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Some Thoughts on IBM Notes and Domino in 2018

Some Thoughts on IBM Notes and Domino in 2018

After spending time with executives from both IBM and HCL, as well as having discussions with several IBM Business Partners, here are some of my thoughts on the current state of Notes and Domino, and the opportunity available.

Future of Work

Tableau Takes Next Steps Toward Smart Analytics

Tableau Takes Next Steps Toward Smart Analytics

Tableau’s Empirical acquisition is its latest move toward machine-augmented analytics. Here’s a look at the company’s ‘smart’ features.

Tableau last month announced the acquisition of Empirical Systems, an artificial intelligence (AI) startup with an automated discovery and analysis engine designed to spot influencers, key drivers and exceptions in data. It was Tableau’s second acquisition over the last year aimed at accelerating so-called “smart” capabilities and part of a larger push that began in 2016.

As I wrote in my January report, “How Machine Learning and Artificial Intelligence will change BI and Analytics,” consumers and businesses alike are increasingly interested in smart capabilities powered by heuristics, machine learning (ML) and natural language processing. In the area of analytics, these smart capabilities promise to take us beyond the limits of self-service.

Despite the embrace and success of self-service over the last decade, it’s increasingly clear that this approach alone is not enough to truly democratize data-driven decision-making. Self-service tools aren’t always intuitive for nontechnical business users. Even more data-savvy users sometimes need help when selecting data, determining how to analyze that information, and deciding how best to visualize and share insights.

To make things easier for novice and experienced users alike, BI and analytics vendors are developing smart capabilities in at least four areas: data prep, data analysis and discovery, NL query, and prediction. In my latest report, “Tableau Advances the Era of Smart Analytics,” I detail the smart capabilities that Tableau has delivered to date, where it needs to fill gaps, and the strength and weaknesses of what it calls its augmented analytics strategy.

Tableau started stepping up its smart capabilities in 2016 with automated clustering and forecasting capabilities. It followed in 2017 with smart table-, join- and data-source recommendations. This year Tableau also introduced a number of smart features within its Tableau Prep data-preparation offering, introduced in April.

Tableau’s recommended-data-source feature delivers user- and context-specific suggestions. 

One of the gaps in Tableau’s smart lineup, at this writing, is natural language query, a feature that let users ask questions of data in plain English rather than using SQL code. This gap sparked Tableau's 2017 acquisition of ClearGraph, a startup focused on natural lanaguage query. It's well known that Tableau is working on bringing natural language query capabilities into its products, but it has yet to announce release dates. I’m not the only analyst predicting that we'll see Tableau's NL query nnouncement in 2018 -- mostly likely at the Tableau Conference in October.  

This brings us back to the Empirical acquisition. If the turnaround on the ClearGraph acquisition proves out, I would expect a 2019 announcement of new smart features based on Empirical’s assets and expertise. (As was the case in the ClearGraph acquisition, Tableau hired Empirical's leadership and staff as well as acquiring its assets.)

As noted in my report, Tableau is far from alone in delivering smart features and it has not been the first to deliver all of the smart capabilities it now offers, but the company’s pace of investment has accelerated over the past three years. I see Tableau as now having a solid start on delivering expected smart capabilities, and it's adding these features as built-in (no-extra-cost) aspects of its core products. Given that Tableau has more than 74,000 paying customers and hundreds of thousands of users, its efforts are going to go a long way toward brining smart capabilities to the market.

Related Resources:
Tableau Advances the Era of Smart Analytics
How Machine Learning and Artificial Intelligence Will Change BI and Analytics
Tableau Conference 2017: What’s New, What’s Coming, What’s Missing

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Musings - Enterprise Acceleration - and what every HR Leader should know about it

Musings - Enterprise Acceleration - and what every HR Leader should know about it

Enterprises have always been faced with competition, as competition is key mechanic of success in the free market economy. But the need for adopting and reacting to the competition and creating new creative strategies has never been as high as it is today. Digital Transformation has substantially changed the game here, forcing enterprises to move faster towards a new objective, while having less room for error – than ever before. Constellation Research has shown that in digitally transformed industries, the leaders are taking more than 70% of revenue and over 77% of profit. This means the risk of being left behind is bigger than ever before Worse, when left behind it is almost impossible to catch up… as a consequence, what matters for an enterprise leader, is how much their enterprise can accelerate as a unit. As it is impossible and unrealistic for an enterprise to catch all the successful trends that become relevant in an early phase, it is even more important that CxOs look at the speed to at which their enterprise can adopt to challenges as thrown at them from existing and new markets. 

 
 

Financial Indices tell the story

To understand the increasing rate of change in the markets, look at the financial indices across the world, and the they tell the story of markets moving faster. Enterprises has been falling out of financial indices at a faster rate than ever before, many of the indices seeing a complete turnaround in members since their start, usually 30+ years ago. The main reason is that many of these enterprises have been acquired, beyond that they others have just not been able to keep up with the rate of change created by the speed of market changes. In essence, these enterprises were not able to accelerate fast enough and adopt to the rate of change they were operating in.

For example:

- The DAX has seen 100%-member turnover in the last 30 years.

- The DOW has seen over 52% of its members disappear since 2003.

- The FTSE has lost 2.6x members that its number of listed enterprises (100) in 34 years.

- The S&P 500 has seen the average age of new members joining reach 10 years.

 

Enterprise Acceleration Formula

So how do we define enterprise acceleration? We look at the two key criteria, technology, manifested in software, and people. For the sake of the blog post we look at people only here. People speed is determined by the talent that people have, their ability to learn new skills, over the speed of forgetting skills and the rate of skills being obsolete.

For HR leaders, the variables are:
  • Hire extraordinary talent, of course with applicability for the enterprise current and future talent needs.
     
  • Understand people have to continuously learn and need modern tools to enable this.
     
  • Make sure skills do not get lost, especially the relevant, just trained ones.
     
  • Minimize the percentage of obsolete skills in the people base of the enterprise. 

This requites a very different approach to people skills, their augmentation and conservation.
 
 

The three key focus areas for Enterprise Acceleration

Strategy

Enterprises need to shift their strategy from satisfying executive, reporting and compliant needs, to a focus on helping the people leader, who has the task to achieve business result for the enterprise. These people leaders manage teams of one or two handful of employees and are chronically under supported from executives, tool and processes. Most requirements from the leadership of an enterprise coming down the chain of command neglect the situation, needs and challenges of these people leaders.

CxOs need to analyze, what people leaders need for their and their team's work and what they need to become more successful. This needs a change of focus from administrators and reporting needs to productivity and efficiency needs as needed by the people leaders in the current situation of the enterprise, as well as the targeted setup of the enterprise from a strategy perspective. This makes the business user focus a key success factor in the overalls strategy for implementing an enterprise acceleration strategy


 

SaaS

CxOs need to have conversations with their software providers on 5 key topics of enterprise automation side:

1. Talent Depth Chart. The talent depth chart is crucial for enterprises to understand where its talent is. As seen in the enterprise acceleration formula, the innate talent of people is one of the key success factors for people speed. This means finding internal talent for the right job is key to identify and then to transport the talent to that next position, where the enterprise needs the people with the right skills.

2. TransBoarding. This is the ability of company to "transport and onboard" talent around in a faster and better way than ever before. Meaning that the transferees will be trained for the next position even before they take on the new position. It also means a seamless transfer between jobs can happen with significant lower cost and friction for the employee and the people leader.

3. 21st century learning. CxOs need to have a conversation about modernizing their learning systems to the needs of the 21st century workforce. This means that learning content has to be pervasive, can be self-created, and can be self-curated and consumed at the space of the modern workforce. Too much learning happens at the wrong time in the wrong place, and the speed of forgetting newly learnt information and capabilities is killing any speed an enterprise was planning to pick up from the training / learning in the first place.

4. Fixed performance management. In order for enterprise to know where the good people are, it needs to know who's performing well. Unfortunately, the state of performance management in enterprises is mostly in a sour state. Fixing whatever needs to be fixed to make performance management work is crucial for the enterprise that wants and needs to accelerate.

5. Lean recruiting. As talent of people is critical for enterprise, the need to recruit fast is crucial for the enterprise. Taking the friction from the talent acquisition process by directly enabling hiring managers to see what talent available in the market is and facilitating the conversation between manager and future candidate is a key step to accelerate on recruiting side.

So, enterprise executives need to ask their software providers, how they can help achieve these 5 capabilities. Are any of them coming, are any on the road map? Or is this the first time the vendor hears about them?

 

Technology Platform

These are three topics for a conversation that people leaders need to have with their CIO / CTO colleague:

1. Machine Learning. No technology will change the work life more than machine learning. An enterprise that wants to accelerate needs to have a strategy on how to leverage machine learning for its needs. HR Leaders need to understand what their enterprise wants and can do in the near future and understand the repercussions and benefits of the technology for the people leaders and their teams in the enterprise. And Machine Learning needs to run automatically on top of the enterprise data, that is ideally stored in Big Data clusters.

2. Big Data. All planning starts with data. In a faster moving economy, enterprises no longer can afford to go on long data collection, cleanse and acquisition projects. All electronic information that it is at the disposal of the enterprise, needs to be available in Big Data clusters. This is the only way for enterprise to directly make decisions based on where data is and where it needs to move / react towards the competition in the respective markets. Establishing enterprise wide Big Data capabilities is a must have for enterprises, so they don't lose time directly at the starting blocks when starting in enterprise acceleration needs to happen.

 
3. Non-Monolithic. Traditionally enterprise software would only provide one way of doing things. That meant that when the enterprise needed different automation for different divisions, organizations or department's customization was needed. Today, a more modern approach to enterprise architecture is needed, which allows each area of the enterprise to run their own set of automation, a non-monolithic approach to enterprise software.

MyPOV

There is only one thing that is certain, and that is that business will never be as slow as it is today. It's vital for enterprises to find ways to help them move faster and be able to accelerate when it matters. It is also clear that more moments will be ahead where the ability of an enterprise to accelerate are crucial. The ability to reach the speed necessary for any transformation ahead is something CxOs needs to focus on, this blog post looked specifically at the people side of enterprise acceleration, something that is near and dear to HR leaders, but ultimately really all people leaders of an enterprise.

Looking forward to hearing back from you how the conversations with the people leaders, the CIO / CTO and the vendors are going.
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Event Report: IPsoft Digital Workforce Summit 2018

Event Report: IPsoft Digital Workforce Summit 2018

Summary

  • Digital Workforce Summit On June 7 IPsoft held their annual customer event in NYC, where they showcased the newest features of their digital assistant, Amelia.
  • Amelia is a software platform that uses artificial intelligence to create human-like interactions for helpdesk/support experience, both with employees and customers. People usually interact with Amelia via a chat user-interface, where they enter queries and Amelia responds. What makes Amelia different than just a â€œQ&A chatbot” is that Amelia can understand the context of the conversation, the sentiment and even the history of the interactions making it a much more natural (and useful) conversation.
  • Amelia Marketplace: Provides Amelia training skills "out of the box" in areas like banking, healthcare and insurance.
  • Amelia City:  Opening of IPsoft’s highly interactive customer briefing centre (at their NYC HQ) that showcases Amelia’s features and use-cases.
  • 1DESK: IPsoft's new platform that bridges front-office (UI) experience with back-end (ITSM) services

We’ve all been there. An application stops working, wifi goes down, you forget a password, or you need an answer to a business process like when to enroll for benefits. Raise your hand if you loved the experience you had looking up the solution or dealing with customer service agents. I’ll wait. No hands up? I didn’t think so. The current breed of support tools are usually frustrating and challenging. Does anyone actually like using those automated phone systems? Push 1, 3, *, 7 if you do or 2, #, 5 if you don’t. How about many searching through help documentation or an FAQ for answers? You get my point.

So how do we solve these challenges? How do we get the accuracy and understanding that a human can provide, while still getting the speed, scalability and ease of use of digital solutions? 

On June 7th I travelled to New York to attend IPsoft’s Digital Workforce Summit where they were discussing their vision of how support should work. Notice the event was called “Digital Workforce” not “Digital Workplace” (a very common term these days) because IPsoft develops solutions which they refer to as digital or cognitive assistants. These new “digital coworkers” are quickly becoming part of the workforce, as they help augment the capabilities of internet help desks and customer support call centres and websites.

 

Who is IPsoft?

IPsoft is a privately owned company, headquartered in New York City, founded in 1998. With over 2500 employees and offices in 13 countries, the company developers solutions for automating and managing IT and business solutions.

Below is an image of their product portfolio:

More Than A Chatbot, Meet Amelia

I imagine most of you reading this have at some point interacted with the growing number of “digital assistants” such as Apple Siri, Google Assistant, Microsoft Cortana or Amazon Alexa. These tools can perform a variety of actions from answering questions, to setting alarms, to interacting with appliances and lighting. But have you used such a tool at work? Vendors such as IPsoft and its competitors are hoping that as our trust and comfort with these digital assistants improves, their usage will become as common as using an ATM for doing your banking.

Amelia is more than just a chatbot or a tool that responds to a simple question by searching for the most relevant answer. IPsoft has spent more than 15 years creating a digital model that mimics many of the ways the human brain works. Amelia’s “brain” (a deeper discussion of artificial intelligence is outside the scope of this article) uses several different elements to determine how to respond to people. These include:

  1. Semantic Memory - this is where knowledge is stored
  2. Process Memory - this is where business processes and workflows are stored
  3. Analytical Memory - predictive models for next best actions and constant refinement for accuracy
  4. Episodic Memory - this is where past experiences are stored
  5. Affective Memory - empathy and contextual understanding

MyPOV

Think of the first three as the understanding of your business’s workflows. For example, if an employee asks how to enrol for healthcare benefits, Amelia will process the information she’s been trained on about healthcare providers, deadlines, common questions, etc. and formulate an answer.  Where things get really interesting are the last two facets: experiences and empathy. Rather than just providing a generic answer, Amelia can leverage a personalized history of interactions (ex: Alan, last year you enrolled for plan A) and understand the sentiment of the question. (ex: Alan, I see you’ve submitted two claims for chiropractic work, I hope your back is feeling better) By combining these five elements, Amelia becomes more than just a “static chatbot” which gathers input and performs and query into knowledge bases to provide a generic response. This elevates Amelia beyond just 1:1 question and answer, and enables employees and customers to have more detailed conversations, ones that can become more granular, or even branch into a different direction from the original questions. 

At the Digital Workforce Summit, IPsoft demonstrated two use-cases that impressed me. The first started off as a pretty standard internal helpdesk situation, where an employee had a question about vacation benefits. However, after answering a few questions Amelia then proactively asked the person of they would like to schedule paid time off, much like a real person may do when having this conversation.

The second demonstration was around customer engagement. It highlighted how Amelia can be used to help a customer find products while shopping online. Amelia is able to guide people through the buying process, asking them questions about things like size, style, colour, availability, etc. ideally leading to a more a successful “surf to sale” (ok quote to cash) experience. 

Augmented Assistance Requires Industry Expertise 

While there are several platforms that software developers can use to add artificial intelligence or machine learning into their applications/chatbots, for the most part they don’t provide the knowledge that is needed to train them to work in specific industries. Think of it like hiring a new employee who while skilled in their area, does not actually know anything specific about your company’s products, rules, policies, workflows, etc. You have to invest a lot of time and money training them after they are hired. Digital assistants are similar in that they are only as good as what they have been trained on and what they’ve experienced and learned from. The cost and complexity of training these digital assistants are two of the challenges that early adopters have faced. At the Digital Workforce Summit, IPsoft announced they intend to reduce these issues by providing 16 pre-trained roles for Amelia with more than 140 skills, via a new industry marketplace.

Here is a sample of the skills that IPsoft will be making available to customers using Amelia:

Industry Role Skills
Banking
  • Credit Card Concierge
  • Personal Teller
  • Financial Advisor
  • Mortgage Agent
  • Payments, lost/stolen cards, travel alerts, reward programs
  • Balances, ordering checks, helping transfers
  • Investing services
  • Approvals, balances, interest calculations
Insurance
  • Automotive Agent
  • Property Rental
  • Life Insurance
  • Policy quotes, payments, accident claims
  • Coverage queries, claim processing
  • Variable vs universal life, coverage and rider queries
Healthcare
  • Insurance Benefits
  • Care Concierge
  • Coverage, plans enrolments
  • Booking appointments, refilling prescriptions


Automating ITSM with IPsoft 1Desk

One of the big announcements at the Digital Workforce summit was the launch of IPsoft 1Desk, which they describe as the “convergence of front and back-office functions into a single autonomic framework."

What this means is that automated support for employees can go beyond just “Q&A type chat conversations" with Amelia, they can now result in actions being taken to resolve the issues. For example, if an employee asks questions about wi-fi or email issues, once Amelia determines what the problem is, it can attempt to take corrective actions automatically, or at least step people through the actions they need to take, including showing screenshots or visual guides. 

Building Trust, Understanding and Administration 

While speaking with customers at the summit, it became clear that while they are very interested in the features that Amelia provides, one of the hurdles is in understanding the administration of “digital agents.” As with any nascent technology, companies need to know what new skills they are going to require from their IT staff, their support staff, their developers and their employees (“users”). For example, several customers told me they desire detailed analytics around what’s happening (what type of questions are being asked), what’s working well (which have high-resolution rates or times) and which processes need to be improved (where is automated response failing, what’s frustrating users, etc). 

Augment, not Annihilate. Enhance not Eliminate

Any time you speak to someone about AI or automation these days, the same question always comes up… “What impact will this have on my headcount?" While it is impossible for me to give a generic answer without learning the specifics of each company, I still find it important to emphasize that solutions like Amelia are not intended to replace humans, but rather augment their ability to get their jobs done "better". Better could mean faster, more accurately, higher volume, better satisfaction, more creatively, or a host of other improvements.

Conclusion: Business not Buzzwords

One of the challenges for IPsoft and its competitors is establishing what market “digital assistants” are part of. Is it RPA? Is it IT Service/Support? Is it Customer Experience? Accurately and simply explaining to customers what problems IPsoft can solve is critical. IPsoft is doing a very good job at focusing on the “business” of automation, rather than the technology. Chief Marketing Officer Anurag Harsh gave an excellent opening keynote, where he focused mainly on “what Amelia can do” and not “how it can do it.” I find it too common these days for tech companies to get too detailed about artificial intelligence and machine learning, neural networks and training data sets, confusing customers and raising too many questions. It would be like a car salesperson telling you how the airbags work instead of just telling you that they keep you safe. Don’t get me wrong, there is a need for technical details to help customers understand scale, security and other differentiators, but I think focusing on business use-cases is always the right way to start the conversation. IPsoft is doing well with their use-case focused messaging and the amazing new Amelia City lab/briefing centre.

For further information about IPsoft’s Digital Workforce Summit, here is a short video I record while at the event:

Also, here is a customer case study my colleague Cindy Zhou and I wrote:

How SEB Bank Uses IPsoft to Increase Customer and Employee Engagement
This case study examines SEB Bank's experience implementing IPsoft's Amelia artificial intelligence (AI) platform for use by both internal employees and external customers. Since the Swedish bank deployed Amelia, which it renamed Aida, internal employees have dramatically reduced the resolution times for common IT support issues. Externally, 91 percent of the customers that used Aida rated the solution as "very good" or "good." Aida also helps customers book branch sales appointments for more-personalized service and reduced wait times.

 

Future of Work

Alteryx Offers Gift of Time for Analytical Innovation

Alteryx Offers Gift of Time for Analytical Innovation

Alteryx adds repeatability, automation features so analysts can streamline data prep, step up predictive analysis.

Alteryx eliminates tedious and time-consuming data-prep work so users can spend more time on innovative, advanced analytical work.

This was the core appeal articulated at Alteryx Inspire, the company’s annual customer conference held June 4-7 in Anaheim, CA. Riffing on the event theme “Alter Everything,” CEO Dean Stoecker encouraged the more than 3,000 Inspire attendees to use Alteryx to eliminate error-prone, repetitive spreadsheet drudgery and drive transformations and new business opportunities through data science.

Alteryx CEO Dean Stoecker shares examples of customers that gained time through repeatable data prep and transformation that they could redirect toward analytical innovation.

Alteryx laid out more than a dozen significant product enhancements at Inspire. It also set forth a roadmap toward machine-learning-based recommendation features and cloud-based deployment options coming to future releases. Here’s a closer look.

Alteryx Upgrades for 2018

Alteryx offers four products that it’s moving to synthesize into a tightly integrated platform. The core product that all customers use is Alteryx Designer, a desktop data-prep, blending and analytical tool that was introduced in 2006. Alteryx Server, added in 2010, provides a platform for connecting to data sources, collaborating around and automating Alteryx data workflows, and executing at big data scale. Today the vast majority of Alteryx revenue comes from an even split of Designer and Server licenses, but the company introduced two new products in 2017.

Using proceeds of its March 2017 IPO, Alteryx made two acquisitions in June 2017. Building on the acquisition of Semanta, a data cataloging and governance vendor, the company introduced Alteryx Connect, which offers data-discovery and collaboration capabilities. The assets of Brooklyn, NY-based startup Yhat were developed into Alteryx Promote, which supports analytical model deployment, monitoring and ongoing optimization.

The key announcements at Inspire were around more than a dozen upgrades across all four products. Some of these upgrades are already available, some are set for later this year and a few won't be available until next year. Demos of several of these upgrades drew raves from attendees while offers seemed overdue. Highlights included:

A social data catalog and asset recommendations. Search enhancements now generally available make it easier for users to find the data they’re after. In Q3 Alteryx will beta release an upgrade whereby users will get recommendations on the most popular data sources blended with a particular data source when they drag and drop it into a workflow. 

Workflow caching. This upgrade, set for beta release in Q3, makes it easier to develop reusable data-prep and data-processing workflows by saving interim steps during an iterative design session.

Data profiling. Now generally available, this feature provides statistical details on the number of records, range of values, average value and other details about data set. Quality stats, such as the percentage and number of missing or exception values, will be useful in driving cleanup recommendations.

Python SDK. Alteryx already offered extensive support for use of R-based models, but with so much analytical development moving to Python, Alteryx has added an SDK supporting analytic development in this ascendant language.

Interactive Data Grid. These enhancements to Alteryx Designer’s core interface, planned for Q3 and beyond, drew hearty applause from customers, as it will make it easier for users to search, sort and filter their data without leaving Alteryx.

Alteryx VP of Product Management Ashley Kramer introduces the long list of upgrades the company has planned for 2018 and beyond. 

MyPOV on Alteryx Upgrades: As noted, some of these upgrades, like key data-source connectors for Alteryx Connect, SAML support in Alteryx Connect and Alteryx Server, and the addition of data profiling and the Python SDK, seemed overdue. The workflow caching, Interactive Data Grid and a new Insight Tool for dashboards (which are all future enhancements) were real crowd pleasers. They look like they’ll deliver more problem-solving shortcuts around what would otherwise require tedious and repetitive manual work. Overall Alteryx seems to have stepped up its pace of development, so I’d expect less catch-up development and more innovative new feature development in future releases.

On the Horizon

Alteryx has plenty of competition both from dedicated data-prep vendors, such as Trifacta and Paxata, on the one hand, and advanced analytics vendors, such as RapidMiner, Knime and Domino Data, on the other (DataRobot and H2O are partners). Adding to the competitive pressure on Alteryx has been efforts by the likes of Tableau, Microsoft PowerBI, Qlik and other mainstream analytics vendors to add basic data-prep capabilities.

Roadmap themes going forward for Alteryx include:

  • Knit together Connect, Designer, Server and Promote more closely to support seamless, end-to-end analytic workflows.
  • Add machine-learning based capabilities across the platform to augment the skill of humans and support automation.
  • Build out a container-based cloud deployment approach to support consistent, reusable use of the platform in hybrid and multi-cloud deployment scenarios.

Specific developments on the horizon include a Solution-Based Modeling Utility that will walk business analysts through the predictive modeling steps of data prep, analysis, model building and deployment through a wizard-driven interface. Also coming, in the ML vein, are data formatting, cleansing and join recommendations and natural language query capabilities.

MyPOV on Alteryx. I know from prior research (like this case study on Ford) that Alteryx is a great, time-saving and democratizing option for companies looking to make data-driven decision-making more of a self-service proposition. As was abundantly evident at Inspire, the company is growing quickly and has plenty of enthusiastic users of Alteryx Designer and Alteryx Server.

What remains to be seen is how successfully the company’s new products, Connect and Promote, can be knitted tightly into inseparable platform. Plenty of customers at Inspire told me they are considering adding these components, but few have done so as yet. A notable exception was Shell Oil Company, which offered a presentation on how it’s using Alteryx Promote as part of an effort to spread ML-based predictive analytical capabilities across the company.

What also remains to be seen is the extent to which native data-prep capabilities coming from the likes of Tableau will sap demand for more Alteryx licenses. Alteryx execs contended that these moves will only seed more demand for its platform. Whether entry-level prep happens in Alteryx or not, I see the company’s expanding analytical and model-deployment capabilities as the company’s bigger opportunity. Prep is something to get out of the way and make repeatable. Analytics is where companies are going to get more bang and business impact for the buck.

Releated Reading:
Qlik Hits Reset Button, Rolls Out New Cloud, AI & Developer Capabilities
MicroStrategy Makes Case for Agile Analytics on its Enterprise Platform
Ford Analytics Team Democratizes Data-Driven Analysis

 

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News Analysis - Unit4 releases People Platform Extension Kit - A new way to fit ERP to business needs

News Analysis - Unit4 releases People Platform Extension Kit - A new way to fit ERP to business needs

 

It's not often ERP vendors change the game on customization and extension, this press release from Unit4 deserves attention as it does exactly that.

 

Let's dissect the press release in our customary style – it can be found here:

 

 

Unit4, a world leader in enterprise software for service organizations, announces today the release of new cloud services designed for customers and partners to easily extend its enterprise solutions with custom industry specific apps.

MyPOV – Ok – good summary of the press release.
 

 

 

The People Platform Extension Kit is designed to meet the specific challenges of service-based business models. As organizations modernize their business models to engage people in new ways, Unit4 is providing customers and partners with the freedom to develop differentiating front-end applications, that benefit from the critical data held in their back-office systems.

MyPOV – The innovation here is not the extension kit, ERP vendors have done this since decades in various forms, but the focus / choice of capabilities for service heavy industries.
 

 

 

The People Platform is the foundation for creating intelligent enterprise applications, providing services enabling Unit4 applications to become self-driving by offering access to machine learning capabilities, based on data collection and mining. The Extension Kit gives partners and customers access to the full breadth of Unit4 technology. They can construct custom tailored extensions or complete applications, benefiting from the powerful capabilities of the People Platform and intelligence in Unit4 Business World, becoming first-class citizens of the Unit4 application eco-system. Due to the loosely coupled, micro-service based architecture, partners and customers can develop using their preferred tooling and offer their solutions through any industry-standard marketplace.

 MyPOV – Investment in platforms always pays off, once they work and SaaS offerings run on them – this is another proof point, with the extension kit being based and running on the Unit4 People Platform. Making the extension seamless to the users is a key feature, as user experience should not be aware of what is vendor vs extension capability. For the business user the result of an extension has to be seamless UX integration. 

 

 

 

"We're in an age of business process uncertainty where for the first time technology can do more than what traditional business best practice demands," said Holger Mueller, VP and Principal Analyst at Constellation Research. "We're seeing enterprise acceleration at unprecedented rates with organizations moving faster than ever before. They can be a disruptor or be disrupted and it's their people that can make the difference. By empowering them to purpose build services and small apps in the areas that matter, connected to their enterprise applications, they can break away from the monolithic nature of ERP. Through low-code technology like this, people in business become smarter and empowered to work more effectively, producing better value in their work."

MyPOV – Solid quote... ok. Might be a little biased here. The key aspect is the low code and small apps ability. It expands the number of people available to build extension, a key aspect as often SaaS / ERP software does not work well for areas of the business that will never receive Its attention or justify the cost of a consultant or even developer to make things run smoothly. The other key aspect and innovation is that this makes ERP less monolithic, meaning there is only one way to do things. Being able to create lots of small applications with the extension kit – they may have similar / duplicate capability – but work for different users, is a major break through in ERP architecture.

 

 

 

 

"The everything as a service economy is driving business model changes around the world," said Stephan Sieber, CEO of Unit4. "As customer demand for simple online subscription services and rapid value grows, organizations are modernizing business models to create greater efficiencies and to engage customers, employees, and business partners in new ways. Core enterprise systems are vital, but do not deliver competitive differentiation on their own. Our customers have unique strategic processes, and by opening our solution platform for simple application development irrespective of programming language or industry marketplace, they can build very specific apps that deliver rapid value and seamless user experience. Essentially this is the next generation of customization technology enabling organizations to have exactly what they want and need to be successful."

MyPOV – Good quote from Sieber, focusing on what matters – smooth running software, now enabled by technically savvy – but non-developer – resources in the enterprise. 

 

 

 

 
Pricing and Availability
The People Platform Extension Kit and pricing details will be available in Fall '18. Customers and partners can sign up to the Early Adopter Program from June.
 MyPOV – Always good to see immediate availability – at least for early adopters already in June. 
 

Overall MyPOV

Enterprise software will never be a 100% fit for enterprise automation needs. The move to the cloud has made the category even more resistant / unable to move to the perfect fit. It's good to see that in the more modern version of SaaS / cloud-based ERP software, vendors are starting to overcome these limitations. That requires to build on a modern platform and to expose these services, not only to technically savvy developers, but also to reasonably technology aware business users. The ability for business users to create smaller, department level or division wide applications, which can overlap, be redundant is a key step to move of the monolithic heritage of ERP. Good progress by Unit4.

On the concern side, there can be the situation of the what Disney showed well starring Micky Mouse in the Sorcerer's apprentice movie. In this case too many custom apps being created, performance, reliability, compliance and more issues can arise from the approach. But it's better to try a learn than not do the move, so it will be interesting to see what Unit4 customers will be building and what overall experience will be.

But for now, congrats to Unit4 on a major milestone of making ERP fit better to the needs of service businesses.

 

 
 
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Discussion with Logitech: The Rise of Video Meetings: Smart, Affordable Collaboration

Discussion with Logitech: The Rise of Video Meetings: Smart, Affordable Collaboration

Improvements in both technology and culture are contributing to a rise in the use of video during webconferences. I sat down (over video of course) with Scott Wharton, GM of Logitech's Video Collaboration division to talk about the state of the market.

 

 

AI Investment Rising Significantly Among Early Adopters

AI Investment Rising Significantly Among Early Adopters

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Sixty percent plan to increase investment by more than 50% compared to last year

Early adopters are ramping up investment in artificial intelligence (AI) technologies in 2018 reveals an AI study conducted by Constellation Research. Sixty percent of C-level executives surveyed say their organizations plan to increase investment in AI by over 50% compared to last year (Figure 1). AI budgets, however, remain relatively modest with 92% of respondents expecting to spend less than $5 million on AI in 2018.

Figure 1. AI Budgets Rising in 2018

Modest AI budgets signal cautious adoption and deployment of foundational AI technologies for now. However, because AI often delivers successes exponentially, Constellation expects AI budgets to continue to rise by more than 50 percent annually for the next four to five years as AI R&D yields bigger successes at an increasing pace.

Firms investing in AI to improve the customer experience and drive growth

AI adoption highest among IT; Customer Service; and sales and marketing departments

The Constellation Research 2018 AI Study reveals firms are investing in AI to help improve the customer experience and drive growth. C-level executives surveyed by Constellation reported the highest levels of investment and adoption in the following departments: information technology; customer service/commerce; sales and marketing; and employee productivity.

Fifty-two percent of respondents report AI projects in production or in pilots in the IT department, 50 percent report production or pilot AI projects in customer service/commerce, 46 percent report AI projects in production or pilots in sales and marketing, and 36 percent report AI projects in production or in pilots in employee productivity (excludes manufacturing employee productivity) (Figure 2).

Figure 2. AI Spending By Department

AI spending within the organization

Driving this trend, explains Cindy Zhou, a Constellation Research principal analyst, is the ease with which firms can acquire AI capabilities for these departments. Packaged apps with AI capabilities are widely available for sales, marketing, employee productivity and commerce. As stated earlier, packaged apps with AI capabilities are often features of existing software or a platform that can simply be "turned on."

"As far as sales, marketing, and customer service organizations are concerned, AI is already here," says Zhou. "Salesforce and Microsoft for example, sell applications with AI capabilities rolled into the core product, or they are sold as add-ons. Salesforce Lightning platform customers automatically get basic Salesforce Einstein capabilities with their contract. If customers need more robust AI capabilities, they can upgrade," she explains, speaking about Salesforce Einstein, the company's AI layer within the platform, which powers a variety of built in and, in some cases, optional skills and application capabilities.

Highlights from the Study

  • Widespread adoption with caveats: Seventy percent of respondents to the Constellation 2018 AI Survey indicate their organization currently employs some form of AI technology. This number, however, tells only part of the story. AI budgets remain relatively modest (see below), and, even among early adopters, no organizations in the study have deployed true AI.
  • AI investment modest but growing fast: Ninety-two percent of respondents say they will spend less than $5 million on AI in 2018. However, respondents indicate significant year-over-year increases in AI budgets, with 60 percent of respondents registering a 50 percent increase in AI budgets compared to last year.
  • Firms employ three primary modes of AI development: developing homegrown applications by building out data science teams and using open source frameworks; developing homegrown applications using cloud-based ML and deep learning (deep learning services; and adopting packaged applications with AI capabilities.
  • Companies are investing in AI to help improve the customer experience and drive growth. When Constellation asked respondents to indicate the department(s) where AI is planned or implemented, IT, customer service/commerce, sales and marketing, and employee productivity ranked among the departments receiving the most planned or in-production AI spending. Driving this trend is the ease with which firms can acquire AI capabilities for these departments. Packaged apps with narrow AI capabilities are widely available for sales, marketing, employee productivity and commerce.
  • Potential AI-proficient talent shortage. Rising demand for workforce talent with AI proficiency poses a potential challenge for organizations that want to implement AI solutions. Eighty percent of executives say their organizations need to hire additional human capital to implement AI solutions. Seventy-two percent of organizations say they obtain new talent for AI projects via recruiting. Taken together, these two trends have the potential to culminate in a talent war as more AI projects come online.
  • Executives are feeling the pressure. Eighty-eight percent of executives say they expect their roles to change as their organizations adopt AI. Fifty-four percent of executives say they will need to understand how to restructure the business to accommodate new business models, 50 percent report a need to acquire data expertise and 48 percent report needing to learn how to motivate an AI-augmented team.
  • Resistance to AI: Fifty-two percent of respondents report resistance to AI within the organization. Top sources of resistance among those who reported resistance to AI include lines of business at 67 percent, IT at 32 percent and HR at 25%.
  • Data privacy strategies are not yet ubiquitous among firms using or developing AI. Among firms using AI, 23 percent say their organization does not have a data privacy strategy to protect personal information ingested by AI. Thirty-one percent of organizations       currently using AI do not have an opt-in policy to handle personal information ingested by AI.

About the Study

The Constellation Research 2018 Artificial Intelligence Study leverages findings from the 2018 Constellation Research Artificial Intelligence Survey which assesses the state of AI among the first movers, early adopters, and fast followers that comprise Constellation's subscriber base.

The Survey asked C-level executives about the state of AI investment and deployment in their organizations, budgets for AI investment, technologies driving AI development, how AI might impact executives and the workforce, sources of internal resistance to AI, and privacy.

For the purposes of both the Survey and the Study, Constellation defines artificial intelligence as the culmination of technologies including deep learning, neural networks, natural language processing, and big data/predictive analytics to produce software that is self-improving, automatic, and emulates human intelligence.

Seventy-four percent of responses came from the C-suite, with CEOs making up 26 percent of the sample; CIOs, 20 percent; CTOs, 10 percent; CDOs, 6 percent; CMOs, 2 percent; and other C-level executives, 10 percent. There were no CFOs in the survey sample.

The sample consists of respondents from twelve different sectors, mostly in the United States. Sectors include automotive; consumer electronics; consulting/systems integration; finance/insurance/real estate; government; healthcare/medical/pharmaceutical; media/interactive/PR agency; news/entertainment; retail; technology-hardware, software, services; and telecommunications or travel/hospitality.

Total revenue of respondents' firms in 2016 range from less than $10 million to more than $1 billion. Twenty-nine percent of respondents reported revenue of less than $10 million; 14 percent reported revenue between $10 million and $50 million; 29 percent reported revenue between $50 million and $500 million; and 29 percent reported revenue of over $1 billion.

Download a complimentary copy of the Constellation Research 2018 AI Study.

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Microsoft Acquires GitHub

Microsoft Acquires GitHub

On June 4th, 2018 Microsoft announced their intention to acquire GitHub. My research focuses on team collaboration, not application development, so my interest in this deal is around areas of working together, community, etc. Here are a few thoughts:

  • If/when/how Microsoft could create a use-case focused version of Microsoft Teams for developers
  • What solutions could be created by adding GitHub data into the Microsoft Graph? Could this help developers promote their projects, connect with new contracts, etc? Could it help employers find developers? Could this help create better developer communities?
  • How will this enable Microsoft to compete against Atlassian's combination of BitBucket and Stride?

For more information related to the technical aspects of application development tools and platform, follow my colleague Holger Mueller.

Similarly, Ray Wang has some great thoughts about this from a business standpoint, especially around enticing a new generation of developers to think about Microsoft.

Here is a collection of tweets showcasing some of the thoughts from my Constellation Reseach colleagues and me. 

Host Analytics Simplifies Collaboration Between Finance and Business Users

Host Analytics Simplifies Collaboration Between Finance and Business Users

Host Analytics introduces MyPlan, MyPlan Mobile to enable budget owners on the business side to collaborate on forecasts, plans and agile course corrections.

 

Budget-owners on the business side don’t want to use software designed for financial professionals any more than finance types want business people interacting with data or software features they shouldn’t see or touch.

 

These prevailing instincts are the reason Host Analytics (Host) recently added a business-user-oriented MyPlan interface for its cloud-based enterprise performance management (EPM) system. At its May 21-23 Host Perform user conference, the company followed up by announcing MyPlan Mobile, a device-native app (initially on iOS) designed to keep executives who are on the go connected to budgeting and planning processes.

 

Held this year in Dallas and attended by some 700 customers, Host Perform also highlighted recent upgrades and coming attractions to the vendor’s software-as-a-service-based EPM platform. But MyPlan and MyPlan Mobile were the clear centers of keynote and expo-floor attention.

 

Design for Business Users


EPM vendors are all fond of saying that budgeting and planning should be a team sport. And in a perfect world, finance wouldn’t rely on emailed spreadsheets and other disconnected, manual methods to gather data and collaborate with budget owners around forecasts and plans. EPM systems give finance a centralized, collaborative platform for budgeting and planning, but these systems have not typically seen broad adoption outside of finance. In Host’s assessment that’s because EMP systems are designed, first and foremost, for finance professionals and are not familiar or intuitive for business users.

 

Rather than dumbing down its usual interface, Host developed MyPlan through clean-sheet design sessions with budget-owning business users. What these users want, Host discovered, is a simpler interface in which they can see where they stand, meaning actual performance to date, see where they’ll land, meaning at the end of current budget period, and see what they can plan, meaning how they can adjust their spending and allocations to meet budget expectations.

 

The result was the MyPlan interface (shown below), which was made generally available in March. The interface gives the budget owner – it this case, a marketing executive – a clear sense of where they stand in terms of people, equipment, travel and program expenses. Green and red colors highlight where forecasts and budget figures are on track and where there’s variance.

 

 

Host's MyPlan (top) and MyPlan Mobile interfaces (above) are designed to show business users where they stand on actual performance and where they're forecasted to land by the end of the current financial period. By selecting a wrench icon, users can test changes, reforecast and then update their plans in order to meet budget expectations.

 

The MyPlan Mobile App, which will be released in the second half of 2018, will enable employees who are on the go to see the latest results and then respond, by adding or deleting a planned employee, adding or deleting an asset, or approving or rejecting an expenditure and submitting the update to finance. In a role-playing scenario during the opening keynote at Host Perform, a corporate lawyer used MyPlan Mobile to reviewed the latest expenditures for the Legal department, make changes to his plan, reforecast and then submit updates to his budget.

 

MyPOV on MyPlan and MyPlan Mobile. Like other EPM vendors Host offers integrations to Microsoft Excel, but the company says the business users it talked to when designing MyPlan pointedly did not want a spreadsheet-like grid for collaborative budgeting and forecasting. As I see it it’s a clean design that keeps things simple, but the strength of the MyPlan interface is that it’s a connected and collaborative view of each stakeholder’s budget and plan. Users can click on the wrench symbol to reallocate resources, optimize and otherwise update their plans in order to meet budget expectations. I particularly like the fact that MyPlan eliminates toggling between applications by exposing everything the user needs within a single interface.

 

Pricing details were not disclosed by Host, but customers will pay for a contributor subscription plus an upcharge for the MyPlan interface that will also include the coming MyPlan Mobile app.

 

Coming Attractions

 

Among the recent, soon-to-be released and on-the-horizon upgrades showcased at Host Perform, here are a few highlights:

 

  • Dashboard upgrades added with Host’s May 25 Spring release introduced server-side custom calculations that can be reused across dashboards, speeding development and ensuring consistency.
  • Drill-through capabilities expected this summer will enable users to see more details behind the numbers, whether they’re about assets, employees, transactions.
  • One-click rolling forecasts now on the roadmap will make it easier to do quarterly and monthly forecasts. You’ll be able to create copies of forecasts and try new scenarios around selected parameters with a single click.
  • MyPlan V2 upgrades on the longer-term roadmap will introduce “smart” recommendations for first-pass budgeting and ongoing adjustments to spending based on patterns in historical data.

MyPOV on Host’s path forward:  This is just a sampling of the upgrades Host has in the works. The company also detailed long lists of planned upgrades to its planning, consolidation, modeling and reporting capabilities. Taken together with the MyPlan initiative, there’s clearly healthy investment in supporting both deeper functionality and broader deployments. If there’s one criticism it’s that the move into machine-learning-based predictive and prescriptive capabilities is just getting underway, but it’s early days for these sort of capabilities across the EPM space.

 

The big trend in EPM is that companies are going cloud and want to take the power of planning into many operational areas. Host was already seeing some of the largest cloud-based EPM deployments, but with MyPlan and MyPlan Mobile, the company is raising the bar. One big customer in the property management space that already had 6,000 Host subscribers added 500 MyPlan users soon after it was released. It’s an early sign that Host is poised to win even bigger and broader deployments.

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