The Future Of B2B Mobile Enterprise Services

Dan Bieler

Business-to-business (B2B) ecosystems facilitate the continuous exchange of information and collaboration. B2B ecosystems will play a central role for all businesses because they form the basis for redefining approaches toward innovation, knowledge management, supply-chain optimization, product development, sales, and marketing.

While the ultimate focus of these ecosystems is to create customer value, their more immediate effect is to drive operational agility in service of customers. Mobility will be a central enabler for these B2B digital ecosystems. Why?

  • Mobility is evolving beyond enterprise mobility management. Mobility shifts the way B2B ecosystems service their customers, support their partners, and affect competition. As a first step, technology teams need to move beyond enterprise mobility management (EMM). This comprises device, app, and content management, as well as telecom expenses, policy management, and security management. EMM relies on using several mobile apps in parallel without any functional integration between them.
  • Enterprise mobility experiences will significantly improve. Today, despite all the excitement concerning automation and machine learning, smart mobile devices still rely on direct user instructions. Business customers and employees have to move in and out of dedicated mobile apps to obtain support for specific business processes like procurement, product information, or sales analytics. These enterprise mobile apps rarely take into account the conditions that particular enterprise users find themselves in.
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Do You Have A Digital Intelligence Strategy That Will Win?

Cinny Little

Your digital intelligence strategy and implementation is struggling to keep up with your device-hopping customers.  You’re trying.   And it’s difficult – so many obstacles.   But you face the Digital Dilemma, introduced by colleague Nigel Fenwick:  your customers’expectations of digital experience keep rising.  When any digital experience they have with you doesn’t meet their expectations, their perception of the value your firm provides falls … which leads to risk of customers taking their business elsewhere.  Ouch.   So, tackle the Digital Dilemma head on.  Focus your digital intelligence strategy like a laser on the customer experiences that matter most to your business outcomes.  How?  With an actionable digital intelligence strategic plan.  Here are 3 of the key components your strategic plan must include.

1.       Align the plan to the right metrics and KPIs.  The optimal approach is to align measurement with customer-focused KPIs that stakeholders are already measured on.  Simple, but not necessarily easy.  But this is how you get that laser focus on the experiences that matter most to outcomes.

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The Vanishing Dichotomy Between B2B and B2C Branding

Dipanjan Chatterjee

 How My Experience As A Decision Maker Formed My B2B Branding World View

Before I threw caution to the wind and launched myself with wild abandon into the world of branding, I had a normal life.  For a few years, I ran a retail business for a Berkshire Hathaway company (and since everyone asks, yes, I did meet and have dinner with Warren, although I suspect his recollection may not be as crisp as mine.) We manufactured and sold uniforms to government agencies: Police, fire, EMS, postal service, and others. As you'd expect, our customers were quite insistent that the fabric for the uniforms be made in the U.S. That is until budgets got slashed, and belts got tightened. Then the only thing that mattered was cost. So we were sent scampering to find the lowest-cost fabric and our global fabric sourcing program had to go from zero to sixty in a matter of months. 

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Alexa, What Should My Intelligent Agents Strategy Look Like?

Jennifer Wise

As packages continue to arrive from this year’s record-breaking Black Friday weekend, it’s no doubt you’re seeing Amazon packages complete with front-and-center ads for Amazon’s Echo and Dot devices. You may even be one of the reported millions that ordered one that weekend.

These are more than just devices — they are Alexa-enabled and are helping Alexa further integrate into consumers’ lives. And Alexa isn’t alone: from Alexa to Google Now to Microsoft’s Cortana to Apple’s Siri, we have a budding class of intelligent agents (IAs) on the rise. In 2015, 45% of US online adults used at least one.

As consumers, these purchases mean a new product or a holiday gift. As a marketer, these are part of the growing intelligent agent landscape that threatens your direct relationship with customers. How? As consumers fall in love with the customized, proactive utilities IAs provide, IAs will capture customer moments. The good news: If you work with them, you can gain valuable new customer access and insights. If you don’t, you risk losing your direct customer interactions to this powerful intermediary.

How do you land on the positive scenario? The answer isn’t “launch a [skill, card, whatever the agent-specific experience may be].” Don’t repeat the app mishaps we saw from brands launching an app whether it made strategic sense or not. Instead, determine the strength of your brand loyalty, digital commitment, and data insights to decide if launching your own IA strategy is feasible today — or if you should pursue a different type of IA strategy as outlined in this report.

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Business Intelligence Skills

Boris Evelson

So you have gone through the Discover and Plan of your Business Intelligence (BI) strategy and are ready to staff your BI support organization. What skills, experience, expertise and qualifications should you be looking for?

  • Since the term BI is often used to also include data management processes and technologies, let's assume that in your case you are only looking for expertise required to build reports and dashboards and it does not include
    • Data integration (ETL, etc) expertise
    • Data governance (master data management, data quality, etc) expertise
    • Data modelling (relational and multidimensional) expertise
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Want To Create Action From Big Data? Look At Enterprise Insight Platform Suites

Brian  Hopkins

By now firms are deep into their big data investments — and frustrated. Too many new and rapidly evolving technologies are built on an open source and named after a bunch of zoo animals. The term insight platform has struck a chord with technology buyers exactly because it offers a path out of this mess. In fact, insight platform was the number-one emerging technology in terms of investment and interest in Forrester’s Q3 2016 Global State Of Enterprise Architecture And Portfolio Management Online Survey.

What exactly is an insight platform though? I introduced the term in my May blog post Insight Platforms Have Arrived and then refined it and explained the vendor landscape in my August post Tame The Beast: Forrester’s Insight Platform Vendor Landscape. Over the last few months, we have been conducting a Forrester Wave™ evaluation of the most mature segment of the market, enterprise insight platform suites, which are:

“…Integrated or partially integrated suites of data management, analytics, and insight execution components that require some integration and configuration to form a platform.”

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Velocity with quality mandates a model based approach to ARA tools and DevOps

Robert Stroud

DevOps velocity mandates change velocity

Enterprises today are focusing on delivering applications faster to drive customer experiences and drive business transformation to meet rising expectations. For some, faster delivery is simply faster time to disappointment where the delivery process is shoddy and speed is the only metric. Speed without quality in an oxymoron – and extremely dangerous. The automation of the process known as Application Release Automation (ARA) is one of the critical impediments in the DevOps journey for I&O organizations today. ARA tools are designed to remove errors from manual processes by standardizing and automating the movement of applications with middleware and infrastructure – the critical final step in the delivery pipeline of applications to deliver customer value.

Continuous delivery is the goal; ARA tools are the vehicles to get there

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Amazon Go Ushers In A New Era In Retail Technology

Nigel Fenwick

Amazon's new Amazon Go store ushers in a new era in brick and mortar grocery and convenience shopping. In the early 80's, electronic point of sale (POS) dramatically changed the checkout experience in grocery stores, speeding up checkout lines. Today, a checkout without POS is unthinkable unless it's a farm stand on the side of the road … and even here we're likely to see Square hooked up to a smartphone. But even with POS, the checkout has always been the big time waster in any grocery shopping experience. Until this week.

Six years ago, "The Ultimate Grocery Shopping App" described a future in which the grocery shopping experience was radically different from what existed in 2010. This week, Amazon has brought part of that vision to life by opening its first Amazon Go brick and mortar convenience store for Amazon employees in Seattle. A convenience store with no checkout lines … with no checkout.

Gone are the POS systems. Welcome to the era of automatic checkout. Amazon has used new technologies like image recognition and machine learning to go beyond at least some of the experience predicted back in 2010. Instead of shoppers having to scan items into their shopping cart, Amazon uses this advanced technology to track what shoppers pick up and add to their cart and what they put back on the shelf. No scanning, no checkout … just walk out and pay.

Why will this take off? Becuase it gives shoppers back significant time savings and it gives retailers potentially enormous costs savings.

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APM Is Hot. Don't Laugh, I'm Serious.

Milan Hanson

I cover the APM market for I&O professionals, and it seems that every week I am briefed by yet another vendor entering the APM market. I wonder “What’s the attraction? Why is APM so hot?” Maybe it’s the mess.

I’m weird. I like cleaning up after Thanksgiving dinner. Why? Because it’s a huge mess. A little effort produces the dramatic result of a clean kitchen, ready for the next attack:  leftovers.

In September Forrester published The Forrester Wave™: Application Performance Management, Q3 2016. For vendors entering the APM market, it’s your guide to be a contender. For clients seeking an APM solution, it’s your guide to what’s available.

The Wave evaluates fourteen vendors on twenty-eight criteria.  We selected these fourteen as key players based on their functionality, market presence and the fact that they are most frequently mentioned in our conversations with clients.  Of course there are more than fourteen APM vendors in the market.   

For a bigger list of vendors, see the Forrester report Vendor Landscape: Application Performance Management, Including Mobile APM, Q2 2016.It includes twenty-six vendors, and even that isn’t all of them -- more vendors enter the APM market every week.

The “mess” that attracts vendors to this market is that I&O teams face an eternal battle to deliver…

  • faster service
  • to more users
  • by improving monitoring and management
  • of software, hardware, virtual-ware, and cloud
  • that grows more complex daily through:
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Developers: Will AI Run You Out Of Your Job?

Diego Lo Giudice

Much has been written about how artificial intelligence (AI) will put white-collar workers out of a job eventually. Will robots soon be able to do what programmers do best — i.e., write software programs? Actually, if you are or were a developer, you’ve probably already written or used software programs that can generate other software programs. That’s called code generation; in the past, it was done through “next” generation programming languages (such as a second-, third-, fourth-, or even fifth-generation languages), today are called low code IDEs. But also Java, C and C++ geeks have been turning high level graphical models like UML or BPML into code. But that’s not what I am talking about: I am talking about a robot (or bot) or AI software system that, if given a business requirement in natural language, can write the code to implement it — or even come up with its own idea and write a program for it.

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