Automation: the application of machines to tasks once performed by human beings
It’s hard to comprehend, but it was just over a hundred years ago when car manufacturers relied on horse-drawn carriages to deliver each frame to the workers. Then, in 1913, Henry Ford introduced the industry’s first moving assembly line at the Highland Park Plant in Detroit.
Now, complex robots with “laser eyes” perform everything from welding, to die casting and painting, alongside their human colleagues on the factory floor.
Meanwhile, automation in the so-called “hi-tech” world of software has been much slower coming. Servers need bouncing, patches must be applied, security alerts need investigating, performance needs to be tuned, and code needs to be developed. All by hand.
And this is just maintenance of the actual machines! If we then flip the script and look at the experience of the humans using the software, we see the same glaring inefficiencies.
Figure 1: The help desk of the future
Entire “call center” industries have been created, all predicated on the idea that Enterprise software is too difficult to use – and only manual intervention can fix that.
The advent of the Cloud was the first step in starting to solve this problem, but in itself was not the solution. What it was, was the enabler of the solution. Step one was about creating one infrastructure and one code-line supporting thousands of organizations.
Step one was great, but step two is where the Cloud starts to realize its true potential. Step two is all about automation.
And this is where the real benefits to organizations are realized, all powered by the driver of what will be the next industrial revolution: Artificial Intelligence (AI). Today we can confidently say that the future is autonomous. And that the future is now “open for business”.
Figure 2: The future, as described in The Jetsons, isn’t so far away!
But what is fascinating about this new era is that it will differ in one key way that will make it massively different to every revolution beforehand: barrier to entry.
In the past only the super-rich could take advantage of each industrial revolution. Want to build cars? Well, good luck finding the money to create a factory of robots and assembly lines. However, if you want to fully automate your entire IT infrastructure, and enable robots to automatically handle “help desk” calls? All you need is a subscription. Everything you need has already been built and it’s in the Cloud.
The new industrial revolution will be priced on a pay-on-demand basis, and will be available and attainable for all organizations, big or small. There will be almost no barrier to entry. The playing field will be leveled by the most egalitarian revolution in the history of mankind.
API’s and AI will combine to enable automation in the same way a faucet, when turned on, provides water.
Figure 3: Once upon a time this was a revolutionary means of transporting water!
So, why is the autonomous revolution now market-ready? Two things:
Autonomy across the entire platform is key for many reasons:
Note: the security aspect cannot be stated more strongly. Many Cloud systems are hardened at the perimeter only, like an egg with a hard shell. Unfortunately, once the perimeter is broken into, there is little to prevent further intrusion.
With Oracle autonomously baking security into every level, there are multiple levels of security that are all monitored, patched, and repaired in real-time. This means the entire system is always in compliance without the need for human intervention.
85% of all security breaches occur when a patch is available but not applied.
Figure 4: Automation, the new “Easy” button
What also stands out with Oracle’s and IntraSee’s offerings is the low barrier to entry. At IntraSee we pride ourselves on making AI a turnkey solution. Which is why both Oracle and IntraSee provide pilot options, where you can quickly see the value of automation for your organization.
With our chatbot solution we can implement and configure in just four weeks. Let your department kick the tires for another four weeks. Then roll it out to a larger pilot audience for another four weeks.
If you like it? Then roll it out to your entire organization in another four weeks.
Using IntraSee’s Chatbot 4×4 implementation methodology, the benefits will be instant. Chatbots dealing with complex calls for less than one dollar a conversation. Compared to $5 to $200 for an actual human. Plus, with the added bonus of higher customer/employee/student satisfaction and a lot more reasons too.
The future will belong to those organizations that embrace autonomy. And those that don’t will struggle with never-ending spiraling operational costs that will hinder their ability to compete.
Imagine if Ford were still trying to transport car frames via horse-drawn carriages. That’s right, they wouldn’t exist today. The lesson in life, as always, is adapt or perish.
Figure 5: Old vs. New
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Since the dawn of time (almost), people have been communicating via conversations. And this worked great for many thousands of years. Then computers happened, and suddenly we all had to learn a different mechanism for communicating. This was loosely referred to as computer-speak. And over the years it changed as technologies changed. From mainframe, to MS-DOS, Windows/Mac, client-server, and then the web. But the one constant over the years was that it was still computer-speak. Meaning that it had nothing to do with how humans actually spoke to each other.
And this is the crux as to why your Enterprise systems are so difficult for your organization to use today. And why it costs you so much money to support everyone, and everything.
Implementing a chatbot solution for your Enterprise, if done right, will save your organization millions of dollars per year, increase organizational efficiency, and improve user satisfaction with your systems.
The ROI is dramatic. A conversation with a chatbot should cost less than 50 cents per conversation. Whereas a conversation with a human is costing your organization at least 10+ times as much, and, if HR professionals are involved, often 100+ times as much.
But to get there everyone needs to be comfortable with what this new era will look like, and how to get it started. To that end, the recommendation of Gartner (and we wholeheartedly agree) is to pilot the solution to ensure that you don’t embark on a failed IT journey.
So, here’s our recommended 10 steps to ensure that you hit this one out of the park on the first pitch.
First off, pilots should be cheap, and they should be short (and if they are not, then that’s a red flag). But it’s also super-important to understand what the cost structure looks like once you’ve rolled this out across your entire organization. So, work with the vendor that’s pitching the pilot to fully explain what things will cost after the pilot is done and you’ve decided to roll this out to everyone in your organization.
The last thing you want to tell your CEO is that the pilot was a success, but it’s not cost-effective to roll out the solution organization-wide. Remember, the #1 reason for implementing a chatbot solution is to reduce operational costs.
All implementations will require some time from your internal teams. That’s normal and desirable. But you really should avoid solutions that could tie up teams of your people for months on end.
Also, once implemented, you should expect support and maintenance to be minimal too. If you suddenly discover you are now performing “dual maintenance” of content, then this means you chose the wrong solution.
A chatbot solution should require minimal involvement from your team to setup, monitor, and support.
It feels like every day we hear about a security breach at some of the biggest internet companies in the world. Concerns about security and infrastructure are very real and must be addressed. It’s critical to understand the architecture that the chatbot provider is proposing, as you may discover that your data is not only flowing through channels you’d prefer it not to, but is also actually being stored in places it shouldn’t be.
At IntraSee we take infrastructure and security very seriously. Which is why we reside solely within the fully certified Oracle Cloud.
We would recommend around 200 people for an average chatbot pilot. And while it may be tempting to select them all from the IT department, we would recommend a broad range of your organization, but would focus on employees/managers or students/faculty (in the higher education world).
Try to select a broad demographic that most accurately represents your organization. Including those who speak any languages you would want the chatbot to support.
Chatbots are capable of conversing in many languages, some better than others. So be aware of which languages the people in your organization will be conversing in, and check with your vendor to get feedback on how competent they believe the chatbot is in those languages.
Adjustments can be made for any languages that the chatbot may not be completely proficient in. Just let your vendor know up front.
Ok, so the pilot went great. Everyone loved it and now you want everyone in your organization to get to use it. Be sure that you have a pilot-to-production plan in place before you started your pilot. Because now you’ll know what to do next, and how much it should cost.
The key to pilot-to-production is that it should be a relatively quick process. We would say that four weeks should be attainable, but that anything more than twelve weeks would be excessive.
Talk to your help desk team, and your HR Generalists, they can provide you with the top 100 things that they get asked on a frequent basis. That’s a great start. But also get insight into how the conversations go.
This will help with configuring how the chatbot interacts with your people.
The idea is that the chatbot understands your best practices and follows them every single time. Just like a perfect employee would.
It’s critical that your chatbot understands context, because then it can make helpful suggestions during a conversation. Just like a well-trained support person would. Plus, it’s also important that the chatbot understands who you are and where you are. This way a meaningful conversation can take place, as opposed to a simple Q&A.
So, for example, if someone asks a question about taking time off work, the chatbot should already know that if the person resides in Germany, that it should respond with whatever is the German policy (because that may be different to the American policy). And, also, that it offers to help the person complete a leave of absence request, if they so wish.
There is a school of thought that says that chatbot pilots should only include a small number of “intents” (aka functionality). We at IntraSee do not subscribe to that point of view. A pilot using this methodology may appear to be a success – but that could all be an illusion.
The main (but not only) purpose of a pilot should be to see what would happen in a full rollout to your entire user population, but with a smaller group of people where you can monitor and see what works and what doesn’t. And the only way to do that properly is to try and make your pilot scope close to what you expect your full production scope to be.
This means you also need to be agile during the pilot and can adjust to things you see, such that by the end of the pilot you have a close match to what your pilot-to-production path would be. HINT: This is why you need a configurable and fully automated solution.
There’s no doubt that chatbots are the most exciting thing to happen in the software industry in the past 20 years. And there’s a ton of examples on the internet about how easy it is to create a chatbot that can accept pizza orders. But Enterprise chatbots are highly complex and sophisticated creatures. And to build one properly from scratch would take many years. So, the strong recommendation would be to use something already built off-the-shelf that can quickly be configured for all your needs. This isn’t just our recommendation, this is the recommendation of Gartner too, from last year’s Gartner Application Summit.
Gartner’s clear advice for IT is to stop building things that are already built. Ultimately, it’s not just a waste of time and money, it also contributes to IT being primarily focused on being in “maintenance mode”, instead of “innovation mode”.
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With the proliferation of Amazon’s basic one-size-fits-all AI, millions of users have experienced Alexa playing music, summarizing the news, and providing information found on the internet. After the initial thrill is gone, many come to find out Alexa can’t really do much more without adding Alexa Skills to make her smarter. These “skills” are the bridge between your commands and actually getting something accomplished, like adjusting your thermostat or turning on a smart light bulb.
In the Enterprise world, IntraSee’s chatbot-automation bridges the gap between artificial intelligence and real-world business transactions, empowering AI platforms like Oracle Intelligent Bots to turn on the proverbial smart light bulb for your enterprise or institution.
When people ask us what we do at IntraSee, we explain that we are like Amazon Skills for the enterprise. These skills are what large organizations need to realize millions of dollars in savings. Instead of wasting time and money designing and maintaining websites that beat around the bush, IntraSee’s chatbot solution gets straight to the point and does the work users need to get done. There’s basically no web page, just a chat window. We’ve developed a means of automating chatbot implementations that makes configuring these solutions quick and simple, so the AI knows how to do the stuff that needs doing – right out of the box!
AI and Enterprise software finally collide
IntraSee’s suite of products empowers users to accomplish tasks like moving an employee to a different team, tracking a new hire’s to do list, aiding a nurse restocking medical supplies, or helping a student register for classes by phone. All the user has to do is ask straightforward questions, and the chatbot will do the rest. Without navigating through a website, a busy nurse can simply ask the chatbot to “Buy more bandages,” and the chatbot will guide them through the required steps: “What type of bandage? What size? How many? Would you like to add something else to your order?” College students can give the command, “Search for English classes,” and after choosing a class from a list the chatbot will ask, “Would you like to add English 101 to your cart?” Simplicity makes cents.
At IntraSee we have taken leadership in the Enterprise UX space, and transformed that into an automated means of generating a chatbot that is multi-talented from day one. It is so advanced that it can immediately solve problems that your development teams have spent decades, and masses of money, working on. And while automatically turning on a light bulb is a nice trick (and saves someone having to push a button). Our chatbot can perform things immediately that often take teams of people days to achieve. This is exponentially better than anything Alexa can do.
So, while programmers are churning out thousands of simple AI skills, none of these applications can handle complex business logic or the decision process required for multi-step transactions like tracking time in Kronos. Alexa can’t make intelligent decisions because she doesn’t know anything about the user. This is where IntraSee puts the “I” in business intelligence. We leverage all of the information we know about users without asking, utilizing known data such as reporting structure to logically streamline workflows. When the chatbot has all the information it needs it provides a summary of the transaction and executes the process securely and efficiently on the backend.
Many Alexa users worry about security and privacy because Alexa is “always listening,” and you would never want co-workers to hear you say something sensitive like, “Give Jimmy a big bonus.” Chatbots eliminate such security concerns by allowing users to type questions and commands. The entire suite of IntraSee products is designed to seamlessly work with highly secure data systems such as PeopleSoft, Oracle HCM Cloud, Oracle Student Cloud, Salesforce, Taleo, Kronos and many more. Each month we continue to add to the library of skills, so if it’s not there now, it will be soon.
In business it never makes sense to spend a dollar chasing a nickel. At IntraSee, our focus has always been to streamline business processes to save your organization money, increase productivity and reduce frustration. IntraSee has been helping organizations increase profitability by simplifying the user experience since our inception. To say that IntraSee is ahead in the AI skills game is an understatement. For nearly a decade IntraSee has been developing a suite of products that provide cost-saving self-service solutions straight out of the box. It turns out that our mature transactional architecture is the perfect fit for the next generation of AI, marrying complex transactional processes with the AI platforms of the future.
Artificial intelligence investment is intelligent business today, not something your organization should wait to do tomorrow. Building a library of AI assets is something that needs to start today. We encourage you to look at IntraSee chatbot solutions as you would Alexa Skills, the necessary smarts needed to get meaningful work done. Being a business that is ahead of the curve in AI integration will make the difference between winning and losing.
Launching artificial intelligence for your organization’s users is simple and straightforward. The AI’s have matured, IntraSee’s got the skills covered, and our risk free pilot takes the guesswork out of adoption timing. Contact us to start your Chatbot Pilot today.
It’s been said that nostalgia isn’t what it used to be, and in the world of technology there’s a lot to be nostalgic about! Times change so fast. Just over twenty years ago client-server was all the rage, and then the internet arrived and suddenly browser-based systems became the new way to do everything. Then in the mid-2000’s Apple coined the phrase, “there’s an app for that”, which then begat a mad rush to build phone-based apps for everything under the sun.
Starting in 2018, all of those things have been usurped by a new UI that will change the technology landscape yet again: chatbots. And, for generation Z or millennials, this is the way they expect to be able to interact with everything. Text and voice are their UI of choice.
Research has shown that students much prefer a conversational UI over all other channels of communication. They don’t use email, they don’t want to call the help desk, and more so than ever, they don’t want to use your mobile app. Of all the activities on a mobile phone, nothing has had the growth of messaging, which recently saw almost 400% in yearly growth.
The message (no pun intended!) is clear: students just want to chat.
Already, surveys show that only 8% of millennials have not heard of chatbots. They have quickly become pervasive in their messaging apps, and social networks like Facebook. If students aren’t already demanding chatbots to help with their academic careers, they will be very soon. The key is to get ahead of the curve and not put yourself in catch-up mode like many institutions found themselves during the mobile app boom.
So, a chatbot seems like an obvious fit for students, but which chatbot is right for your university? Chatbots and voice assistants are everywhere, but let’s focus on the chatbot types that can help a student with their academic life. You will find the two most popular types are:
So, what is the difference between the two? Our best analogy would be to step back in time to the mid 90’s and recall the advent of MapQuest. Anyone who was in the consulting business back then remembers the trials and tribulations of making a car journey in a strange city, armed only with a printed copy of your MapQuest directions. Holding a piece of paper in one hand, while driving with the other was no fun at all – especially at night. And all you had to do was miss one turn and you were lost.
MapQuest circa 1998: You’d get lost too!
Then the 2000’s came along and now we had Google maps on our phones and what a huge difference that made. Now we had a device that would guide us every step of the way to where we needed to go, and could adjust on the fly no matter which turn we took. It even had a voice to ensure we kept our eyes on the road. Technology improved the quality, and safety, of our lives.
In this scenario, the FAQ chatbot is the printed copy of MapQuest directions. And the Enterprise Assistant chatbot is Google maps on your phone.
One is very clearly a lot better than the other. So, let us describe in detail why this is.
The FAQ chatbot has a single focus: provide a chatbot that can answer the most popular questions your help desk receives. This chatbot is meant to reduce help desk calls. To set it up, you basically load in a series of questions and answers. For example:
How can I order a transcript?
Official transcripts can be ordered on our registrars site which you can visit at
Essentially the FAQ chatbot is just a search engine that understands natural language. This is not a huge leap in innovation for most universities who have had a search page that is already serving this purpose. Some FAQ chatbots can crawl your public website (just as a search engine does – see a trend here?) and if your question matches one of the bot’s search results, it would answer as Siri does:
I found some web pages which you may find helpful…
If your web pages were redundant or confusing, well, listing out search results isn’t really that helpful, even if it is in a chat bubble (as shown above).
While these FAQ chatbots do use artificial intelligence, it is a rather shallow use. As ultimately the student still needs to go to the actual web page to get the answers they are looking for, and then figure out what to do next.
FAQ chatbots are the digital equivalent of pointing someone in a general direction and wishing them good luck.
While Enterprise Assistant chatbots can do everything an FAQ chatbot can do, they can also do a whole lot more. Such as:
The key differentiator being that it can guide the student through to the final outcome of what it is they need to do. Just like Google maps does. It doesn’t stop helping until you get to your final destination, and ensures no wrong turns.
Let’s go back to our FAQ chatbot example and imagine how it would work with an Enterprise Assistant chatbot:
How can I order a transcript?
I can help you with that. I found the following Guides:
Or here are some things I can help you with now:
Order an official transcript
Great. I can order an official transcript for you.
What date would you like your transcript processed on:
Process Immediately
How many transcripts would you like?
1
What is the name of the person you would like the transcript sent to?
John Doe
Which country do they reside?
United States
What is their street address?
123 Main St
What city?
New York
What state?
NY
What zip?
10111
Thanks. Your transcript has been submitted for processing. After processing, it usually takes up to 5 business days to arrive.
Thanks!
That’s a totally different experience! Let’s take a deeper look at some of the key feature differences between the two options.
FAQ Chatbot: Usually the FAQ chatbot uses a proprietary content system for loading in questions and answers. This means that if you were ever to switch bots, your content may be locked inside a proprietary system. It also means that all your content would have to be manually loaded into the new chatbot. And it now means you have to maintain your content in two places: web site and chatbot.
Enterprise Assistant Chatbot: Enterprise Assistant chatbots can tap into an existing content repository via APIs. You likely already have a knowledge base inside Salesforce, ServiceNow, Drupal, Oracle Content and Experience Cloud, PeopleSoft Interaction Hub, or another platform. An Enterprise Assistant chatbot can read that content dynamically. So it is always up to date, and there is one source of truth. Which means you will never have conflicting information between your web site and the chatbot.
FAQBot: The FAQ chatbot cannot perform transactions. It is a content/search only chatbot.
Enterprise Assistant Chatbot: This is where the Enterprise Assistant chatbot shines. It can help the student actually get something done rather than pointing them to a web page. This doesn’t just save time, it also ensures accuracy in everything that is done, while continuing to work in a way that your students prefer. Text and voice.
FAQBot: The FAQ chatbot cannot dynamically run reports or query data in other systems.
Enterprise Assistant Chatbot: Enterprise Assistant chatbots can run reports from your PeopleSoft, Oracle Cloud and other cloud applications. They can even email you a full report! Reports for rosters, grades, advising and more.
| Feature | FAQ Chatbot | Enterprise Assistant Chatbot |
|---|---|---|
| Integrate with your existing content/knowledge base | ||
| Search web sites & FAQs | ||
| Integrate with your on-premise and Cloud systems | ||
| Perform transactions | ||
| Approve workflow | ||
| Run reports/queries |
Chatbots are a priority for many higher education institutions. As you begin your journey into chatbots, we hope this blog helps you understand your options better. Even with that clarity, it is always best to know what you are getting into. You have one chance to make a good first impression with students. If you roll out a chatbot poorly, you may never recover from that poor first impression. Contact us below to learn more about rolling out your enterprise chatbot in just 12 weeks.
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