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You’re Still #OpenForBusiness — and NetSuite is Here to Tell Your Story

March 21, 2020 NetSuite

You’re Still #OpenForBusiness — and NetSuite is Here to Tell Your Story

Amidst the upheaval and unprecedented change around the world today, people are showing resilience, compassion and grit.

Many businesses, and NetSuite customers in particular, are stepping up to the challenge. The answers often pour out of creative minds in the middle of the night. They are born sometimes out of necessity — out of goodness and serving others — and sometimes just out of pure survival instinct.

This perseverance, drive and quick thinking are helping to keep them #OpenForBusiness. It’s also inspiring and a story NetSuite wants to share.

Already, customers are demonstrating how it’s possible to remain #OpenForBusiness:

Language learning app Duolingo is teaching students new languages for free as parents adjust to homeschooling and online learning.
Dog is Good continues to spread joy with its pup-inspired apparel while giving back to pet and veteran organizations.
Kiva is making its small-business loans more accessible to hard-hit entrepreneurs by expanding their eligibility requirements and enacting longer grace periods.

That’s just a small sampling of the steps people have taken in a few short weeks or less, and there’s plenty more out there. NetSuite wants to help share those stories. This is a critical time for our businesses, our country, our world. It’s a time to turn toward community, and the NetSuite community can be a valuable one.

Here and over on Grow Wire, where you can already find stories of businesses going above and beyond, NetSuite will be sharing how our community is helping others — and themselves.

#OpenForBusiness will be a regular showcase of NetSuite’s amazing customers that are very much still ready to serve customers of their own.

Please follow NetSuite’s social channels to see the latest from some of the greatest businesses on the planet.

Don’t forget we’re in this together.

Posted on Fri, March 20, 2020
by Barney Beal filed under

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If you’re worried about the end of privacy, don’t waste your outrage on Clearview AI

March 5, 2020 Big Data

It’s easy to feel outrage at Clearview AI for creating facial recognition trained with 3 billion images scraped without permission from sites like Google, Facebook, and LinkedIn, but the company should be only one of the targets of your ire. Pervasive surveillance capitalism is designed to make you feel helpless, but shaping AI regulation is part of citizenship in the 21st century, and you’ve got a lot of options.

On Tuesday, Senator Ed Markey (D – MA) sent a letter to Clearview AI demanding answers about a data breach involving billions of photos scraped from the web without permission and the sale of facial recognition to governments with poor human rights records like Saudi Arabia. That would be scandalous news for most companies, but not Clearview AI. For context, here’s what the past week looked like for the company:

News emerged Monday that Clearview AI is reportedly working on a security camera and augmented reality glasses equipped with facial recognition.

Following a data breach reported last Wednesday, we learned that Clearview AI’s client list includes more than 2,900 organizations, including governments and businesses from around the world. In all, it comprises businesses from 27 countries, including Walmart, Macy’s, and Best Buy, and hundreds of law enforcement agencies, from the FBI to ICE, Interpol, and the Department of Justice. Tech giants like Google and Facebook sent Clearview AI cease-and-desist letters last Tuesday.

Back in January, the New York Times’ Kashmir Hill, who first brought Clearview AI to people’s attention, reported that the company was working with more than 600 law enforcement agencies and a handful of private companies. But reporting last week brought the Clearview AI client list into sharper focus, along with the number of searches by each client. The story also revealed that a total of 500,000 searches had been made.

A breakdown of an APK version of the Clearview app found by Gizmodo on a public AWS server the same day signals the potential addition of a voice search option in the future.

Clearview AI CEO Hoan Ton-That previously told multiple news outlets the company focuses on law enforcement clients in North America, but an internal document obtained by BuzzFeed News shows government, law enforcement, and business clients around the world.

Everything we’ve learned about Clearview in the past week gives credence to the New York Times’ claim in January that the company might end privacy, and to VentureBeat news editor Emil Protalinski’s assessment that Clearview is on a “short slippery slope.”

If what Clearview AI did and continues to do makes you angry, then you’re probably with the majority of people who lack understanding of data privacy law and feel you have little to no control over how businesses and governments collect or use your personal data.

If you believe privacy is a right that deserves protection in an increasingly digital and AI-driven world, don’t aim your anger at the Peter Thiel-backed company itself. The way it operates may be insensitive or even horrifying, but save your questions for the businesses and governments working with Clearview AI. People deserve answers to the kinds of questions Senator Markey asks about the extent of the data breach and Clearview’s business practices, but people should also question policy that enables Clearview to exist.

Because Clearview AI doesn’t matter as much as the public’s response to how those in positions of power choose to use Clearview’s technology.

What AI regulation looks like

Clearview AI is not the only company inciting fear and outrage. In the past week or so, everyone from Elon Musk to Pope Francis have called for AI regulation.

In addition to the Clearview AI story, we also learned more recently about NEC, a company that started research into facial recognition in 1989. One of the largest private providers of facial recognition in the world, NEC has more than 1,000 clients in 70 countries, including Delta, Carnival Cruise Line, and public safety officials in 20 U.S. states.

The EU is considering a pan-European facial recognition network, while cities like London, which has the most CCTV cameras of any city outside China, are launching live facial recognition technology that makes it possible to track an individual across a web of closed-circuit cameras.

In a very different set of developments, last Thursday we learned more about how the U.S. Immigration and Customs Enforcement agency (ICE) uses facial recognition software. The Washington Post reported that ICE has been searching a database of immigrant driver’s licenses without obtaining a warrant. This policy may terrorize immigrants and their families, put more people at risk by increasing the number of unlicensed drivers on the road, and deter immigrants from reporting crimes.

In the past month or so, the White House and European Union have attempted to define what AI regulation should look like. Meanwhile, lawmakers in about a dozen states are currently considering facial recognition regulation, Georgetown Law Center for Privacy and Tech said earlier this year.

But defining AI regulation isn’t something tech giants or machine learning practitioners should work out on their own. It’s up to ordinary people to recognize that, as Microsoft CTO Kevin Scott said, understanding AI is part of citizenship in the 21st century, and there are many ways to influence change.

Ways to respond

Clearview AI and tech giants with unprecedented power and resources — like Amazon and Microsoft — want to establish a market for the sale of facial recognition software to governments.

These companies are trading in a surveillance capitalism market with the potential to suppress fundamental rights and exacerbate over-policing and discrimination. This is all the more concerning after NIST’s December 2019 study found nearly 200 facial recognition algorithms currently exhibit bias, with a high likelihood of misidentifying Asian American and African American people.

That’s a lot to take in, and outrage is understandable, but it’s important to not give in to despair. Experts like Shoshana Zuboff and Ruha Benjamin argue that making people feel helpless is the point of surveillance capitalism.

We’re living on the verge of a COVID-19 pandemic, we just saw the largest stock market drop since 2008, and climate change remains an existential threat. But we still have a lot of options when it comes to shaping AI regulation:

Call your member of Congress
Ask political candidates running for office about the issues
Find out if facial recognition or privacy regulation is being considered in your state
Read the Partnership on AI’s facial recognition paper to better understand how the tech works
Formulate your own definition of acceptable or ethical use of the technology
Learn why people support or oppose the idea of people owning their own biometric data
Consider why a Trump administration official told VentureBeat that San Francisco’s ban of facial recognition is an example of overregulation
Understand why a bipartisan group of lawmakers in Congress don’t want facial recognition being used at protests or political rallies
Find out why experts in the U.S. worry about the use of live facial recognition that can track a person across a web of CCTV cameras in real time that’s spreading to cities like Buenos Aires and Moscow
Ask how businesses and governments put AI principles into practice
Understand why making biometric data the property of individuals is a growing policy solution but learn why some data and privacy advocates say that’s dangerous

If you live in California, under the new Consumer Privacy Protection Act (CCPA), you can send an email to privacy-requests@clearview.ai to request a copy of data the company is collecting about you and ask it to stop. Vice reporter Anna Merlan and colleague Joseph Cox sent such a request to Clearview AI. After supplying the company with a photo for a search about a month ago, last week Merlan received a cache of about a dozen photos of herself that had been published online between 2004 and 2019. Clearview told her the images were scraped from websites, not social media, and agreed to ensure those images no longer appear in Clearview AI search results.

Is the New York Times right? Is Clearview AI going to make it impossible to walk down the street in anonymity? Is it the end of privacy? That’s up to you.

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Big Data – VentureBeat

Hey Einstein, Brian Solis is talking to you. And you’re talking back

January 8, 2020 CRM News and Info

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Hey all, Happy New Year! As you probably can guess, I’m heads down and deep into the CRM Watchlist 2020 submissions so rather than leave you out in the cold (and depending on where you are it IS cold) I thought that I’d start the new year just right with the pitch perfect Brian Solis kicking it off with a guest post.

I’m pretty sure that you know who Brian Solis is. And if you don’t, then it’s on you. But just in case, I figured that I would give you an introduction to the guy who qualifies as a legend in parts of the business world. As jokey as I get, no joke here.

Brian is not only a dear friend, but he is the man who you can point to and say: Brian revolutionized the PR industry by bringing social into it. Of course, as a result of him doing that, he gained his own celebrity and thus Hollywood got attracted to him. Check out the forewords to his earlier books and you will see they are by Ashton Kutcher and Katy Couric. That reflects the kind of impact he had on an entire industry. Hollywood provides the moths to the lights.

But he is SO much more than that. Brian is an expert in not just customer experience, but design and user interfaces and the user experience. He’s an expert in making your personal digital life something that isn’t toxic but instead is valuable by knowing when to dial it down, dial it up, reduce the stress and increase the effectiveness of your digital life. He is also a thought leader who focuses on digital transformation and annually, while still with Prophet/Altimeter, did a survey that was an industry standard when it came to valid work on the state of digital transformation (most recent edition here) – without any of the typically included hype or misdirection and misinterpretation of the term. The work was/is the real deal.

The intersection of all of this has led Brian to a deep understanding of the enterprise technology market – especially the CRMish, CX, customer engagement world and the vendors within.

The other thing? The man has a big big heart and is loved by those who know him.

So what better way for me to kick off the new year than with one of Brian’s cogent observations on something in the enterprise tech world that encompasses all of his expertise in one place. Salesforce, Einstein and voice.

So, Happy New Year, all of you folks out there, and take it away, Mr. Solis.

“Alexa, what are the most important trends in customer calls with our sales reps?”

“Brian, according to real-time analysis of this customer call, here are the following recommendations and next best actions to help.” – Siri

Voice is part of our everyday life. Whether it’s Alexa, OK Google, or Siri, how we communicate with devices and information is not only becoming conversational, it’s changing our behaviors and expectations as a result. Now, asking questions, searching for information, interacting with apps and services, and making decisions is much more intuitive, productive and natural. It was just a matter a time until conversational interfaces would permeate the enterprise.

brian solis head Hey Einstein, Brian Solis is talking to you. And youre talking back — Brian Solis

In 2019, I was introduced to Aera Technology and the concept of the Self-Driving Enterprise. In an interview with CEO Frederic Laluyaux, I learned how Aera connects disparate (and aging) ERP systems to introduce a next generation cognitive layer that connects data, insights and people in an on-demand operational model. Aera provides Google-like indexing capabilities with an Alexa-style interface. At one point in our conversation Laluyaux picked up his iPhone and asked, “What’s my forecast?” Instantly, a professional, yet friendly voice responded, “On track at $ 1.2B with an additional $ 134M revenue opportunity. Do you want the regional breakdown?”

By connecting disparate data, and through voice and AI, Aera is essentially creating a digital brain for the enterprise. It becomes the repository for knowledge and IP, one that serves as a cognitive operating system and enhances human decision-making. It’ll only get smarter and more efficient over time.

Shortly after meeting with Aera, I attended Dreamforce 2019. At the event, Salesforce announced that it was bringing AI-powered voice capabilities to every customer and employee experience across the Salesforce Customer 360 Platform. Like Amazon Echo’s “Alexa,” the voice prompt, “Hey Einstein,” became the call sign of the event, with Einstein-powered voice apps, skills and intelligence literally giving a voice to its entire ecosystem.

While Aera is automating the back office and leading the industry in creating a “Self-Driving Enterprise,” Salesforce is championing the automation of CRM and the front office. And with the incredible footprint and momentum Salesforce has in the industry, it will bring a level of attention to voice automation that will accelerate evolution and adoption.

Between Aera, Salesforce and the rest of the enterprise vendors who follow, it’s clear that 2020 will be the year that enterprise data gets a voice.

Hey Einstein: How do we deliver better user experiences and ultimately CX through voice?

At Dreamforce 2019, Salesforce announced three new pillars of Einstein Voice, its enterprise voice platform. Each layer is aimed at ushering in a voice-enabled enterprise that leads to radical improvements in optimizing data input, user engagement and insights:

Einstein Voice Skills empowers admins and developers to build custom, voice-powered Salesforce apps tailored to any role or industry, giving every employee a personalized CRM guide.

Service Cloud Voice integrates telephony into a unified agent console, enabling Einstein to offer recommendations and next best actions in real-time to improve service experiences.

Einstein Call Coaching helps managers spot trends within conversational data and provide sales reps with the best practices and insights needed to optimize every customer call.

Hey Einstein, Brian Solis is talking to you. And youre talking back — Prototype Einstein Smart Speaker

Marc Benioff

Salesforce Partners with Amazon to Bring Alexa-functionality to Einstein Voice

To help Einstein find its voice, Salesforce announced a partnership with Amazon to embed Einstein Voice functionality into Alexa devices. The company debuted a prototype Einstein smart speaker to showcase the new capabilities on stage. The company clarified that the smart speaker itself wasn’t coming to market, but it sure was clever and honestly, quite adorable.

In a demo during the mainstage keynote (see video above at 1:45:58), Salesforce Co-Founder Parker Harris asked the Einstein smart speaker, “Hey Einstein, what can you do?”

Einstein replied, with a curious British accent, “You can ask me for many of the amazing Einstein features like ‘give me my account insights’ or ‘Einstein predict my quarterly forecast.’ Note, that my capabilities are always growing.”

The idea here is that Einstein will apply natural language processing to everyday workflow, across the entire Salesforce ecosystem, i.e. service, marketing, sales etc. Adding an AI-powered voice layer will help teams gather more valuable insights that drive smarter work and more personalized user and customer experiences.

Einstein Gets His Skills

Salesforce introduced Einstein Voice Skills for developers to immediately create custom voice apps, capabilities and experiences without needing any knowledge of voice technology. Beyond the skills for extracting insights from data, there will also be skills to improve data input and integration, the bane of any CRM system. As they say, the better the data, the better the insights and predictions.

The ease of incorporating new Einstein Voice Skills was demonstrated live on stage by Qingqing Liu, Principal Mobile Architect at Salesforce. Here’s a quick demo (see video above at 1:48:14).

Einstein Call Coaching Connects Leaders to Conversational Trends

Beyond Einstein Voice Skills, Einstein Call Coaching will also offer executives new ways to extract insights on business processes, service cases, CSAT performance and more.

For instance, AI-powered natural language processing is coming to Sales Cloud to help give managers visibility into conversational data, i.e. what competitors are repeatedly coming up in calls? What are some of the most common questions asked? How are representatives responding? What products are customers asking most about? How are the best reps performing?

Beyond expediting access to this important information, leaders gain real-time insights necessary to expedite on trend strategy development, program execution and resulting measurement.

Einstein in the Service Center Will Automate Authentic Human Conversations

Improving employee experiences through voice and AI is just the beginning. Einstein Voice is also set to radically improve customer experience as well.

In the opening keynote, Harris along with chairman and co-CEO Marc Benioff demonstrated how AI-powered voice was set to transform CRM. Richard Socher, chief scientist at Salesforce, joined Harris and Benioff on stage where he was asked, “Can our customer’s customer call and talk to Einstein?”

Socher responded with an affirmative, “Einstein will sit in the service center.”

He then proceeded to share a real-world example of a common experience that could be fully automated by Einstein and its new Service Cloud Voice integration.

Socher called a fictitious car rental company after hours in an attempt to extend his rental period. The system answered with a personalized greeting, “Hi Richard, I’m the digital assistant for Adventure Car Rentals. I’m here to help outside of business hours.”

Socher then went on to demonstrate how the system could naturally interact with customers based on common scenarios while using customer data in real-time to personalize next best actions at every step. At one point, the system identified that his current class of vehicle wasn’t available for the extended days, but it matched Socher’s loyalty information with relevant inventory to upgrade him on the spot. Once everything was agreed upon, the system finalized the details and confirmed on all sides…all without human intervention. (see video above at 1:41:26)

Service Cloud Voice Coaches Representatives in the Moment

In reality, today’s interactive voice response platforms (IVRs) leave customers feeling disenchanted and frustrated. Chat bots are still largely basic. Self-help knowledge bases are inhuman.

Voice and AI are starting to get to the heart of the matter…real-time, contextual, outcome-focused customer experiences. Add to this the ability to anticipate or predict customer needs, voice-powered automation offers the ability to combine personalization and humanization, especially when it counts.

This is where Service Cloud Voice can play a significant role while the rest of the cognitive enterprise takes shape. It integrates smart insights into critical moments of customer engagement. During customer calls, Salesforce’s AI-powered NLP can assess real-time transcripts to help customer service agents serve up recommended responses, knowledge articles and next best actions in the moment. This connects customers to desired outcomes quicker and with greater accuracy giving customers a better support experience and leaving them satisfied.

Voice is the Now Frontier in the Future of Work and CRM

While this is a glimpse of the future of CRM, it is a future that’s already starting to materialize.

AI-powered voice automation is changing the game for user and customer experiences. It’s also changing how the workforce works and how customers interact with brands.

Voice and AI are fueling an IO renaissance, allowing for every employee and customer touchpoint to be reimagined. Adding voice and imagination to the mix, frees up cognitive resources to invent new work and customer experiences. CIOs, CDOs and CxOs must align technology and business value moving forward. They’ll need help from vendors to separate hype from innovation and best practices.

As the real Einstein once said, “Imagination is more important than knowledge. Knowledge is limited. Imagination encircles the world.”

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AI Weekly: With AI-empowered devices, consider what you’re buying

December 1, 2019 Big Data

It’s Black Friday, and throngs of people are shopping for deals on virtual assistant-powered smart home devices from the likes of Amazon and Google. The initial appeal of smart speakers, smart displays, voice-controlled lights is obvious, and according to Strategy Analytics, growth in the smart speaker segment alone is expected to grow 57% by the end of 2019. But as we consider whether these devices will make our lives easier or better, are we giving enough thought to the trade-off between convenience and privacy?

It’s essentially the same paradigm, writ small, that the world is facing with AI in general: AI has delivered unprecedented capabilities, but it has also engendered an uneasy sense that we’re losing control over these new tools and technologies. But when you consider buying a device for your home that has an AI assistant on board, you can focus on the questions you should always ask of technology: Does this technology make my life better or easier? What are the trade-offs, and are they worth it for the convenience?

Although those are heavy questions generally, when it comes to Black Friday-Cyber Monday weekend and you’re looking at a killer discount on some smart home device and wondering if you should click the Buy button, it’s less of an existential conundrum and more of a practical one. What will you use a Google Home Mini for, exactly? Do you really want to turn on music in your kitchen every day by shouting at an Amazon Echo Studio that gets your request right only most of the time? What is the purpose of a “smart” night light?

Yes, a smart night light. That’s a real thing that exists in the extended universe of Alexa-compatible smart home products. And its utter banality serves as an excellent illustration of why we need to ask ourselves those aforementioned questions.

This particular smart night light is made by Third Reality and is certified as “Made for Amazon.” It’s actually an accessory that attaches to the Amazon Echo Flex. The Flex is a palm-sized device that plugs into your wall outlet and can control things like your lights and thermostat. It has its own little mic and speaker that let you not only control Alexa, but talk to people through other Alexa devices in other rooms like an intercom. In a way, the Flex is almost an accessory itself, because it’s designed to be a part of a larger network of Alexa devices rather than a standalone device. It has a USB port on the bottom where you can charge a phone or plug in an attachment, such as a smart night light.

The smart night light becomes part of your Alexa device list, and you can manage and control it remotely with the Alexa app on your phone. Features include the ability to adjust the brightness from 1% to 100%, choose from a variety of colors, and determine when the light goes on or off.

In other words, it does everything a night light does, but with brightness and color options, and you have to manually set when it turns on and off. In addition to the time you have to spend setting it up and configuring the settings, the smart night light costs $ 15, and the Flex costs $ 20. You can buy them together for $ 32.

By contrast, you can get a four-pack of non-smart night lights for $ 9 on Amazon. They turn on when they sense that the light in the room is too low. They shut off when the light becomes brighter. Installation comprises plugging them into a wall outlet.

Arguably, the non-smart night light is already a perfect product — cheap, easy to install, reliable, purpose-built — so why does the smart night light exist? Sure, it’s neat to be able to do things like adjust brightness, pick fun colors, and control it with your phone, but you’d have to stretch to make the case that it’s making your life better. It’s certainly not making anything easier than non-smart night lights, and it’s not more convenient. And it costs more money.

There’s nothing wrong with wanting a silly, fun device, and there’s nothing wrong with paying a little more for it than you need to. But there is a larger cost to consider: Amazon has grand plans for your home. The company is clear that it wants to put Alexa everywhere it possibly can, and just this week it rolled out increased abilities to build its intelligence to even more IoT edge devices with AWS IoT Core and enabled Alexa controls for new classes of objects in the home. Like other major virtual assistant platforms, Alexa devices record audio of your commands, necessitating oversight by you, the user. There are problems with Alexa’s user-submitted answers, too. Amazon also owns video doorbell maker Ring, with its troubling privacy and surveillance concerns, and it makes the controversial Rekognition facial recognition technology. This is not to mention its extensive AWS services.

When you buy that little smart night light and the Flex to go with it, you’re buying further into an ecosystem of devices, services, and technologies that’s entirely controlled by Amazon.

This is not an argument that you should or should not buy into that ecosystem; it’s a reminder that when you buy a smart device, you’re not just buying a product with some extra features. That’s not how AI-powered products work.

Buy your smart device or give some as gifts, or don’t, and be happy with your choices. But like all emerging and transformative technologies, don’t forget to ask yourself what it will give you, and what it will cost. And then when it comes to larger decisions about building, buying, or creating AI technologies for your company or organization, ask the same questions.

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Big Data – VentureBeat

You’re The User Of AI. So Take Charge!

April 3, 2019 SAP

Part 8 in the “RPA and AI in Finance“ series, which examines the role that robotic process automation and artificial intelligence can play in finance operations.

Have you ever worked on a project where consultants were involved? Who worked with the solution: you or the consultants? It was probably you. So why is it that so often when we bring in consultants, we don’t have enough of our own people involved? This is not to say you shouldn’t bring in consultants – often they bring competencies you don’t have – but more to point out that you need to own the solution.

Anders 4 2 You’re The User Of AI. So Take Charge!

That also goes for projects involving artificial intelligence (AI). You’re the customer of the solution, and if it doesn’t work for you, you’re the one with the problems. Make sure you’re working with the right partners on such a project, otherwise, it spells trouble ahead! This challenge is what we’re addressing in Step 4 of our model for how to work successfully with AI.

How to choose the right partner? Most companies have processes for choosing vendors to work on projects. Typically, they issue an RFP (request for proposal), and vendors then submit their suggestions. But what do you do from there?

4. Reference-check your business partners – the right way

Challenge: There is an enormous difference between academic knowledge about AI and authentic experience. We would say we know how to plow a field with a plow – from a theoretical perspective. But put most of us on a tractor, and we would fail disgracefully. In the same way: It’s easy to study AI and get a degree – even a PhD. But applying AI on a real-life case, and real-life smelly and dirty data, is a whole other ballgame. So just because your business partner is a big name, it’s no guarantee that you will succeed in your quest.

Fix: Use the “Thomas Schultz” 10-step AI-test on a napkin as a sanity check on the claims of your business partner. And ask for real-life, operationally implemented cases and references that are providing the client with true business value. (Oh – and check up on those references as well.)

Most partners can show you the fancy slides, but they have few successes to show for it in real life. That’s not because they’re incompetent or it’s easy to work with AI. No, it’s because it’s hard and requires a lot from all parties involved in the project. Just because you bring on a partner on your AI project doesn’t relieve you of your responsibilities. No, you must take ownership of the project, run the meetings, understand the solution design, and implement the product. You. Not the partner. Are we clear now?

What does this mean for finance?

It means two things:

1. You must have project management capabilities.

2. You know something about AI and how it could potentially impact the solution (see the Thomas Schultz 10-step process for testing an AI solution).

If you’re clueless about what you’re trying to achieve, you will fail. You’d be surprised how often companies are rather clueless about the purpose of what they’re doing. That won’t happen to you, though, and certainly not in your next AI project. Now you know how to select a good business partner, and you’re ready to embark on your project! Have you figured out what that project should be yet? If you have, let us know by emailing us: Anders Liu-Lindberg and Thomas Schultz. If not, go back to Step 1 in the model, because we’re confident you’re not without business pains for AI to solve.

This article originally appeared on LinkedIn and is republished by permission.

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Digitalist Magazine

You’re Going Cloud Native—Don’t Forget Cloud-Native API Management

February 13, 2019 TIBCO Spotfire

Making progress on her code — Cropped shot of a young computer programmer looking through data

This is part two in a three-part series on the evolution to cloud-native application development. Read last week’s introduction to cloud-native app development, and check back in soon for a special cloud-native announcement.

Last week, we introduced you to cloud-native application development and deployment; today we’re going to talk about cloud-native API management and it’s vital role in your digital business strategy. The goal of cloud-native is faster development, faster deployment, more control, and a more agile business.

API management includes the creation, productization, security, and analytics of APIs. A cloud-native API management platform is designed to operate natively within your broader cloud-native stack of tooling and processes. It provides a lightweight, easy to deploy solution that manages all of your APIs seamlessly, regardless of where those services run.

Here are a few of the top benefits that will make you want to invest in a cloud-native API management platform:

Containers and Beyond

Is container management tool Kubernetes part of your cloud-native strategy? The ability to deploy apps or microservices within containers, and orchestrate those containerized services, is a noted benefit. You can deploy and isolate microservices and complete applications that are able to scale and run independently. However, not all apps are developed with such capabilities. With a cloud-native API management platform, you can deploy the platform in a cloud-native manner, while still managing API-led services that reside anywhere in your enterprise ecosystem, cloud or not.

API-Led Design

Without APIs, there is no integration, and API-led integration is the key to a seamless and efficient digital business. This is why cloud-native apps are always developed under the pretense that they will connect to and work together with a variety of other apps. Cloud-native begins and ends with utilizing and connecting to a variety of systems and microservices via APIs to encourage interoperability and reuse, key tenets of efficiency.

Cloud Agnostic

Taking advantage of the cloud doesn’t mean relinquishing control of your assets. With cloud-native API management, you maintain a fully containerized, portable, and scalable platform, deployed how you choose. Cloud-native means deploying all services on-premises or in a private cloud, including public cloud container services like Azure Kubernetes Service (AKS) or AWS Elastic Container Service (ECS). You can continue to take advantage of data center investments that you have, or those of a public or private cloud, while still benefiting from the elastic and agile nature of the cloud.

DevOps Alignment to Drive Agility

DevOps is a strategic IT framework implemented during your cloud-native evolution that drives more efficiency and agility for your digital business. Each microservice developed within a cloud-native app goes through an independent life cycle, managed via an agile DevOps process. For the app to function properly, multiple continuous integration/continuous delivery (CI/CD) routes work together to deploy and manage the application. Cloud-native API management is a seamless fit with DevOps app development and deployment models, because the platform operates within the same containerized environments as the apps.

The Bottom Line: Deploy Anywhere, Manage Everywhere

Evolving to cloud-native architecture is top of mind for all digital businesses trying to stay ahead of the curve. That’s not always easy, given the amount of legacy on-premises tools and services that are too expensive and time-consuming to replace in the immediate future. A cloud-native API management solution gives you the ability to create, manage, and analyze your APIs seamlessly with cloud-native tooling, and this will align with your company’s overall cloud-native evolution. Further, a single view of all on-premises, cloud, and edge APIs is key to enterprise efficiency and transformation. The flexibility to begin developing green field cloud-native services, while also maintaining operations on hybrid architectures, is what really makes cloud-native API management valuable.

Enterprises continue to trend towards cloud-native solutions, and implementing that into your API management platform is crucial for a complete digital transformation. To learn more about how TIBCO^® can help you learn more about cloud-native technologies, check out TIBCO.com, and stay tuned for our special announcement on Feb 19.

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The TIBCO Blog

How to Be Sure You’re Getting the Most Out of Your CRM Solution

January 31, 2019 CRM News and Info

If your CRM system is not doing all you hoped it would, there are two common reasons. Either the system was not set up properly with your processes in mind, or perhaps your sales team is not using it properly, or at all.

To the untrained, CRM systems can seem difficult to learn and there is often a perception that the time spent learning new processes will not yield additional value. However, if your CRM software is aligned with your preferred sales processes and your sales team can easily learn to transition, there will be better adoption of the system and ultimately sales will be increased. Your sales team will come to view it as a valuable tool for driving increased profits.

There are proven ways to align your CRM software and your sales processes. Here are our suggestions for 6 steps you can take:

Begin by defining your processes.

Before you even think of implementing new CRM software such as Microsoft Dynamics 365 CRM for Sales, it’s a good idea to actually define and articulate just what you want the CRM to do. Putting your processes into writing will give you and your CRM implementation partner the structure you need to ensure that the solution will meet your needs.

Differentiate between processes and technology

Don’t start with a CRM system and try to figure out how you can change your processes to fit the technology. Define your processes on their own first. Then look for the technology that will allow you to do things the way you want to. Of course, it’s a good idea to discard any outdated tasks and processes because they may no longer be necessary or useful.

Start with reports and figure out which processes will meet to your goals

It may seem like starting at the end and working backwards, but if you can identify which reports will be most helpful, you can examine your processes to see how they generate the data you’ll need for those reports. This step will help you see which processes are most productive and necessary. That’s where your attention should be focused when working with your implementation partner.

Involve the key stakeholders from the beginning

Usually the IT department is tasked with implementing new CRM software. But they are not the ones who will be using the solution day in and day out. Include stakeholders on your sales team to ensure that the technology will meet their needs and will work with the processes that they are used to using.

Set and manage expectations

Implementing a new CRM solution may present some difficulties for sales teams. Make sure to keep the processes realistic and straightforward. Define the specific benefits or success factors you want to gain from the CRM system and make these the focal point of your project. Outline workable timeframes and let everyone on the team know your expectations. Assure them of the assistance they need.

Avoid becoming overwhelmed; you can do this!

CRM projects can often seem overwhelming. Breaking the project into workable phases can help. Start with basic issues. A phased approach will help with user adoption and greater project success.

Get help from the experts

BroadPoint has successfully implemented CRM systems for hundreds of companies over our nearly two-decade history. Whether you’re just starting out with CRM, upgrading your system, considering moving your CRM to the Cloud, or just need answers to your CRM questions, we can help.

Contact our CRM experts at BroadPoint to request a free CRM assessment.

By BroadPoint – www.broadpoint.net

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So, You’re Getting a Data Warehouse for Power BI…

October 15, 2018 Self-Service BI

Data Warehouses: What Do I Know?

Well, I’m no expert. I learned Power Pivot and Power BI through Excel. What I know is from helping to build a SQL data warehouse. That is, I’ve worked with a data warehouse pro. So, BI pros or others, please add your observations in the comments!

Data Warehouse: the Promise.

In 2009 on Twitter, Rob Collie noted that the data model in Power BI and Power Pivot: “very much is meant to work in conjunction with, and be fed by, well-designed data warehouses.” (Power Pivot’s Impact on BI Pros). For me, a good data warehouse enables business pros to create reports without needing to think too much about the data model. Another benefit I see is the ability to deliver operational reports from transactional databases (ERP, CRM, financial systems). By design, these systems are for logging events, not for creating reports. And yes, even Salesforce is for logging tasks. Reports are secondary.

Data Warehouse: the Hype.

I’ve heard some idealistic claims from data consultants and Microsoft TSPs. For instance, data warehouses will soon replace Power Query and data modeling. Really? When I hear these claims, I tend to smile and nod. Why? Because, business needs and data sources evolve and the data warehouse lags behind these needs. Another benefit is having a single source of truth. For me, the real promise here is empowering business pros to get reliable data.

Data Warehouse: a Couple of Things.

Star Schema. Data warehouses use a star schema. In a star schema, data falls into lookup tables and transaction tables. Or, for the data warehouse pro, dimensions and facts. Typically, transaction tables hold time and event-based data. Whereas lookup tables hold the descriptive details for contacts and accounts (attributes). For more info about star schema, see Data Model: Beast to Beauty. One lookup table can contain data that’s in multiple hops in the source database. For example, transaction type code will be one field and its description will be another field– instead of in a separate table.
Historical Analysis. The purpose of a data warehouse is historical analysis, and this shapes design decisions. Since longer text fields won’t aggregate in a simple way, the first urge is to drop them.
Platform Agnostic. The data warehouse doesn’t care how users connect. Users can use Power BI, Excel, Tableau, etc.
Other Abstractions. Data warehouses have other abstractions that may confuse end users. For example, how they handle blank values in data (nulls) or how they handle transactions that don’t connect to lookup tables. And, the data warehouse may use internal IDs not found in the source. While I’m less concerned with these abstractions, they are good to be aware of. A data warehouse will involve a learning curve.

5 Practical Suggestions for aligning a data warehouse with Power BI.

(your mileage may vary)

To begin with, views are critical to Power BI. Views are versions of tables. Typically, these views are for specific purposes. While a good data warehouse person won’t adapt tables to Power BI, they will adapt the views. But you have to know what to ask for.

First, depending on how your data warehouse handles nulls, your dates may not be continuous. If your data warehouse replaces nulls with 12/31/9999, the date table will have gaps. The view for the Date lookup should filter out this invalid value. While you’re at it, be sure that all of your date fields have sort columns. A Month Year column formatted Apr 2020 will need a Year Month column like 202004 that will sort.
Second, naming conventions. Some platforms (Tableau, for example) can’t recognize spaces in table names and/or column names. Because of this, the data warehouse may use CamelCase for everything. While Gil Raviv has a query for fixing camel case column names, it’s best to fix this in a view. Similarly, prefacing every table name with the word Fact or Dim can make a data source alien to a business pro. Rename in the view. Always prefer clear human readable names for Power BI.
Third, long text fields in transaction tables. Long text fields can snag performance in Power BI. But you may need them for operational reports. One solution is to truncate these fields to 256 characters or less. Another approach is to add an index to the transaction table and split the text off into a special lookup table. However, with this second solution, see below.

About Relationships…

20151105 RelationshipsCreated So, You’re Getting a Data Warehouse for Power BI…

Behold, the lovely star schema

Fourth, prevent one-to-one relationships. (Only you can prevent monogamy). With a great data warehouse, Power BI will set up the relationships between transactions and lookups automatically. What can block this automatic setup are tables where both sides have unique IDs. I prefer to add two invalid rows with blank data to the table that needs to be on the many side.
Fifth, decide what to do about tables that may have multiple lookups to the same table. Your sales table may have a Sales Date and a Ship Date. Because Sales Date is the usual link between the tables, I prefer to rename Sales Date to Date Id (or whatever you Date key is called). This enables Power BI to create the main relationship without the business pro having to think about it. Other cases are when there is a credit account and a debit account. The user can always create a second inactive relationship to the other field.

Note on Relationship Auto-detection in Power BI.

Power BI can match up lookups to data tables. Automatically. Sadly, Excel Power Pivot can’t. Power BI recognizes lookups because they have a column with unique values. It links lookups to transactions on identical column names. Power BI will create one-to-many relationships. It does not attempt to create many-to-many relationships. Thank goodness! It will, however, create one-to-one relationships. Ruh oh. This is because it has no way to determine which side is NOT the lookup side. This problem is what the Fourth suggestion above remedies. What’s so tricky about one-to-one relationships is that it throws off auto-detection of all of the other relationships. And there are other results in the data model from these dreaded one to one relationships.

No one knows the Power BI ecosystem better than the folks who started the whole thing – us.

Let us guide your organization through the change required to become a data-oriented culture while squeezing every last drop* of value out of your Microsoft platform investment.

* – we reserve the right to substitute Olympic-sized swimming pools of value in place of “drops” at our discretion.

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Your Audience Called. They Say You’re Fired.

September 21, 2016 CRM News and Info

TMI

Even if there are still a few gaps in all that content, our audiences are already maxed out. They’re pummeled with information from every other corner of their lives. You might be selling widgets, and you worry about whether they’re reading your widget white paper or your competitor’s. But they have more to think about than just widgets; they have 20 other aspects of their business to juggle, and each comes with its own panoply of media to be consumed. And they have lives: their Twitter feeds are often a mix of business and personal. Webinar invites are happening when they could be having coffee with a dear friend. In-person events could mean that they’ll miss an internal focus group with the CEO. Or their kids’ soccer practice.

These peoples’ attention is precious. And it cannot be bought. So when we serve our business needs too heavily in our content – to the suppression of our audience’s needs – they start to disconnect.

This disconnect is happening a lot. Engagement rates are falling – and not just on social media. In part, perhaps, because the audience’s needs aren’t being met well enough by the content many firms are publishing. When that happens, they naturally disconnect.

Over time, they opt out.

That’s an audience member’s version of firing us. If enough of them opt-out (or “emotionally unsubscribe” as some email marketers put it), then you’ve got a deeper problem: Lots of content your audience doesn’t care for, and too often company-focused.

“Fool me once”

There’s another hidden risk to content that doesn’t serve your audience. It can actually train them to ignore you.

Here’s how it happens: You have a busy publishing schedule to keep up with. So you keep pushing out content, piece after piece, chasing that little “just-published” spike in traffic and shares. The content looks okay on the surface, but it’s kinda disappointing once consumed.

In an experience similar to “fool me once, shame on you; fool me twice, shame on me” your audience will peek at your content a few times, find it lacking, and move on – remembering that you disappointed them. Do this a lot, over time, and you’ll have literally trained them to distrust you. You’ll have taught them to ignore you.

An example of content that celebrates the company and ignores the audience

I got a webinar invite yesterday for a full 30-minute webinar that was an interview with the company’s CEO. A kind of “get to know you” sort of thing.

There was no new product or feature. There was no talk of customers. It was just the CEO talking about his views of the company.

Now don’t get me wrong – I bet this CEO is a fun, interesting guy. Most CEOs are. And I bet this webinar is interesting for employees of the company, and perhaps media and industry analysts. But that’s not a compelling enough reason for this company’s prospects to want to get on this webinar.

This company’s customer and prospect audience is made up of busy people with more pressing things to do. And unfortunately, launching a webinar about getting to know the CEO comes off as self-serving to a customer audience. Picking a topic like that sends a great big billboard of a message to your audience: This company still thinks it’s all about them.

The company may not have intended this. I bet they didn’t. I bet they wanted to do something entertaining and outside the typical white paper and blog post format. That’s a great instinct. But… I think they might have done better if their content team had kept brainstorming, even after the awesome CEO-webinar idea came up. Or maybe it was the right content for a very specific target audience, and that’s where the disconnect happened. The point is, it was a major disconnect, and you can’t afford too many of those.

Too many of us do too many of those disconnects, too often.

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4. Reference-check your business partners – the right way

How to Be Sure You’re Getting the Most Out of Your CRM Solution

Begin by defining your processes.

Differentiate between processes and technology

Start with reports and figure out which processes will meet to your goals

Involve the key stakeholders from the beginning

Set and manage expectations

Avoid becoming overwhelmed; you can do this!

Get help from the experts

So, You’re Getting a Data Warehouse for Power BI…

Data Warehouses: What Do I Know?

Data Warehouse: the Promise.

Data Warehouse: the Hype.

Data Warehouse: a Couple of Things.

5 Practical Suggestions for aligning a data warehouse with Power BI.

About Relationships…

Note on Relationship Auto-detection in Power BI.

Transform Your Business with Low Code, APIs, and Microservices (Even if You’re Not a Developer)

Your Audience Called. They Say You’re Fired.

TMI

“Fool me once”

An example of content that celebrates the company and ignores the audience

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