IBM Automation Insider

A bimonthly round-up of useful information to help you automate all types of work at scale

January/February 2020

5 articles

24 min

2020: The year of hyperautomation

By Tuck Satterfield

I recently had the opportunity to virtually sit down with Tom Ivory, global leader of IBM Automation and responsible for IBM Automation Services practice. New to IBM but well-versed in the automation market, Ivory previously worked as an analyst and services practitioner in the intelligent automation space. In this interview, he shares his perspective on where automation is going and what that could mean for IBM and clients.

Q: You’ve been in the automation space for nearly a decade. Has it changed much and what trends have you observed?

A: Eight years ago when I began working with HfS Research as COO, our research was focused on traditional outsourcing and how functions like procurement and HR could be streamlined. That changed in 2012 when Blue Prism reached out to us to author a white paper on robotic process automation (RPA), which nobody was really using in the broader services industry at the time.

As we looked closer at RPA, it was clear it could have a transformational impact on repetitive human labor – on anything that required manual data entry or moving information between disparate applications. It was equally clear RPA was just one tool in the automation toolbox, and that other components of automation – combined with AI and machine learning (ML) – could form a comprehensive automation solution with transformational value to businesses.

It’s been an interesting journey over the last eight years, coming from an analyst perspective at HfS, then moving to a practitioner role in the services arena, then coming to IBM just a few months ago. At IBM, automation has gone from a point solution to that broader, more comprehensive solution capable of transforming whole processes and business operations, not just tasks.

Q: What are customers looking to solve with automation now?

A: I think clients are evolving from executing process by process, or ad hoc automation by department, to asking, “How do I streamline all of this under a single automation initiative – one that’s centrally funded, that’s measured on its impact on internal operations and customer touchpoints?” Basically, one that tracks not only cost reduction but also revenue growth. 

That’s the big inflection point we’re at right now, moving from that narrow point solution to driving organization-wide digital transformation.

Q: What are you seeing as key drivers of automation success for clients?

If you look at an IBM automation engagement now, you’ll see us working with clients to identify their top challenges, applying business analysts and industry-specialized consultants to find gaps that can be solved through automation – or where they can integrate multiple business processes and applications through automation technologies.

And that integration requires a platform that’s extensible, that may have RPA, but also business process management (BPM) and more cognitive capabilities like ML and AI, plus the ability to orchestrate those technologies in an operational manner – without which the client won’t see the benefit of automation on a grand scale. 

Q: As clients strive to achieve holistic transformation, where are they getting stuck and where are they looking for help?

A: When clients get stuck it’s often because they’re looking narrowly at automation. They have what Forrester calls “islands of automation”¹ throughout their enterprise. For instance, they have automation initiatives sprouting up in finance, maybe in IT, and their partners are bringing in point solutions. This is where clients often look for help: to bring it all together, to cross-automate between customer service and IT, finance and HR, or across their supply chain. I think that’s why Gartner called 2020 the year of hyperautomation. Automation is becoming pervasive throughout the organization as clients build on, and work to connect, discrete automation successes.

Q:  How do you see IBM helping clients with a more holistic strategy?

A: Three things come to mind:

  1. Industry experience. When we work with a manufacturer or consumer packaged goods company, we bring industry-specific domain knowledge and expertise.
  2. Extensible and evolving automation platform. There are a lot of platforms out there, but ours is unique in that it uses the IBM Cloud™, works with all players in the ecosystem and major RPA vendors, and can integrate with any BPM platforms. We can offer clients a full business operations automation solution if needed – a combination of technology and expertise that can help COOs take that broader view of intelligent automation – or hyperautomation – across the enterprise.
  3. Best-of-breed software capabilities. We have a technology stack that can work with our services platform, that can plug and play nicely for BPM.

Automation is one of the strategic pillars for clients and C-level executives. It’s the foundation for creating intelligent workflows and setting up the organization to achieve wider digital transformation. If analog processes and operations are still living in the past – if they’re manual and repetitive, if they’re not integrated – it’s going to be difficult to move forward with emerging innovations like Industry 4.0, blockchain and 5G for the next chapter of digital reinvention.

Automation is propelling companies to re-engineer processes, optimize them, standardize them and even eliminate ones that are redundant or unnecessary, enabling the digital blueprint of the enterprise.

With a combination of services and software, a focus on innovation and a history of integrating business processes across enterprises, we can help clients execute on a holistic automation transformation that can move the needle for their business.

Q: As somebody new to IBM, what are your impressions so far?

First, I’m impressed with the talent of our people. At the end of the day, this is a people business. Our people are our products, especially within Global Business Services. IBM employees are passionate, creative and smart. I’ve worked with smart people throughout my entire career, and working at IBM feels like a step up, sincerely.

IBM also gives their employees a lot of freedom for entrepreneurism. And for someone like me, that’s essential to make a difference. For a company of almost 400,000 people, you feel like you can come in here and create something, no matter what your role or level. It’s great.

Finally, last year, in one of her many speaking engagements, Ginni Rometty showcased the Apollo 11 moon landing and IBM’s involvement in that mission. Her emotion was contagious as she talked about how NASA and the astronauts relied on IBM. There was a photo of the IBM jackets in the Kennedy Space Command Center. I knew I made the right decision to come work here. We’re not only looking out for our clients’ success, we’re also looking for moon shots – for the world.

Join Tom Ivory and IBM Automation executives at IBM Think 2020, 4 – 7 May in San Francisco.


1. Predictions 2020: Automation Strike Teams And Services Rise To Fend Off A Paradox, Forrester (link resides outside IBM)

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Sky-high gains in back-office efficiency using RPA

By Cheryl Wilson

When completed, the Dubai Creek Tower will be the world’s tallest free-standing structure — scraping the sky at nearly four-fifths of a mile in elevation. It’s emblematic of Emaar’s sky-high ambitions as one of the largest real estate portfolio holders in the world.

To keep pace with business aims and revenue management, Emaar expanded its back-office operations. However, business processes, such as invoicing, contract management and bank reconciliation, remained heavily manual and prone to higher error rates. Too many employees were spending too much time on repetitive tasks, leaving less time for customer service or planning for the future. And during peak volume periods, office workers struggled to complete work on time.

“There were a lot of inefficiencies accumulated over years of fast-paced growth,” says Binoo Joseph, chief information officer (CIO) of Emaar. “A lot of the processes were a bit siloed and a bit dated. Before we could automate processes to actually bring in benefits, we had to attack the area of process re-engineering. And that’s where IBM came in.”

How Emaar addressed the inefficiencies

Emaar selected its Malls division for the initial deployment of the robotic process automation (RPA) solution. Targeting the Malls division gave them a significant opportunity to streamline operations for the Dubai Mall — the world’s largest retail destination with over 1,300 stores and 200 restaurants.

Collaborating with Emaar’s IT department, IBM focused on five back-office processes where automation could add notable value — transactional processes, such as invoicing, receipt management and reconciliation. A key part of the project was the development of a business case and deployment plan to guide the RPA implementation over a six-month period. Getting employees to willingly accept automation of their tasks was as important as the technology especially when it came to training bots and dealing with issues caused by noncompliance with data management processes.

“IBM expedited solving these issues and provided insights on how others had addressed them successfully,” says Joseph. “They helped convince our people and showed them how it could be done better.”

How did it go?

By implementing the IBM Robotic Process Automation solution, Emaar achieved the following results:

  • 86 percent automation of the total daily volume of processes
  • 40 percent reduction in staffing costs
  • 50 percent reduction in process turnaround time

“At the core, Emaar and IBM did something that ensures a cleaner process flow across the teams,” says Joseph. “We are redefining and improving the functionality of the system while doing the automation layer on top. This allows the business users to reap the most benefit out of what tech has to offer.”

Read the full case study.

IBM Automation clients, executives and experts will gather to share the latest knowledge and practice in automation and AI from 4 – 7 May in San Francisco. Learn more about Think 2020 – IBM’s annual business and technology conference.

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Four tips to drive efficiency by automating your business using low-code apps

By Jeff Goodhue

Recently I was at a financial services organization working with a lead expert on the business team on some enterprise transformation models. During a break, we compared stories where good intentions led to a “yet another” exception process.

His example appeared simple at first: a new requirement to obtain his approval before any team member could enter a new request into the system to start the process. At the time, he wasn’t worried about the minor change.

However, after two weeks, he couldn’t keep track of all the emails and spreadsheet attachments that small change generated. I offered my sympathies and support to model this pre-process-process. “Nah, it’s only 15 minutes of my day,” he said. “But 15 minutes every day, roughly 260 business days a year. That’s 65 hours,” I said. Feels all too familiar, I thought.

man seated at computer monitor

Tasks, such as approving, reviewing, searching and routing, can consume our time in email and spreadsheets – time that could be spent innovating, helping customers or anything that delivers more value. What if you could stop this time theft by developing your own simple automation app without a big IT project – and easily connect it to enterprise systems in a secure and governed way?

While I wish I could say one solution can do it all, here’s some practical advice for solving these familiar problems using some low-code tools.

Tip 1: Avoid spreadsheets and email (please!)


We’re all members of cross-enterprise and small, team-based processes. The enterprise processes typically get funded and employ tools, web portals and repositories for document management. Conversely, the small, team-based processes don’t get as much focus and fall back to email and spreadsheets. This works well the first and second times but breaks down as these solutions expand or survive past their expected life, and they always do. (Don’t get me started on digging out of an ever-growing inbox and moving to a collaborative messaging platform with thousands of channels.)

One of my favorite comics said, “But a spreadsheet would be so easy.” This is true, in part, but loses transparency quickly and when (yes, when) the spreadsheet author leaves, it’s a nightmare to maintain.

Remove some email and spreadsheets from your daily life and simplify your work tasks by building an app using a low-code platform. Make sure the app can connect to approved services in your organization to avoid duplicating documents and logging in to multiple systems manually. You won’t need a robot to automate five screens when you can easily connect to five systems without writing a line of code.

Click here for an example of a low-code application platform from IBM (video, 04:45).

Tip 2: Don't let documents stop automation (put them to work)

When modeling an automation, analysts and modelers can get stuck when a task’s input or output is a document. Without the structure of a database or the accessibility of a REST API, documents can seem like adversaries when they should be put to work as the allies they are.

There are many options to automate the extraction of data – even imagery and media – from documents. Low-code, intelligent data extraction platforms can power the augmentation and automation of your business. In addition, with the growing popularity of AI, you can add increasingly accurate Natural Language Understanding (NLU) models to automate document classification with high confidence.

Click here to experience how IBM Cloud Pak™ for  Automation provides a low-code training interface for AI document classification and data extraction models. You can also check out the videos here, if you’d rather watch than try.

Tip 3: Intentionally partner business and IT in small teams

When was the last time you heard “bring business and IT together”? This advice seems to move in and out of fashion every three years or so. From requirements modeling to waterfall, from user stories to agile and scrum, they all provide a method for business and IT to collaborate. But as low-code capabilities rise and scale across enterprises, I’m concerned business will separate from IT again, as they did at the height of other technology curves, so it’s worth resurfacing this perennial advice.

people working on laptop computer

To avoid wasting time building an app that business won’t use or IT won’t approve, the methodology you choose must be paired with a low-code platform to achieve maximum effectiveness. One methodology, three-in-a-box, brings together product management, design and engineering/development in small, three-person teams. Another three-in-a-box variation is a business leader, designer and engineering/development expert.

Low-code capabilities can support the three-in-a-box method by allowing the business leader and designer to quickly model their designs and even begin using them to power a prototype, showing the engineering/development team member what needs to be automated. As new automation services, including APIs, workflows, decision services and more, are created they can easily be added to the low-code app.

As mentioned in the first tip, make sure your low-code platform supports simple connection to the services you need – along with integrated governance, such as strong versioning, that matches the IT team standards for flexible deployment.

Tip 4: A picture is still worth more than words

When you need to describe how to get from one place to another, how do you do it? Words, pictures, gestures, audio cues? A low-code tool many analysts and modelers already use is a process modeler, probably because it’s easier for many of us to learn by looking at something. A process modeler allows the author to deliver a single model of instructions and high-level requirements.

decision diagram

 A decision model diagram

Don’t forget about using less common low-code model types, such as decisions and data models. To reduce initial project design time and increase ease of documentation and transparency, use low-code models that directly execute with no code generation required.


Everyone in business performs manual exception process tasks in email and spreadsheets that consume time each day.

Low-code tools can help by enabling you to automatically extract meaning from your documents, quickly design your ideas in visual models and immediately execute them as prototypes. Using low-code can save time for other things, such as innovating and staying ahead of the next business curve.

If you’re not sure where to get started, consider a free one-day automation workshop, or check out IBM Think 2020, 4 – 7 May, where you can experience the new low-code capabilities of IBM Cloud Pak for Automation and much more.

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“How do you best operationalize AI?“

By Harley Davis

One of the biggest challenges many businesses face is how to effectively use the good work done by their data scientists, AI experts and business operations experts to improve business outcomes.

For example, data scientists typically work with whatever data they can find to understand client behavior, or how the business runs, to implement predictive analytics and machine learning (ML) models. However, these models are used sporadically, offline, to generate propensity or risk scores that are only updated when the models are retrained. They don’t respond to situations as they occur.

The potential for integrating AI models into operations has never been greater. Organizations across industries are moving quickly to bring their analytics work out of the shadows and into daily operations. To do this successfully requires good tools used in the right ways with a focus on data and understanding the nature of your models.

A new generation of tools for operationalizing AI

One of these good tools is a new generation of digital decisioning platforms that can insert the models right into the transactional decision making – whether it’s processing a claim, at the point of purchase, or during client interactions on a website.

Originally based on human-readable business rules, decision management systems have evolved to manage more complex business requirements by combining the specificity and clarity of business rules with the ability to apply AI-based ML models at the point of decision making. All of this is wrapped up in a decision modeling framework that lets businesspeople understand how decisions are made and how the elements come together to more efficiently run the core transactional and operational decision making of a business.

The potential benefits are significant, but how do you get there? There are three keys to help ensure success.

Key 1: Reimagine your process

Start from the decision you’re trying to make and the data you have available, and work to bridge the two. What does this mean in practice?

Create a decision model. With modern digital decisioning platforms, you can model how you make decisions. For instance, a large health insurance company may start with the following decision: “Should I approve this claim, reject it, or send it to a human adjuster?”

Break down the decision into its component parts. If the claim does not meet the rules of the policy, reject it. If the claim is very likely to be fraudulent, reject it. If the claim might be fraudulent but we aren’t sure, send it to a human. Otherwise, accept it.

Continue down this path for each of the component parts: What are rules for the policy of the claim? How do those rules apply to this claim?

Identify the data needed for the decision. To answer the questions above, you need data about the claim itself, thresholds and other information in the policy.

If the claim is likely fraudulent, the process will be a bit different. Here you need to apply an AI or predictive analytics model. This model takes various parameters around the claim and the client as input and produces a numerical confidence score indicating the degree of reliability of the model’s judgment.

Key 2: Assemble a decisions team

Once you’ve identified the process, bring together the key stakeholders:

Businesspeople who understand the decision. The businessperson can help model the sub-decisions to determine the business rules and thresholds for the AI model and how they’re plugged into the decision model.

IT people who build the decision model in a digital decisioning platform. They choose and insert the model into the transaction flow, identifying and sourcing the data elements needed for the decision. The IT person also develops a governance process and test plan to ensure that the decision service will work correctly.

Data scientists who construct the AI models used in the decision. They need to provide the context for how the model can be used and, perhaps, modify it to take into account the execution context and available data at decision time. They’re also responsible for other issues that impact the decision model, such as getting feedback from the decision for future iterations and managing issues such as KPI drift and bias detection.

Key 3: Map the data to the decision model

Finally, map all of the parts of the decision model to the available data. Some data may have to be mapped from one form to another – to match the format expected by the analytics model. And you may have to adjust the decisions or change the transaction stream to get the needed data.

This whole process is outlined in the diagram below:

decision process model

By moving to AI-based models that embody deep understanding of the business and leverage big data, you can make more accurate and customer-centric decisions. If you can store and use the result of these decisions, you can also provide valuable pre-curated data to help retrain and refine the models dynamically, making the process scalable.

Watch this demo video (04:59) to see how you can make business decisions with greater flexibility and accuracy by infusing business rules with machine learning.

At IBM Think 2020 in San Francisco, 4 – 7 May, attend sessions that can enable you to apply AI to help improve decisions at every level of your organization.

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A new single build experience for accelerating digital transformation

By Scott Mills

Do any of these scenarios ring a bell?

  • You’re part of a development team tasked with building business solutions that require different services, and you’re compelled to work in different tooling environments. Each environment has its own idiosyncrasies, including its own lifecycle and governance, and it’s up to your team to hand code the interaction between those services.
  • You’re an IT administrator and your team is behind delivering on business requirements to automate more.
  • You’re a line-of-business owner or subject matter expert who wants a more direct role in digitizing your business.

To address the challenges above, IBM Cloud Pak™ for Automation has introduced a single build experience called IBM Business Automation Studio (see the following figure) to help IT and business teams accelerate digital transformation. Business Automation Studio integrates IBM Cloud Pak for Automation under a single authoring build environment for developing and integrating business services, applications and digital workers. The low-code tooling allows traditional developers to deliver more and enables business owners and subject matter experts to directly contribute to digitizing solutions.

ibm business automation studio homepage screen shot

Business Automation Studio home page

Business Automation Studio was designed to deliver on the following key principals and supporting capabilities:

1. Give business owners and subject matter experts a direct role in digitizing their business

  • Unified landing page for all platform designers
  • Low-code and enterprise designers
  • Common consistency among designers
  • Easy navigation among designers
  • Author automation business services
  • Consume these business services in applications and digital workers

2. Ensure lifecycle and governance consistency so authors can create and manage their projects

  • Common authorization and project collaboration
  • Project branching and snapshots
  • Common decision-making and oversight process

3. Promote and discover reusable assets

  • Templates used to accelerate building your projects and toolkits to promote reuse
  • Configurators provided that discover deployed services

4. Facilitate communication among authors working on projects

  • Project discussion threads
  • Notification of project updates

Today, Business Automation Studio is the entry point to the following tools:

  • IBM Business Automation Application Designer is a low-code application builder where business users can build, modify and refine business automation-based applications, taking advantage of the capabilities of IBM Cloud Pak for Automation through iterative development and playback. The low-code building experience focuses on page creation with easy-to-use methods for populating the page with UI views and configuration.
  • IBM Business Content Analyzer is the cloud-based REST API web service, designed to work with IBM Cloud Pak for Automation. It helps you accelerate extraction and classification of data in your documents — no matter what you’re using today.
  • IBM Automation Digital Worker is used to automate or augment the activities of a job with digital workers. It helps human workers offload lower-impact work in favor of higher-impact work that requires their uniquely human expertise.

What should you expect next in the single build experience?  

  • Look for expanded and new capabilities in the key principal areas
  • New integrated designers

To see how easy it is to build an automation application using the low-code Application Designer, watch this demo video (04:45).

Experience Business Automation Studio, low-code designers like Application Designer, and other automation software tools at IBM Think 2020, 4 – 7 May, San Francisco.

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What automation opportunities are out there? How do you get results?
Every other month our experts share five pieces of strategic content to help you drive growth through automation.