At IntraSee we are super excited to announce that version DA-19.2.1 is currently being rolled out to all our customers. Also, many thanks to Oracle for all their support and collaboration as we utilize their excellent Oracle Digital Assistant (ODA) technology via our Hybrid-Cloud compatibleGDPR compliant, and world leading meta-data driven middleware solution. 

Our goal of automating every aspect of ODA design, build, test, and deployment wouldn’t be possible without having such an awesome partner to work with. So, with that said, here are the highlights for IntraSee DA-19.2.1:

  1. Microsoft Teams channel support for ODA (with full single sign-on).
  2. Complete GDPR compliance (not even email addresses are stored).
  3. Fully automated utterance supervised training.
  4. Fully automated utterance testing (with full explanations on any mismatches).
  5. Additional administrator dashboard ad-hoc reporting and analytics to improve oversight and reporting of chatbot usage. 
  6. Additional configurable semantic analysis when matching questions to answers.
  7. General improvements to the configurable Vocabulary Engine.
  8. Additions to the Skills Library (more delivered HCM & Campus skills).
  9. Extension to FAQ+ Wizard to include transactional and reporting intents, as well as data elements from over 10 SaaS systems and 2 on-premise systems (PeopleSoft & OBIEE).
  10. Embeddable complex web forms inside a conversation (useful for things like address change, or advanced MSS transactions of optional input fields).

Product Update Notes

Many of the product changes we focused on in this release were centered around making the overall chatbot solution simple to maintain by business analysts. Our key philosophy is that AI is massively complex and therefore requires a middleware layer to simplify it, such that functional experts can easily maintain and add to its skills. Therefore, if we focus on the middleware, our customers can focus on the business use-cases without having to create hundreds of thousands of lines of code, or having to become AI experts.

Additional automation and configuration were the keys to achieving these goals, plus improvements to the semantic analysis capabilities of the Vocabulary Engine. Our aim was to add even more means for a business user to train and direct the Digital Assistant, to ensure super-accurate matching of questions to answers – as well as adding to the scalability of the intent matching capabilities. Such that we are confident we can scale up to, and beyond, thousands of questions and still maintain accuracy of matching. 

The main UI additions for this release were to add the option of embedding complex web forms (with lots of business logic) into the middle of a conversation. Plus adding support for Microsoft Teams as a channel, with all-important single sign-on included. The following screenshot shows a conversation in MS Teams with Charlie the ODA chatbot, speaking both Spanish and English. Out of the box ODA will speak over 100 languages, so this is a terrific and simple way of enabling multi-lingual self-service for your organization. 

Sample conversation in Microsoft Teams using Oracle Digital Assistant

MS Teams Chatbot

Figure 1: Charlie the Chatbot in MS Teams speaking Spanish and English

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In January 2011, IBM unveiled on the TV show Jeopardy what they claimed to be the ultimate FAQ chatbot – Watson. Unfortunately, Watson proved to be “all hat and no cattle” and was never able to translate game show success into practical Enterprise AI success. Meanwhile the world has changed a lot, and AI has made many advances since those early days. 

As is often the case with any new technology, the things that appear to be amazing in the early stages of innovation quickly become basic features as the technology matures and real business world problems are tackled and solved.

Today, a chatbot answering basic questions is considered a bare minimum requirement when considering what a chatbot needs to be capable of to be able to perform the jobs of actual humans. 

We now use the term “Digital Assistant” or “Enterprise Assistant” to describe a chatbot that has many more skills than just being able to answer simple questions. Though often, the first time many organizations try out a chatbot solution, it’s by piloting what they believe is the easy option: an FAQ chatbot. 

However, not all FAQ chatbot skills are created equal. In the AI world of FAQ capabilities there is a huge variance between different vendor solutions. 

Think of it this way. Most people can sing, but most people aren’t great singers. In the same way, most chatbots have basic FAQ skills, but very few chatbots have great FAQ skills.

Freddie Mercury vs. someone
Figure 1: Both of them can sing, but one is a lot better than the other.

So, to cast much needed light upon this subject, we’ve created an FAQ about FAQ chatbots that should help explain the difference. 

Q: Can I add as many questions as I want to an FAQ chatbot, and it’ll be able to answer all of them accurately once I’ve conducted supervised training?

A: For most FAQ chatbots the answer is no! Many of them start to suffer the dreaded “intent mismatch” issue at around 100 questions. Only Chatbots properly architected can handle thousands of questions accurately. 

Q: What’s an “intent mismatch” issue?

A: This is when you ask a chatbot a question and it matches to the wrong question, and therefore gives you the wrong answer. This is the worst thing that can happen in the chatbot world, and will destroy confidence of it in your organization. 

Q: What causes intent mismatching?

A: Oftentimes it’s poor training that’s the culprit, and that can be easily fixed. But there are scalability issues that tend to kick in around 100 questions (though it can happen at a lot less than that), whereby the chatbot starts to get more and more confused as to what it thinks the human is asking it. 

Q: Why is there more likelihood of intent mismatch issues once I get close to 100 questions?

A: As the number of intents for a chatbot increases, the chance of some intents (questions) looking similar to other intents also increases. This is a scalability issue. If the FAQ chatbot is not architected properly it will suffer hugely from scalability issues, and will be unable to handle lots of questions that sound (in the mind of the chatbot) very similar. 

Q: What do “good” FAQ chatbots do that allows them to solve the intent mismatch issue?

A: The good ones have multiple ways of understanding what the human is asking. They don’t just rely on simple NLP (Natural Language Processing) training, and are able to also factor in things like subject recognition, entity existence, and knowledge of your organization’s vocabulary. The reason this is a far superior means of intent matching is because this is how actual humans think. We don’t just use one indicator to understand what someone is saying, we deduce understanding from multiple elements and inferences of a sentence. And that’s how a really smart FAQ chatbot does it too, and how it’s able to handle thousands of questions and match them perfectly. 

Q: What happens when the question is ambiguous because the human wasn’t completely clear on what they wanted?

A: This all depends on the chatbot. Some chatbots just cross their fingers, make a guess, and hope for the best. Some recognize ambiguity based on confidence level analysis (which isn’t always accurate either). While the very best have smart algorithms for dealing with ambiguity and will ask clarifying questions to make sure they understand the “intent” of the question. 

Q: Does this mean that a good FAQ Chatbot is more complicated to manage than a bad one? Given how much more it is capable of doing?

A: No, quite the opposite. Because it’s massively more capable it makes it much easier to manage. Think of it this way, training something that already has lots of skills is much easier than training something that has very basic skills.  

Q: Can FAQ chatbots handle the fact that though the question may be the same, the answer can vary due to location/job/department differences of the person asking the question? For example, the question may be, “what is the sick leave policy”. And depending on who is asking, the answer is often very different.

A: Like the mismatch question, the answer varies based on good chatbots vs bad chatbots. The bad ones only support basic 1-to-1 mappings. One question always equals one answer. In the Enterprise world this doesn’t work at all. So, the good chatbots are capable of understanding demographic information about the person asking the question and can tailor the answer based on that. 

Q: My chatbot vendor said I need to load all my “answers” into their chatbot in the Cloud. Is this a good idea? 

A: No, this is a terrible idea. Loading all your content into someone else’s environment is not only technically unnecessary, it’s also forcing you into dual maintenance of two sources of truth. A good chatbot needs to be able to plug into your many sources of content to provide the answer

Q: But what if the answer is too long to show in a conversation? My chatbot vendor is telling me that I need to manually create abbreviated versions of all my unstructured content. 

A: Best practice UX (user experience) is that the chatbot does provide summarized responses (with options to see the full answer) to make the conversation easy to understand by the human. However, good chatbots can use AI to auto-summarize the text, and this would be the recommended approach. 

Q: Can FAQ chatbots only answer a question with static (ex: text, HTML, or web links) information, or can they also include data too? 

A: Basic FAQ chatbots are limited to only being able to respond with static data, but the good ones can also include data from other systems. And the great ones can also bring back that data from both on-premise and multiple Cloud systems. 

Q: It sounds like there’s a massive difference between FAQ chatbots and it’s important to look “under the hood” before I make a decision?

A: Yes, if you can take the time to test-drive a $20,000 car, then you should definitely test-drive any chatbot before making a decision. 

If you’d like to see a great chatbot in action, please contact us for a live demonstration. 

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Our last blog featured analysis of how Workday is falling behind the times in 2019, and how it will hold its clients back in the era of disruption we are now entering.

It may come as a surprise to know, that for those PeopleSoft clients still running an on-premise solution that goes all the way back to 1987, that options in this new era are far more plentiful than Workday’s. So, how is that possible? 

The reasons for this are that PeopleSoft comes with built-in features that Workday still doesn’t have (hint: a portal). While Oracle also provides comprehensive PaaS (Platform-as-a-Service) offerings that clients are actually allowed to use (unlike Workday). Also, again unlike Workday, Oracle doesn’t just allow their clients to enhance the UX any way they want, they encourage it!

So, here’s a list of the three fast and easy things you can do today to move your UX to the Cloud, and greatly improve it at the same time. 

Note: All of the options below are managed services in the Cloud that you could configure as you please. But wouldn’t have the burden, or cost, of maintaining and upgrading.

1. Chatbot, aka Digital Assistant, in the Cloud (interacting with PeopleSoft and all your other systems)

Figure 1: Video of a chatbot in action

Summary: Chatbot as a Service, reducing operating costs and improving user satisfaction.

Description: Try out a fully configurable out-of-the-box chatbot solution that is GDPR compliant and comes delivered supporting all the complex use-cases your Enterprise system requires. As well as supporting your on-premise PeopleSoft solutions, it also comes delivered with out-of-the-box integration with over 10 major SaaS vendors, plus adapters for other on-premise solutions like OBIEE.

Plus it is future-proofed to also fully integrate with all Oracle Cloud chatbot skills being developed by Oracle development teams, and can act as a “concierge chatbot” for any chatbot skills created on the Oracle ODA stack (Oracle Digital Assistant). 

Implementation Overview: Fast 12-16 week pilot, with an option to roll out to the entire organization at the end of the pilot. 

2. Portal in the Cloud: using Oracle Content & Experience Cloud (CEC)

Figure 2: Video of Oracle CEC plugged into your Enterprise

Summary: Portal as a Service, improving user satisfaction and efficiencies, while also adopting Oracle’s next-generation portal.

Description: Implement a one-stop-shop, GDPR compliant, portal that combines not just your on-premise PeopleSoft, but also comes delivered with out-of-the-box integration with over 10 major SaaS vendors, as well as adapters for other on-premise solutions like OBIEE.  

Also, as this would be using Oracle CEC, you would now have access to a state-of-the-art content management system too. 

Plus it is future-proofed to also fully integrate with all Oracle Cloud applications, such that it could be your portal of choice for the next twenty+ years. And with this being a cloud solution there would be no environment maintenance and upgrades required by your team. Just a plug and play option for your business users to extend as they wish.

Note: For organizations already using the PeopleSoft Interaction Hub as an on-premise portal, this would not only replace the need for that environment (allowing you to decommission it), but would also greatly improve the UX as part of the implementation.

Implementation Overview: Fast 12-16 week implementation. 

3. Portal as a hosted solution in the Cloud: PeopleSoft Interaction Hub

iHub Screenshots
Figure 3: Some samples of the PeopleSoft Interaction Hub configuration options

Summary: Portal as a hosted Service, improving user satisfaction and efficiencies, while also moving to a hosted portal solution in the Oracle Cloud (IaaS), and utilizing a fully managed PeopleSoft Interaction Hub.

Description: Implement a one-stop-shop, GDPR compliant, portal that combines not just your on-premise PeopleSoft, but also comes delivered with out-of-the-box integration with over 10 major SaaS vendors, as well as adapters for other on-premise solutions like OBIEE.  

Plus it is future-proofed, such that any “pagelets” that exist in the PeopleSoft Interaction Hub can easily be converted to be drag-and-drop components in the Oracle Content & Experience Cloud, if you subsequently move to that platform in the future.  

Note: For organizations already using the PeopleSoft Interaction Hub as an on-premise portal, this would not only replace the need for that environment (allowing you to decommission it), but would also greatly improve the UX as part of the implementation.

Implementation Overview: Fast 12-16 week implementation. 

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It’s almost three years since we wrote the original Workday blog, and since then the world has changed a huge amount. But, surprisingly, Workday has not. Back in 2016 they were a cool back office HCM Cloud SaaS provider, and today, well, they’re still the same. Only what was shiny and glittery back then, now looks a tad jaded and long in the tooth in 2019.

So, while doing a decent job of becoming PeopleSoft 2.0 was definitely an accomplishment of sorts, the world has changed enough over the past few years that you have to wonder what the attraction is now.

So, with that said, here’s 10 reasons why Workday may not be a great option in 2019.

1. It lacks UX innovation tools or solutions (while its competitors are racing by it).

It’s almost two years now since Workday announced details on what their “intent” to open up their PaaS platform would actually mean. So, what’s the status now?

After the passage of two years, we were hoping to see much more progress in this area. Unfortunately, as of today, Workday appears to have made almost no progress. On their web site, they advertise limited availability to be one of the first to be able to use their PaaS platform.

Limited Availability: This exclusive program gives you the opportunity to be one of the first organizations using the Workday Cloud Platform. Create business-impacting applications leveraging Workday’s technology. Help influence our roadmap.


2. It’s turned its back on the new UI revolution: chatbots.

Also, and maybe a lot more concerning, Workday’s participation in the AI revolution and the new era of disruption appears to be stalled in the chatbot realm. If you go to and search for chatbot, you get zero results. Whereas if you go to and perform the same search, you get over 1,100 results. That’s a massive differentiation.

Meanwhile, the advice of Gartner is that conversational UI (aka chatbots/digital assistants) is a critical feature of our lives that we all need to be focused on for the next decade.

“Conversational AI-first” will supersede ‘cloud-first, mobile-first’ as the most important high-level imperative for the next 10 years”.

– Gartner Sept 2016

Certainly, we are just a few years away from wondering how Enterprise systems were ever usable without some kind of digital assistant. In the same way we would now wonder how we ever managed to use the web without Google search.

And here’s 10 reasons why the Enterprise needs a chatbot solution, if you need to be more persuaded.

3. It’s a closed community

Innovation requires activity by multiple parties to spark new ideas, and new ways of doing things. Workday believes that only they can innovate on their platform, and that any attempt to do so by their clients or other vendors needs oversight, control, and permission. They have a euphemism for this: “curation”. In the Workday world, curation is the means of stifling innovation. Or, to quote their CEO, Aneel Bhusri:

“Right now what we’re seeing is what I’d call small pieces of additional functionality rather than applications that have a larger purpose. So the potential impact is limited. You can bring whatever code you want but, we curate and certify everything that goes into that platform and will continue to do so. We have to because we have a responsibility to ensure that customers remain compliant”.

“We are approaching verticalization and extensions differently to others. We are curating everything and will discuss our plans with partners so that there is a clear line between the areas we will enter and those where our partners will have a free run

– Aneel Bhusri

The bolded comments are the ones we feel are most pertinent. In the new age of digital disruption: agility and innovation are the key requirements of any organization. Without these things, you cannot adapt. Having an Enterprise system that requires curation and certification will be an impediment to clients and partners ability to provide the UX that their organizations want. And in this new world of digital disruption and transformation, this will be a major inhibitor to progress. Certainly, with the rise of chatbots as the new UI, organizations need the ability to adapt to these changes, and should not risk being forced to go through a curation and certification process. Or, even worse, be told, “no, you can’t do that”.

4. It’s not fully mature

How long has PeopleSoft been around? Forever, right? Well, technically since 1987. But in the software world, that’s pretty much forever. And guess what? There are still new features and functionality being added to it each year. Oracle has done a great job keeping on top of things and expanding functionality to meet demand. So that’s over 30 years of development. Building a mature Enterprise system takes decades. It’s a colossal undertaking. For Workday to catch up to all that development will take many years, if ever, before they can match PeopleSoft feature for feature.

And now, to make matters worse for Workday, Oracle has not only passed them by with their HCM Cloud SaaS offering. But they are also the undisputed leader with their Cloud ERP (aka Financials).

Meanwhile Workday still has a very long way to go in the Campus world, and the Financials world, to really be able to describe themselves as a mature Enterprise software vendor.

5. It’s like selecting a client-server solution, when everyone else is selecting web-based systems.

As any NFL quarterback will tell you, you don’t throw the ball to where the receiver is, you throw it to where the receiver will be.

Likewise, you don’t select an Enterprise software vendor for what they are doing today, you select one based on where they will be in one year and beyond.

And right now, there’s a revolution taking place in the field of UX. Web-based systems focused on back office use will become dinosaurs, while systems built with conversational UI’s (chatbots/digital assistants) that everyone in the organization can use, will be the new standard for all Enterprise systems.

Selecting a vendor in 2019 that has no chatbot solution, would be akin to selecting a client-server solution in 1997. Or buying a VHS player, while everyone is buying DVD’s.

Selecting Workday is a tough buy in 2019. There’s a sense that they are being passed by, and are drifting into a state of irrelevance. Mostly due to an inability, or reluctance, to change with the times.

6. There’s more to an Enterprise system than just having a pretty face

There’s no doubt that Workday has attractive features. And at first glance it does catch the eye (though even that has waned over the past two years).

But from a UX perspective it’s way below par. Having a pleasant UI and poor UX (there’s a difference) is something that can be glossed over in the sales cycle, but not when real people start to use it.

7. It’s not focused on the complete user experience

As Owen Wilson wistfully said in Wedding Crashers, “I think we only use 10% of our hearts”. Workday falls into this trap. Out of the box it doesn’t satisfy the complete user experience. Just a small fraction. How it’s implemented, and the tools provided, are the key to unlocking the real potential of an Enterprise system. In fact, the whole concept of an “Enterprise system” is typically something less tangible than people would like to admit. For most organizations it’s really an eco-system of multiple systems that the user is somehow expected to navigate and comprehend as one system (like the universe).

Unfortunately, the human brain is not wired to process complex and poorly connected applications (unless you’re Stephen Hawking). Which leads to massive under-utilization of the true potential that Enterprise systems could provide (which thus creates an under-realization of ROI). Owen Wilson was right. 10% is a pretty accurate number.

8. It lacks a “portal”

In 2016 we noted that Workday has no Portal. In 2019, they still have no portal. And there’s a fascinating historical reason for this.

Basically, the team that left PeopleSoft to form Workday never had a clue how to fully utilize the PeopleSoft portal (now called the PeopleSoft Interaction Hub) while they were at PeopleSoft (pre-2005). It was a source of frustration for many people. So, when they formed Workday, they just assumed that if they couldn’t find a reason to use it then, then there was no reason to build one now. Obviously, this was one bad decision, layered on a bunch more bad decisions.

All Enterprise systems need some kind of one-stop shop that integrates everything nicely for the user. That’s not even debatable in 2019 (and wasn’t really in the year 2000, or 2005 either). Though the irony is that the truest realization of a one-stop shop is a digital assistant (aka chatbot). It’s the ultimate navigation-less UI. And, unfortunately, as mentioned earlier, Workday doesn’t have that either.

So today, Workday has no portal. Meanwhile PeopleSoft has the Interaction Hub, and Oracle has the Content & Experience Cloud (a terrific portal that actually works with PeopleSoft, as well as other Cloud applications).

9. It won’t integrate with your corporate systems

All organizations have their own eco-system of internal systems that gradually morphed and developed over the years. We can’t just pretend they don’t exist. And if people are using these systems (which they must be) then that makes them part of the usability experience, and they need to be brought into the fold like everything else. Let’s call this Exhibit B in the case for why everyone needs a good portal. And until Workday has one, then they are missing the boat.

10. It’s 2019, and a “brain” for the Enterprise isn’t a nice-to-have, it’s a requirement.

It’s undoubtedly a brave new world that we are about to enter. If 1997 and the advent of web-based systems was a seismic shock to the Enterprise world. Then the new era we are about to enter will be 10 times what occurred back then. Enterprise vendors that don’t deliver a “brain” will leave their customers in a technological wilderness. Some people will try and “roll their own”, which will be shown to be a big mistake. Creating a brain for the Enterprise may sound easy, but it isn’t. Some people will try and use tools like Microsoft LUIS, which is not a good fit, or IBM Watson, which is equally flawed. Others will use vertical solutions, like Salesforce with Einstein, that can only do small chunks of what they need to do.

The correct way to enter this new era is to adopt something already built, that can be configured for your Enterprise needs. Oracle and IntraSee have partnered to provide such a solution and can demonstrate exactly what it looks like.

Please contact us for a live demonstration of what the future looks like, and how you can implement it today.

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A few years ago we took lessons learned from Jurassic Park and applied them to the world of usability testing. Since then the world has changed, but the sage advice found in the movie has not.

We now live in the era of artificial intelligence (AI), and many organizations are grappling with the world of build vs. buy.

The question being asked is, “do we build an Enterprise chatbot (aka Digital Assistant) from scratch using something like Microsoft LUIS, or do we buy something already built”?

As we all discovered in the movie, good intentions can quickly turn into a series of unexpected outcomes. And the main lesson learned (if indeed it needed to be learned) is that as smart as we think we are, there’s no substitute for having a coherent and informed plan. And being able to learn from failed lessons of the past.

So, using Jurassic Park as an example of a build that totally went wrong, we thought we’d look at the lessons learned from the terrific movie and apply them to the world of chatbot implementations. You’ll be surprised at how applicable it is. 

1. Dr. Ian Malcolm: Oh, yeah. Oooh, ahhh, that’s how it always starts. Then later there’s running and um, screaming.

All projects begin with general excitement and great anticipation. And none moreso than chatbot projects. Kickoff and initial design meetings tend to be stress-free and filled with the hope that something great will happen. The prospect of replicating a human brain that can understand your Enterprise sounds like lots of fun. What could possibly go wrong? And, of course, the pizza ordering example that comes with the LUIS tutorial makes it all look like a walk in the park. But then, six months later, it all becomes apparent that ordering pizza isn’t a great use-case. And that the more you build, the more complicated it all becomes. And that’s when the screaming starts. 

And this is at the core of Microsoft’s problem. They are not an Enterprise software applications provider, in the way that someone like Oracle is. What they are good at is building tools that let you build applications. They just don’t build those applications for you. Again, unlike Oracle. 

With Microsoft LUIS, everything is a build, and in the Enterprise software world, the smart people are buying.  

2.  Dr. Ian Malcolm: Your scientists were so preoccupied with whether they could, they didn’t stop to think if they should.

Yes, it is possible to build an Enterprise chatbot using a tool like Microsoft LUIS. But only in the same way it’s possible that an army of monkeys, given enough time, could recreate the works of Shakespeare. The real question isn’t could you roll your sleeves up and try your luck with LUIS, it’s should you? And the answer is a resounding no.

Gartner has already spoken on this subject and advised that IT needs to stop trying to reinvent the wheel and instead purchase things in the Cloud that someone else has already built.

3. Dr. Ian Malcolm: Gee, the lack of humility before nature that’s being displayed here, uh… staggers me. 

Microsoft’s belief is that they just need to hand LUIS to their clients, and they’ll build massively complex neural systems that understand their Enterprise systems. This shows a complete lack of understanding, or appreciation for, the task at hand. 

And this naivete is fundamentally grounded in the fact that they, like IBM with Watson, don’t sell the software that organizations wish their chatbot to integrate with. 

Unlike, for example, Oracle, who not only sell chatbot technology (Oracle Digital Assistant), but are also using that technology to build their own Enterprise skills. Unless you drink your own champagne, it’s impossible to know if it’s any good or not.

4. Nick Van Owen: You seem like you have a shred of common sense, what the hell are you doing here?

At some point in every project, someone needs to apply common sense and say, “enough is enough”. If after a few months you’re not seeing something worth sharing with your organization, then that maybe is the time to try something “off the shelf”. Typically, that point is 3-5 months. By that time, you’ve probably figured out that brain surgery isn’t what your IT group is cut out for, and that you need to look for something already built. So, keep that in mind. 

If somebody keeps telling you that you’ll see the value in year two, then that’s a sign you should move on.

5. Dr. Ian Malcolm: Taking dinosaurs off this island is the worst idea in the long, sad history of bad ideas. And I’m gonna be there when you learn that.

As Gartner once said, “building a bad chatbot is easy, building a good one is hard”. If you spent over a year building a bad one, and then roll that out to your organization, then that’s going to be a tough lesson to learn – for the team that built it, and the organization that has to live with it. 

Trying to build an Enterprise chatbot from scratch using Microsoft LUIS, or IBM Watson, will go down in IT history as a bad idea on many levels. 

Let us count the ways:

  • Massive waste of resources and time
  • Poor first impression for the organization
  • Opportunity cost of lost time that could have been better used implementing a “proven” solution

6. John Hammond: Don’t worry, I’m not making the same mistakes again.
Dr. Ian Malcolm: No, you’re making all new ones.

The history of IT is littered with projects that went over budget and under-delivered. And that’s just looking at web-based implementations over the past 20 years. Given such a poor track record with a very simple to implement technology like HTML, imagine how badly awry projects using a conversational UI could go. Yes, you likely won’t be making the same mistakes. But there’s plenty of new ones to make if you’ve never done this before. 

And using Microsoft LUIS, or IBM Watson, will allow you to make those mistakes. Ultimately, they are just coding tools, and don’t have the smarts already built into them to ensure you don’t go down the wrong path. 

What you want is pre-delivered skills, not a swiss army knife. Skills that already understand your Enterprise needs and rules. Skills that are plug-configure-play. 

7. Dr. Ian Malcolm: God help us, we’re in the hands of engineers.

The last thing you need to be in, while implementing a chatbot solution, is the hands of engineers. Microsoft LUIS forces you into the path of focusing on how to engineer code, and away from the path of “how should this work for the user”. 

In this new world of AI, the focus now isn’t on people learning how to interact with machines, it’s all about machines learning how to interact with people. And to make that happen you need all your engineering issues resolved on day one. Not day 1000. 

8. Dr. Ellie Sattler: [after finding Malcolm with a broken leg] Should we chance moving him?
Dr. Ian Malcolm: [the Tyrannosaur roars nearby] Please, chance it.

An illusory comfort zone is not the place to be in. Whether it’s comfort with your IT group, or comfort with a vendor you’ve happily worked with for years. When you hear the T.Rex roar, it’s time to move to a better place. A safer place. Don’t wed yourself to a toolset or a preferred vendor, take a chance and reach out to the world. Speak to people you’ve never spoken to before. 

Ask for demos from many vendors in the market. Ask difficult questions. Enter into an interview process to find someone who has already done what you want to do. It may seem like taking a chance, but it’s better than certain failure. 

9. Dr. Alan Grant: The world has just changed so radically, and we’re all running to catch up. I don’t want to jump to any conclusions, but look… Dinosaurs and man, two species separated by 65 million years of evolution have just been suddenly thrown back into the mix together. How can we possibly have the slightest idea what to expect? 

The world has just suddenly changed radically. Many people are running to catch up, while others, like Workday, are just ignoring the change and hoping it won’t affect them. But machines interacting with humans, as if they were human, is not a change that is going away. 

At the same time there is a complexity to all this. And ordering pizza doesn’t really describe that complexity. 

Meanwhile both Oracle and IntraSee have been building these skills over the past two years, on the same technology platform (ODA), and have learned valuable lessons during that period. Having already done this, we now know what to expect when adding conversational skills to complex Enterprise systems (both Cloud and on-premise). 

10. Dr. Ian Malcolm: I’ll be right back. I give you my word.
Kelly Malcolm: [pounds her fists on the railing] But you *never* keep your word!

The worst thing about implementing a failed chatbot solution is that you will train people to never trust you. No matter how many times you tell them that the next version will solve all their issues, they’ll never believe it. And they’d be right not to. It’s very rare in life that we stumble across the perfect way to do anything. And the odds of that happening with an Enterprise chatbot (aka Digital Assistant) created from scratch using a tool like Microsoft LUIS or IBM Watson, are slim to none.  

No matter how many assurances from the vendor, if it’s not already been built, you have no reason to believe it will be built properly.

So, ask to see a demonstration of a fully formed chatbot with advanced Enterprise skills. Ask as many people as you can. But definitely also ask us. We’ll be happy to oblige. 

To learn more, just contact us below.

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