Global Vendors Should Accelerate Their Partnerships In China

Charlie Dai

It's never been as challenging for global companies in China as it is right now. First, we've seen a continuous stream of news about the Chinese government requiring greater regulatory governance, starting with the cybersecurity vetting of IT products that relate to national security and public interests in May. Second, leading Chinese Internet companies equipped with emerging technology, such as Alibaba, Baidu, and Tencent, are engaging consumers with enriched products and services, expanding into the enterprise business via innovative business models, and extending their reach from tier-one and tier-two cities to tier-three to tier-six ones.

To gain extensive geographic and vertical coverage in the huge market that is China, vendors have had to engage with partner ecosystems for business operations. Now, it’s even more critical for multinational corporations to enable their local alliances to overcome these disruptions and achieve mutually beneficial strategic business growth. Some vendors have already started doing so, with IBM being a leading example. Its initiatives include:

  • Launching a strategic partnership with Yonyou. On September 13, 2014, IBM announced the start of its strategic cooperation with Yonyou during the latter's 2014 user conference. IBM will optimize DB2 with BLU Acceleration for various Yonyou products, such as NC (Yonyou’s ERP offering) and its supply chain management, customer relationship management, and human resources management products. In return, Yonyou will offer NC on top of DB2 with BLU acceleration to its customers, based on its evaluation of IBM’s product in June 2013.
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Quality, Trusted, Fit for Purpose Data?

Michele Goetz

Often lagging in priorities when it comes to data strategy, it appears that data quality is coming back in favor. As organizations expand beyond data exploration and discovery to putting real action in place organization wide based on these insights, the risk of getting the answer wrong or having dirty data is higher.  

But, this may be anecdotal supposition, even in light of the wide conversations I've had with clients.   What we do know quantitatively is:

1) Data quality is the most important topic for information governance according to our recent Business Technographics research for data and analytics.  In fact,

2) We see an uptick in data quality inquiries from last year.  

3) Vendors are introducing data preparation tools that infuse data quality and governance into analytic and BI processes

Anecdotal evidence and quantiative evidence leads me to the thought that there is a bigger shift happening in how we think about data quality, how we act upon it, and what doing so does for our buisnesses.  When things are a-changing it always make my brain itch to get more data, more stories, and more evidence.  And, while I'm curious, I'm assuming you are too. It is great to see that something in influencing change - and we want to know what that is in order to determine if we too need to change.  However, what is more important is what are organizations doing and which are standing out in terms of success and improved ways of thinking and execution?  In the end, do we need to write a new playbook* for data quality?  Has the bar been reset and we need to rebenchmark?

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E-Delivery Adoption Despite Mobile Mind Shift Is Still Abysmal

Craig Le Clair

 

During the internet bubble of 2000, many of us predicted E-delivery of business content would reach a 40% to 50% adoption within a few years. Here we are now almost 15 years later and it still hovers around 20%. How can this still be true in 2014? Enterprises want print to become a secondary channel because it's less expensive. They form committees to ensure output from core systems is consistent, compliant, and adds to the customer experience. Stymied by low adoption rates — except in specific demographics, such as online brokerage and banking — many enterprises have lost enthusiasm for aggressively prioritizing digital adoption. And it's hard to blame them.

Unfortunately, we are the problem. We do not link paper usage with carbon contribution, don't trust our institutions, or are just are afraid of missing a payment unless the bill lands in the mailbox. Despite the plethora of smart devices, pervasive video, and social media that allow us to interact easily with customer service agents, pass information digitally, and complete business transactions on-the-run, we still hold on to paper delivery. I discuss the reasons for this here and what firms can do about it.

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Kofax Acquires SoftPro, Enters Growing E-Signature Market

Craig Le Clair

There are a few well-engineered products out of Stuttgart, Germany — Mercedes-Benz, an oft-visited tourist stop, is one. Another good Stuttgart product: SoftPro’s E-signature solution. Its strengths lie in its use of biometrics for image verification, particularly the SignAlyze product, a signature verification tool used extensively by German banks. SoftPro has a strong global presence outside of the US and solid banking accounts, all delivered with the kind of engineering foundation you would expect. The acquisition will help Kofax a lot, as it is virtually unknown in the US, with marketing and strategy behind the market leaders, and it has been slow to enter the trending SaaS market. In addition, SoftPro’s shortfalls in selected areas compared to the broader field, such as workflow and analytics, can be quickly plugged with the Kofax Total Agility BPM platform.

All in all, the SoftPro acquisition enhances Kofax’s competitive position in the smart process application category. E-signature also adds to Kofax’s portfolio for capture, process automation, analytics, and mobility to address key requirements for the rapidly growing need to automate and digitize document-centric applications. Kofax talks a lot about the first mile, but now can have deeper conversations about that last mile — where something needs to be signed.

How To Become A Trusted Cloud Service Provider In The Chinese Market

Charlie Dai

Practice makes perfect. In daily life, if someone has proven experience and a good reputation in specific area for relatively long time, we would normally consider them to be trustworthy. For example, if Amazon Web Services claimed that it was a trusted public cloud service provider — if not the most trusted provider — not many professionals in the US would argue against that.

However, this does not necessarily hold true in China; cloud service providers need to receive an official authorization from the government that certifies them as a provider of trusted cloud services (TRUCS). I recently attended the International Mobile and Internet Conference, where I got an update on TRUCS.

  • TRUCS is an official recognition of standards compliance and quality. TRUCS is issued by the trusted cloud servicesworking group of the China Academy of Telecommunications Research of the Ministry of Industry and Information Technology. The working group defined the basic principles in June 2013; earlier this year, it finalized the evaluation standards in the form of a cloud service agreement reference framework.
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Digital Disruption To The Ultimate - I Should Have Taken The Michael Connelly Novel

Craig Le Clair

Vacation is a good time to read things that you can never get to while working. My list is quite long but I  scanned it  and took a copy of “The ZERO Marginal Cost Society” by Jeremy Rifkin to the beach. Now Forrester has a lot of focus on digital disruption, helping enterprises avoid being disrupted by new digitally based business models. We write about business agility, how to drive better customer experiences through mobile, social, and cloud. But we pretty much stop at what disruption means to an enterprise, as these are our clients.  

Jeremy Rifkin takes the digital disruption concept to its ultimate end state, and projects the effect on the entire economic system. He paints a somewhat murky but thought provoking picture of where this all leads.  The basic idea?  Digital alternatives, fueled by the Internet of things, big data, the sharing economy, 3D printing, AI and analytics, will drive the marginal cost of producing a product or service to near 0 and this disrupts the entire capitalist system. Established companies can't generate profit, emerging companies can only maintain temporary advantage, and people don’t have “real jobs” anymore. They ride the wave that he calls “the democratization of innovation” that works outside of traditional business and government.

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Cognitive Computing Forum: 7 Things You Need To Know

Michele Goetz

Day one of the first Cognitive Computing Forum in San Jose, hosted by Dataversity, gave a great perspective on the state of cognitive computing; promising, but early.  I am here this week with my research director Leslie Owens and analyst colleague Diego LoGudice.  Gathering research for a series of reports for our cognitive engagement coverage, we were able to debrief tonight on what we heard and the questions these insights raise.  Here are some key take-aways:

1)  Big data mind shift to explore and accept failure is a heightened principle.  Chris Welty, formerly at IBM and a key developer of Watson and it's Jeoapardy winning solution, preached restraint.  Analytic pursuit of perfect answers delivers no business value.  Keep your eye on the prize and move the needle on what matters, even if your batting average is only .300 (30%).  The objective is a holistic pursuit of optimization.

2)  The algorithms aren't new, the platform capabilities and greater access to data allow us to realize cognitive for production uses.  Every speaker from academic, vendor, and expert was in agreement that the algorithms created decades ago are the same.  Hardware and the volume of available data have made neural networks and other machine learning algorithms both possible and more effective.  

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Visionary Chinese Banks Show How Customer-Oriented Architectures Support Innovation

Charlie Dai

Five of the top 10 companies in the latest Forbes Global 2000 company list (published in May) are from China, and four of them are commercial banks. If you think this is only due to China’s massive consumer base, and that you can easily apply your global innovation strategy to the Chinese market, you’re almost certainly wrong. Enterprise architecture (EA) professionals at companies doing business in China should take a look at what the country’s banking and financial services industry (BFSI) is doing to enable customer-centric innovation.

I recently published two reports focusing on China’s BFSI. In these reports, I analyzed the Chinese banking landscape and the business challenges banks face, described a systematic approach to innovation that EA pros should consider when planning their transformations, and shed light on how they use both mainstream and emerging technologies to unleash the power of innovation around products, operations, and the organization. Some of the key takeaways:

  • Chinese banks suffer from their own customer experience issues. As a longtime monopoly, China’s BFSI has suffered from inefficiency, quality problems, and an uncompetitive ROI — and thus can no longer meet the high bar for customer satisfaction in the age of the customer. EA pros must find innovative ways to resolve these issues.
  • Internet companies and regulatory changes are challenging BFSI players. Visionary Internet companies like Alibaba and Tencent have launched financial services products, including innovative products like Yuebao, that are disrupting China’s BFSI with higher profits, lower barriers to entry, and better flexibility. The government is also making regulatory changes that will open up the market and intensify competition.
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Are Data Governance Tools Ready for Data Governance?

Michele Goetz

An IT mindset has dominated the way organizations view and manage their data.  Even as issues of quality and consistency raise their ugly head, the solution has often been to turn to the tool and approach data governance in a project oriented manner.  Sustainability has been a challenge, relegated often to IT managing and updating data management tools (MDM, data quality, metadata management, information lifecycle management, and security).  Forrester research has shown that less than 15% of organizations have business lead data governance that is linked to business initiatives, objectives and outcomes.  But, this is changing.  More and more organizations are looking toward data governance as a strategic enterprise competence as they adopt a data driven culture.

This shift from project to strategic program requires more than basic workflow, collaboration, and data profiling capabilities to institutionalize data governance policies and rules.  The conversation can't start with data management technology (MDM, data quality, information lifecycle management, security, and metadata management) that will apply the policies and rules.  It has to begin with what is the organization trying to achieve with their data; this is a strategy discussion and process.  The implication - governing data requires a rethink of your operating model.  New roles, responsibilities, and processes emerge. 

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Can You Afford To Ignore The Artificial Intelligence Wave?

Michele Goetz

Recent news of a a computer program that passed the Turing Test is a great achievement for artificial intelligence (AI).  Pulling down the barrier between human and machine has been a decades long holy grail pursuit.  Right now, it is a novelty.  In the near future, the implications are immense.

Which brings us to why should you care.

Earlier this week the House majority leader, Eric Cantor, suffered an enormous defeat in Virginia's Republican primary by Tea Party candidate David Brat.  No one predicted this - the polls were wrong, by a long shot.  Frank Luntz, a Republican pollster and communication advisor, offered up his opinion on what was missing in a New York Times Op-Ed piece - lack of face-to-face discussions and interviews with voters.  He asserts that while data collection was limited to discrete survey questions, what it lacked was context.  Information such as voter mood, perceptions, motives, and overall mind set were missing. Even if you collected quantitative data across a variety of sources, you don't get to these prescient indicators.  

The new wave of AI (the next 2 - 5 years) makes capturing this insight possible and at scale.  Marketing organizations are already using such capabilities to test advertising messages and positioning in focus group settings.  But, if you took this a step further and allowed pollsters to ingest full discussions in person or through transcripts in research interviews, street polls, social media, news discussions and interviews, and other sources where citizen points of view manifest directly and indirectly to voting, that rich content translates into more accurate and insightful information.

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