Robotic Process Automation, RPA in 3 minutes, These Robots will not become self aware

Time Flies!
WOW, it’s already been a year since I started the and completed IBM training on BluePrism® Robotic Process Automation software as a special project for an account.  Later this month, I will be working with Python and Raspberry-pi for completely different robotic and IOT concepts  at Palm Beach State College.

Unlike in “The Terminator”, RPA Robots will never become “Self Aware”!!,  WHY? Because they are simply intended to do as the name states in reverse. Automate, Business Processes via Software Robots.

Refined once more, an RPA robot simply executes the repetitive keystrokes,  Mouse movements and clicks with logic that executes business a “well defined business process.

Many enterprises have employees executing business processes at a keyboard, opening an application or spreadsheet, evaluating that data and moving it to another application or pressing an approval button.  Spending 2, 4 or 8 hours a day using Copy/Paste, entering a few keystrokes and moving and clicking a mouse.

In the scenario above, the best case is 2 hours of a resource is being diverted to a lower productivity task and worst case is a full time employee is required.  Opportunity exists for potentially high and quick ROI.  What if, a software tool (Robot) could do the same thing ?  One time cost to write the robot (let’s pretend it doesn’t require update and maintenance).  It frees up an entire resource for other duties or frees up 2-4 hrs of an employee to do higher level more productive tasks.  Robots can be run at night, weekends several times a day, more quickly, with less human error and reduces costs of mistakes.

One just needs to do the math, what is the current labor cost of the resource-cost of developing and licensing the robot.  So that’s the Idea in a nutshell. I suggest reviewing the Everest Research Group RPA report  or the Gartner report as a ready reference for more detailed information about RPA and Vendors.

My teams focus was Enterprise Mobility Services.  So, how I did I get involved with RPA?  A multi-disciplined account team was proactively engaged with a client to address ongoing requirements. The account was looking more for early identification of issues and proactive action as opposed to saving labor. the client had seen some presentations and the question came up, could several their few to several hour time consuming tasks be automated? I was the only one on the greater immediate team with a Software Engineering background to provide assistance. 

Working with a few RPA tools was fun. It took me back to my programming roots.  I had to quickly learn a few RPA tool’s develop,  assess scenarios, create a few prototypes and make recommendations.  It came down to a comparison between WinAutomation®  and BluePrism to recommend appropriate solution for the accounts projects.  Actually a few of the tasks while easily done in RPA were quite simple and Windows OS related that they were done in Shell Script and the more complex tasks left for WinAutomation or BluePrisim.

The example above demonstrated that the appropriate choice can be radically different based on what the robot is expected to accomplish, the repetitive action applications they solve, infrastructure, the complexity,  skill required and cost.  The cases where scripting were used are examples. 

BluePrism provided a greater set of capabilities with deeper integration with applications and processes that benefit from optimization.  However, it required more effort, greater skill set and a greater cost per instance of a Robot.

WinAutomation was easier to work with, required less skill to develop but had limitations in standard capabilities and not as rich  integration with applications and processes that benefit from optimization.  However, much less expensive.

With either provider a robot was a robot, large/complex =$X; Small/Simple  same $X.  BluePrism robot cost was more expensive.  Additionally, unless changed, in the BluePrism cost model,  a Robot deployed to 10 locations = 10 robots and cost 10*$X.  With WinAutomation Develop once, Deploy many and pay for a single Robot.   For a more detailed look at the RPA landscape I suggest looking at the Everest Research Group RPA report  or the Gartner report from a sponsoring vendor

My experience and the Video
While creating ‘Robots’ using Robotic Process Automation tools is not typical software programming (my 1st love), it does use many commonly used algorithms, constructs and logic typical of traditional programming.  This can be seen in the 2nd part of the 3.5 minute video where robot is repeated in single step mode where the code in the tool takes the form of a flow chart including moving to a new chart, calling a subroutine……..

Depending on the skill of the learner, RPA’s “can” be learned very quickly.  I believe at one time BluePrism made the claim you don’t need trained programmers to implement robots.  However, unless you purchase development services, you do need BluePrism accredited developer which assumes 3 months training and 6 months to become a professional.   I would say a good programmer or process engineer would make an Excellent ‘Robot’ Designer.

 With RPA you can do amazing things and free up expensive resources doing, needed, labor intensive, brute force tasks to do other things.

Both of the RPA products BluePrism and WinAutomation are good and it was a fun challenge to create a few robots.  The brief 3.5 minute video below is a screen recording of a sample training scenario where a BluePrism Robot automates the tasks of a worker opening a daily spreadsheet of orders and enters them into an order processing system, even calling out errors.

Hopefully, this BTE brief was helpful,the short video brings RPA into a little better perspective and will be helpful to you.  Please leave comments below and  LinkedIn,  or contact me on  LinkedIn.

Enterprise Mobile Analytics, Should I care?

Often when we hear the word “Analytics” it is associated with “IBM Watson”, “Jeopardy” and the advances in cancer research and healthcare.

This article discusses Mobile analytics.  What are mobile analytics? The quick answer: done right, mobile infrastructure analytics provides an end-to-end (view of mobile user experience such that trouble areas can be easily identified and proactive steps taken to correct them.
Should you care? Yes

Note: Web Analytics is similar but traditionally assumes desktop browser access as opposed to a device which has a smaller screen.  Web analytics doesn’t address issues where a user may have had to rotate the device to see more clearly or or how often had to use fingers to enlarge an image.

Should you care about mobile analytics for the enterprise?

  • Is your enterprise planning to implement mobile applications in the near future?
  • Does your business rely on the use of mobile applications by customers?
  • Does your help desk get frequent calls about mobile apps not working?
  • Are you losing business or consumer transactions because users are having difficulty and abandoning the application or cart? Would you even know?
    If you said yes to any of the above, then yes, you should care about mobile analytics!

What does it mean to you?
Not having good analytics tools could mean losing business, money and reputation in the market. Your customers or employees may be avoiding adoption of applications because of bad experiences using your app—experiences that could be corrected and prevented using mobile infrastructure analytics.

Let’s start at the beginning. I’ve been around (some say forever) in computing for over 33 years and mobility for 17.  I’m still a bit old school, and I don’t use apps as much as folks of more recent generations.  Because I don’t use them frequently, it’s much more disturbing. Some applications seem to randomly return errors, crash and need to be opened again or even require a device reset.  When this happens, I usually delete the app and attempt to get money back where applicable. I have always held that if it’s happening to me, it can and is happening to others too.

That said,  Millennial’s have grown up with “apps”, expect them to work and may be less tolerant and less loyal to brands.

When a user deletes an app, What does this mean for the enterprise?

  • An online merchant loses customers and sales as carts are abandoned.
  • If it’s a standalone app, the app doesn’t make the sales it should or if free doesn’t get the pass-through advertising or other revenue it should.
  • If it’s an enterprise app, it is not adopted by employees and they work around it or lose productivity.

Where’s the app failure coming from?
As I wrote in a previous post, there are in the mobile infrastructure: enterprise, security, Internet, and user. All four zones must be working properly for the successful daily use of mobile devices in the enterprise. However, they are not all under the control of the enterprise, and a failure of any one of the elements in a zone can cause problems. The app on the device and the app server are only two pieces.

I can’t count the times that I’ve been handed an iPhone or iPad by a family member saying that Facebook, Pinterest, email or a shopping app isn’t working. In most cases, clearing the error message and trying again gets everything working fine. The app no longer fails, data comes back from the server, and therefore the error was in between.  Such as, the local ISP or a load balancer at the enterprise and not app or site itself but,  giving the app, app provider or IT team the black eye.  Not to mention, my having to try to explain.

We have all heard the help desk cries:

  • The app hangs or takes forever to respond!
  • The app went away and I had to reopen it!
  • I keep getting an error message!

Mobile application administrators and help desks hear these statements day in and day out. At any point of failure, even those outside the control of mobile IT, the app gets the blame because the user’s perception is that the application or server isn’t working. Until recently, enterprises had no end-to-end view of how an app was performing or if something was causing it to fail to perform in the users’ eyes.

Where mobile infrastructure analytics can help
Mobile infrastructure analytics provides an end-to-end view of the infrastructure supporting your mobile application. This includes tracking things like

  • The overall user experience
  • How long users stay on a page, what they search for and add to the cart
  • Whether they have to rotate the screen or expand or shrink the view
  • Whether they buy or abandon the cart, where they abandon from, and whether they return to it
  • Whether smartphones abandon more than tablets

All of this data and much more can be collected and and presented grapically to help companies understand the mobile user experience and provide insights for improvement.

Mobile infrastructure analytics correlates the errors seen by the user to events and errors in the infrastructure allowing administrators to proactively respond, correct and prevent additional issues. Mobile analytics predictive capabilities can generate alerts that a problem is coming, and administrators can stake actions to prevent users from ever being effected.

This is what mobile analytics means and why you should care.

How to learn more and get started
Want to know more about mobile analytics and how tools can provide actionable insights into your mobile application infrastructure, performance and your customer or employee user experiences? I suggest a look at the following links for more information:

Hopefully you now have a better understanding of mobile analytics and why it’s important for the enterprise. If you have more questions about the value of analytics, leave a comment.

Analytics, Mobile Infrastructure Analytics Demystified

Analytics, Mobile Analytics, oh my!  High-level math, double oh my!  Add infrastructure, and you’re probably thinking, “Get me out of here… or bring in the science guy!”

In fact, there is no reason to shy away from the topic of analytics, and I will tell you why. First, believe it or not, you already understand analytics. How is that? Let’s take a look at some analogies that provide an easy way to relate the concept, starting with sports.

Four analytics analogies

  1. As a kid, did you ever have to choose sides for a game of soccer, football or dodgeball?  Well, you or the captain used analytics to pick players. The data points were assumptions—right or wrong—based on individuals’ gender, size, strength, speed and past game experience. In essence, you were performing analytics with real or simulated data and associated attributes to pick players.
  2. Or think about the draft in fantasy football. Why do you pick players? Because of their stats. You know the rules and how points are assigned from play each week. Midseason trades too—these are all based on analytics.
  3. How did you choose your last car among the various alternatives? Gas mileage? Reputation of the manufacturer? Repair history? Cost comparison? It’s all analytics!
  4. Have you ever picked up a copy of Consumer Reports to help pick out a washing machine, entertainment center, kids cereal or something else? Yup, that too is analytics.

In each of the cases above, decisions are made based on analytics. In some cases, you’re more familiar with the data; in others, you just used looked at the Harvey Balls.  (Yes, they have a name.)

In simple terms, mobile analytics is very much the same. Like choosing sides for a game, picking fantasy players, or guessing which teams will make the final four, you, your staff or trusted vendors decide what attributes of your business infrastructure relate to mobility and should be tracked and measured.

Then tools, such as IBM Tealeaf or AppDynamics, do the heavy lifting (all the math and calculations) so that you take the insights from your graphically represented customized dashboard of qualitative data instead of Harvey Balls) and transform them into actions that will improve customer experience, reduce customers abandoning the site and increase sales.

What do mobile analytics look like in real life?

Turning to a more practical example for discussion: say your company has had a website presence and maybe even a web storefront for sales. You’ve enabled it for mobile devices or even created a mobile app. Maybe you’ve also developed a mobile application for employees to conduct daily business.

The questions you need to be asking yourself are:

  • How are the employees doing?
  • Are they more productive?
  • Is the help desk getting calls?
  • Are sales increasing?
  • Is brand awareness increasing?
  • Are customers returning to the storefront, completing purchases or abandoning carts?
  • Where do they spend their time when browsing?
  • Where do they experience trouble or give up?
  • Are sales appropriately distributed across the population of device types, or are more transactions completed by tablet than phone?

This is where mobile analytics tools and services do the heavy lifting and provide you with actionable intelligence. Mobile analytics can let you know what’s working well and what is not, with specific insights to why.  In particular, for the enterprise, AppDynamics, SAS, IBM Tealeaf and Cognos , are Analytics technologies can provide dashboard graphics that can be drilled into to determine measures and quantify the data to answer your questions.

Did a customer abandon a cart because the network was slow, there was an error or they were just looking? Maybe they bailed because they couldn’t really see what they wanted on the smartphone screen. With good analytics tools and service, you can see what your customers did, when they did it and sometimes even why.

In addition to helping with user experience, IBM Infrastructure Analytics Services can correlate user events with network and back-end server logs to determine if there was slow response time or even an error that caused the user to abandon the cart or application. From the measurements, the analytics software can proactively generate alerts for infrastructure issues so they can be corrected before the customer or employee experiences a problem.

You’re already familiar with analytics!

Tealeaf CX Screen capture

There is no mystery to it. Implementing analytics mobile or otherwise for your enterprise is simply a matter of knowing the important stages of application use, what’s important important to measure, and letting the tools or a service do the heavy lifting.

 

Without additional Hardware, Software and training,  an analytics service can provide you with a graphical view of that critical data and help you correlate user behaviors in your mobile application in real time. With predictive analytics help achieve better understanding of usage patterns, abandonment, availability, performance and capacity allowing you to make needed adjustments to meet business goals.  Or a service can “host” the heavy lifting while your staff implements the capture and reporting for actionable decision making.

Want to learn more? I suggest a look at:

Hopefully, this blog post has made mobile analytics easier to relate to and given you some insight to mobile analytics and how tools can provide actionable insights into your mobile application infrastructure, performance and your customer or employee user experiences? I suggest a look at the following links for more information:

Please leave comments below or contact me for further discussion on LinkedIn.

Short Mobile Analytics, “Day in the Life” Demo

Short, “Simple” Mobile Analytics Demo

Analytics continues to improve by leaps and bounds. Processing power, data storage capacity, types and amounts of data collected, methods of analysis and presentation to take meaningful action. I narrated and completed a video on my own time in 2015 (in part to learn Camtasia Studio and Tealeaf). It was placed and still hosted on YouTube by IBM. Some some images were provided by colleagues. Other images are actual IBM® Tealeaf®screen grabs of data. “Color of Summer” is from  a current IBM Watson/Tealeaf CX Analytics demo on You Tube analyzing why web shopping carts are abandoned.

This was a very simplified but practical example of using real time mobile analytics and hopefully, analytics a little easier to relate to and given you some insight to mobile analytics and how tools can provide actionable insights into your mobile application infrastructure, performance and your customer or employee user experiences.

Want to learn more?
I suggest a look at the following links for more information:

Please leave comments below or contact me for further discussion on LinkedIn.