubs, new-stuff-as-a-service, the list goes on.

Recognize the convergence happening as vendors evolve their technologies from doing just one thing like predictive analytics or search to many things together. For example, data integration, data warehouse, and BI tools are typically sold separately, but breakout vendor Looker combines data integration, model governance, basic BI, and a runtime for data applications all in one software layer that sits on your data lake. As another example, consider predictive analytics vendor Alpine Data Labs or SAS Viya from SAS. These vendors have built out a lot of data management and insight delivery tooling into their platforms because without it users struggle to maximize value. Another trend is big data search vendors like Maana that now also include hooks for predictive model execution as well as more data management functions. Lastly, systems integrators are packaging their IP and offering it as a data management and analytics integrated product — for example, Saama’s Fluid Analytics Engine or Infosys’ Information Platform.

In fact, the list of innovative vendors blending data management, analytics, and insight execution technology is growing by leaps and bounds. To address this trend, I just published a report, Insight Platforms Accelerate Digital Transformation, in which I created a broad definition that labels this trend:

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Pega Buys OpenSpan: Watch Out - RPA Vendor Landscape Is About To Change

Craig Le Clair

Enterprises, in their quest to reduce labor costs, are applying RPA technologies. Yet they do not have a well-defined set of principles and best practices, including how to position RPA with other process tools and initatives. Today it may have become a bit more clear. Pega is the first tech provider, and only BPM market particpant of substance, to purchase an RPA provider (OpenSpan). The combination brings robotics, analytics, and case management together - and that makes sense. Think of Pega's process/rules capibility firing off a set of RPA scripts.

RPA in many respects is an alternative, some would say the polar opposite of Pega's current business model that feasts on the transformitive "big IT spend" for BPM, case management, automation, and customer service projects. RPA does not require invasive integration. It is a quick hit for automation, a “low touch” approach for process improvement for brittle legacy systems. The bottom line. Enterprises that employ labor on a large scale for process work can gain efficiencies by just automating repetitive human tasks for the “as is” process.

OpenSpan is nice pick-up for Pega that will help with back-office BPM work, but more so with contact center environments where the agent requires human and machine multitasking that often spans multiple windows and web applications, few of which are integrated with each other. Cumbersome process flows, rekeying of data, and lack of integration add up to lengthy call times, reduced accuracy, and an overall increase in customer frustration. Pega/OpenSpan will give Jacada and NICE a run for their money, and the future integration with Pega's analytics tracks where the RPA space is heading.

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kCura Puts the CAAT Into The Bag . . . Acquires Long-time Partner Content Analyst Company

Cheryl McKinnon

We've seen another acquisition in the shifting eDiscovery market this week as kCura, the developer of Relativity, announced its acquisition of Content Analyst Company, the brains behind the CAAT analytics engine (kCura’s press release is here). The acquisition is not entirely surprising. kCura has been relying on the CAAT engine to power its analytics offering for eight years. According to kCura, use of its Relativity Analytics offering “has grown by nearly 1,500 percent” since 2011, with more than 70% of current kCura’s customers with licenses.

What does this acquisition mean for kCura, its customers, and Content Analyst Company customers?

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Think You Want To Be "Data-Driven"? Insight Is The New Data

Brian  Hopkins

It’s been a while since I’ve blogged; not because I’ve had nothing to say, but rather because I’ve been busy with my colleagues Ted Schadler, James McCormick, and Holger Kisker working on a new line of research. We wanted to examine the fact that business satisfaction with analytics went down 21% between 2014 and 2015, despite big investments in big data. We found that while 74% of firms say they want to be “data-driven,” only 29% say they are good at connecting analytics to action. That is the problem.

Ted Schadler and I published some initial ideas around this idea in Digital Insights Are The New Currency Of Business in 2015. In that report, we started using the phrase digital insight to talk about what firms were really after ― action inspired by new knowledge. We saw that data and analytics were only means to that end. We also found that leading firms were turning data into insight and action by building systems of insight ― the business discipline and technology to harness insights and consistently turn data into action.

Here is a key figure from that report:

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Seven New Buying Patterns Reshape The 2017 Enterprise Collaboration Market

Craig Le Clair

The enterprise collaboration (EC) landscape is rife with innovative products that begin with a narrow feature set (e.g., Box for document collaboration or Slack for group messaging). Viral growth and company value often follow — along with competitors that target the newly identified market. A fragmented and overlapping landscape results as newer entrants pursue broader EC goals. Over the next two years, firms will purchase enterprise collaboration in seven fundamentally different ways. The report below aims to helps companies sift through confusing use cases to best apply EC.

What did we find? Firstly, the torrent of information, lack of critical-mass adoption, and context switching create barriers to effective EC adoption, and secondly, platforms that support lead applications, targeted group messaging, project management tools, external communities, or just finding expertise in an organization are the winning formulae for many firms.

Read the report here: Seven New Buying Patterns Reshape The 2017 Enterprise Collaboration Market.

The Blind Spot For Man-Machine Collaboration

Craig Le Clair

We are kicking off a research series on the future of work for "production services," with a focus on administrative and customer service jobs where a high degree of automation is projected. Basically, cognitive computing may do to white-collar jobs what robotics did to blue-collar jobs. This may lead to radically different work patterns and unintended consequences. Enterprises risk blindly bringing in advanced analytics without a best practice approach that covers change management and identifies gaps in the formerly human-driven process that affect compliance, customer experience, and efficiency. To date, few are doing serious thinking about a force that will lead to a restructuring of work that is more profound and far-reaching than the transition from the agricultural to the industrial age. 

Please take or send this survey to businesses contemplating or using smart machines to augment human-based processes. They will receive a free copy of the report.

Thank you.

 https://forrester.co1.qualtrics.com/SE/?SID=SV_6RI5qO6FJ2S13z7

 

 

 

The 2016 Enterprise Architecture Awards: Speed And Responsiveness — And EA

Alex Cullen

Businesses of all types are experiencing the ramifications of an accelerating pace of change. Everything, from economies as a whole to the competitive landscape to consumers’ tastes, is more dynamic. As a consequence, business leaders are demanding that their businesses move faster. ‘Moving faster” may encompass continually updated mobile capabilities, digitized products, and more agility in how firms work with customers and suppliers.

This is what enterprise architecture is supposed to help with, right?

The answer is “yes – in theory,” but for reality to match theory requires an EA program attuned to increasing business speed and improving business responsiveness, not cutting costs and constraining change. I’ve talked to a lot of enterprise, business, and information architect leaders, and my take is that while all EA programs should be attuned this way, only a few are today. Forrester and InfoWorld would like to highlight the stories of these EA programs.

I am pleased to invite you to submit your EA program story to the Forrester/InfoWorld 2016 Enterprise Architecture Awards.

What are we looking for this year? Simply said, we’d like to hear how you helped your business move faster and respond better to shifts in its ecosystem. You could have done this a variety of ways:

  • You moved your business onto a new technology platform, specifically to enhance business agility.
  • You led the way to bringing more customer and market insights into strategic processes of your organization.
  • You guided the development and execution of a digital business strategy.
  • You helped your firm’s embrace of Agile methods and scaled these methods to the enterprise.
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Do Not Confuse Data Governance With Data Management

Henry Peyret

Last week, I participated in a roundtable during a conference in Paris organized by the French branch of DAMA, the data management international organization. During the question/answer part of the conference, it became clear that most of the audience was confusing data management with data governance (DG). This is a challenge my Forrester colleague Michele Goetz identified early in the DG tooling space. Because data quality and master data management embed governance features, many view them as data governance tooling. But the reality is that they remain data management tooling — their goal is to improve data quality by executing rules. This tooling confusion is only a consequence of how much the word governance is misused and misunderstood, and that leads to struggling data governance efforts.

So what is “governance”? Governance is the collaboration, organization, and metrics facilitating a decision path between at least two conflicting objectives. Governance is finding the acceptable balance between the interests of two parties. For example, IT governance is needed when you would like to support all possible business projects but you have limited budget, skills, or resources available. Governance is needed when objectives are different for different stakeholders, and the outcome of governance is that they do not get the same priority. If everyone has the same objective, then this is data management.

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