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The way we do work today isn’t working for many employees and employers. Employers have fewer qualified people to perform complex tasks, while employees get bogged down with low-value tasks. What slowly emerges is a productivity crisis. How can companies solve it?
Automation is one of the go-to solutions, but automation fixes are still segmented, focusing on improving isolated parts of a process versus the whole process as part of an outcome-focused automation strategy. This is where deep deployment of automation technologies comes in.
What is digital process automation for deep deployments?
Deep deployments target the seamless orchestration of whole processes, traditionally associated with business process automation (BPM), at a cross-enterprise level, while solving long-tail challenges with simple business applications in order to improve productivity and end-to-end customer or employee experiences.
To see how deep deployments of automation could impact productivity, take a typical loan officer. Currently, she spends most of her time on low-value tasks like inputting data from documents and generating reports. If her workload is augmented by automation, she can focus on higher-value work like building relationships with clients or finding new business opportunities.

To achieve the type of business outcome that helps our loan officer, deep deployments require a broader set of automation technologies beyond traditional workflow or BPM. To go deeper, it’s helpful to understand such concepts as decision automation, content management, intelligent capture, robotic process automation (RPA) and the effects of AI and machine learning. For this reason, pragmatic enterprises often seek out automation platforms that provide a full spectrum of capabilities in order to address the many opportunities and challenges driving productivity, now and in the future.
What’s new in deep deployments?

AI and machine learning. These technologies are emerging as a natural next step for improving productivity by optimizing workstream automation. As operational data becomes more accessible to organizations, AI and machine learning algorithms can find automation patterns for offloading low-value tasks to technology, freeing employees to focus on high-value work, and patterns for assisting them in higher-value, expert work. For example, AI-enabled digital agents can extract and classify unstructured data in documents and make certain insights or recommendations available to employees.
Low code builder tools. For automation to be successful at scale, users should also be able to solve productivity problems with minimal IT involvement. Low code builder tools put the ability to create automated business applications in the hands of the business users, allowing IT to focus on creating reusable automation patterns that support it. As an example, the loan officer from the above example may have a business app that is created to automatically approve loans below certain criteria. If there is a sudden change in risk appetite, she can quickly and easily adjust criteria without the need for IT involvement.

How are deep deployment solutions evaluated?
Forrester Research recently evaluated 10 vendors on their digital process automation for deep (DPA Deep) deployments options to help application development and delivery professionals select the right provider for their needs. In their report, The Forrester Wave: Software for Digital Process Automation for Deep Deployments, Q2 2019, IBM was named a leader.
According to the Forrester report, “IBM has consolidated its content management, decision management, and process automation offerings under a single executive and engineering team with a unified go-to-market execution. At the same time, it has done some of the most pragmatic integration of IBM’s Watson AI capabilities to drive very process-specific business value. The result is a highly integrated solution well-tuned for handling deep processes.” Additionally, “IBM has a strategy to extend its process and case management platform to enable more of the generalized low-code development that more extensive DPA often requires.”
IBM Business Automation Workflow, which was evaluated by Forrester in the report, is part of the IBM Automation Platform for Digital Business. Our platform enables clients to automate workflows and decisions while deriving insight from the content within those business processes with speed and at scale. IBM clients have created and are running more than 50,000 applications on this platform as they seek to improve productivity and customer experiences.
Register to get the full Forrester report comparing software for digital process automation for deep deployments.
The post Solving the productivity crisis: Digital process automation for deep deployments appeared first on Cloud computing news.
Quelle: Thoughts on Cloud

1. Juli 2019

da Agency

How construction worker feedback is helping shape app development for Mueller, Inc.

I always joke that my knowledge about an MVP (minimum viable product) came from HBO’s hit show, Silicon Valley, where a motley crew of developers race to create prototypes for clients. But, it’s true.
When Mueller partnered with the IBM Garage to create the Material Estimator app, I knew that we’d work together to build a working prototype that would streamline the pricing process for our sales team and our customers. During the Design Thinking workshops, I expected to sit in a room together and brainstorm about the tool’s functionality and design. What I didn’t expect was for the IBM Garage team to put on hard hats and come out to Mueller building sites to talk directly to our contractors and construction workers.
Direct real-world feedback shapes app development
Getting this type of real-world feedback and insight from the field, from the actual people who will be using our app, was a complete game-changer. In some cases, construction workers confirmed assumptions that we’d made about how we thought the app should work. In other cases, they pointed out issues we never could have known because we don’t have that field experience.
For example, we had the innovative idea to include smart voice search in the first iteration of the Material Estimator app. This was genius … until construction workers pointed out that they often have jackhammers or other loud machinery roaring in the background of job sites. So, voice search would never work. Text search, even though it wasn’t as revolutionary, made much more sense.
A new approach to business
Seeking out this type of empathy, not just for the user’s problem, but for the users themselves, was so different from how Mueller had worked before. We looked at the customer relationship in a new way, and our product is so much better for it. Instead of guessing what the user would want, we knew what the user needed – because they told us. Talking directly to our customers was so simple, yet so profound. The IBM Garage has taught us a completely new approach to business.
Watch the below video to see the many ways the IBM Garage changed the game for Mueller and learn more about this project by reading the case study.

The post How construction worker feedback is helping shape app development for Mueller, Inc. appeared first on Cloud computing news.
Quelle: Thoughts on Cloud

29. Juni 2019

da Agency

Toward a pure devops world: why infrastructure must be treated as software

The post Toward a pure devops world: why infrastructure must be treated as software appeared first on Mirantis | Pure Play Open Cloud.
The thing about technology is that even before one wave completely finishes, the next is already on us. Virtual machines were still growing when containers appeared. Containers still aren’t completely in place, and serverless technologies are growing. To say that tech is perpetually in flux is to understate things. Even when it comes to devops.
Or maybe especially when it comes to devops.
Because the goal of devops is to automate everything that can be automated, and that definition changes all the time. We started with applications, and while the bleed to infrastructure was inevitable, the move to cloud native architecture makes this automation essential. In a way, the infrastructure is very much a part of the application.
We’re already seeing that with CI/CD-based infrastructure deployment and AIOps, but it’s more than that. If technology is going to make it to the next plateau, infrastructure must be treated with the same level of care and automation as software deployment. And that means that it must adapt to the same pressures and trends.
CI/CD deployment
These days, no sane developer would produce code for a large-scale production environment without some sort of CI/CD process, even if it’s just version control. But infrastructure management is handled in that ad-hoc way all the time. Granted, this is less common in the world of Virtual Machines — and even less common in truly cloud native environments — but it still happens, and even bare metal deployments can be scripted and incorporated into the normal operations workflow.
Getting to this level of automation is getting easier with the advent of tools such as Airship.
Building blocks
Once the general processes are in place, and it becomes possible to use automated processes to spin up resources, it becomes crucial to know what those resources are and how they’re used. One way to do that is to create building blocks that can be used and combined by users and developers.
Creating these building blocks, such as standard images, makes it possible to standardize deployments and know that you aren’t creating security problems — or worse. Projects such as Harbor make it possible to store these images in a private repository to simplify usage, but the idea of “building blocks” can also extend up the stack to the pipelines that put them together.
Training wheels
The pipelines that create production systems in an enterprise environment are complex, and there’s no way to expect that everyone will be up to speed on how to use them.
To that end, it’s important to provide templated pipelines to get users started, but it’s also important to have a process in place that ensures they’re used appropriately, and that a well meaning engineer doesn’t take down your entire production infrastructure.
An even better solution is to provide a way in which users can perform their duties without having to worry about it at all.
Low-code/No-code
Considering that devops arose as a way to streamline the relationship between developers and IT operations and lighten the load on operations, it’s perhaps no surprise that low-code/no-code environments, which enable end users to create the functionality they need without involving developers are on the rise.
But what about infrastructure? Where does this trend come in?
Well, truth is, we’ve been on this road for infrastructure since users started creating VMs using Amazon Web Service’s web UI, and if we’re ever going to stem the tide of shadow IT, those same capabilities are going to have to be available on-prem.
OpenStack is one example of an attempt to make this possible for end users — in this case, developers who need resources to do their job — but you can also see it in other “as-a-Service” projects. Mirantis recently announced its Model Designer, which provides a way for users to simply enter their requirements and get back a pre-configured pipeline to deploy an entire environment. Mirantis also just announced a beta Kubernetes-as-a-Service application targeted at developers, with both an API and a user interface to provide multiple ways for end users to get the resources needed to do their job — automatically or on demand.
AIOps-ready
While the idea that AI-enabled routines can track your application workloads and infrastructure and detect and resolve problems before they happen, the reality is that most companies are still coping to groups with the “ops” part, and simply aren’t ready for AIOps yet.
That doesn’t mean you ignore it, of course; by getting your infrastructure firmly in hand — and into your operations pipelines — you’re putting yourself into a much better position when you ARE ready to tackle a more self-healing environment.
The overall vision
Nobody thinks that we’re going to eliminate all of IT operations; even when we do get to the point where our infrastructures are more “self-healing” we will still need people to train and groom the routines that keep them that way. But in the meantime, it’s our job to create environments in which all of the resources — including the infrastructure — are managed as code, and in a way that not only take advantage of today’s capabilities but leaves us ready for tomorrow.
The post Toward a pure devops world: why infrastructure must be treated as software appeared first on Mirantis | Pure Play Open Cloud.
Quelle: Mirantis

25. Juni 2019

da Agency

How to start scaling automation projects with design thinking

Digital business automation is helping companies across industries improve operational efficiency, drive innovation and better serve customers. Automating work helps businesses offer a better experience at speed and scale. To begin, businesses must evaluate their big picture. What are the complex processes with multiple steps that when done manually are slow, costly and frustrating for your business and customers?
Resolving operational pain points with digital business automation
Most businesses could benefit from automation. For example, do any of the below operational pain points sound familiar?

Your customers are complaining because their applications take too long to process, or their emails take days to get answered.
You can’t say exactly why your processes aren’t working because you can’t “see” what’s causing the inefficiencies.
Your knowledge workers are restless because they have little time for high value work. Instead, their days are filled with filling out forms, redirecting questions or performing work they weren’t hired to do, but spend most of their time completing.
Your business can’t keep up with compliance and regulatory requirements, the maintenance of which is stealing focus from key innovation initiatives.

These common problems can be mitigated by applying digital business automation software, such as data capture, workflow automation, process modeling, decision management and embedded AI. With the right automation technologies, companies can improve operations. Here are some examples.

Interactions between people, such as approval steps or determining when to send reminders for tasks.
Interactions with IT systems or applications, such as verifying client benefit eligibility information, obtaining product information, or updating a client record.
Making decisions, such as whether to accept a loan request, determining whether a claim or transaction is fraudulent, or setting the price for a shipment.
Processing and storage of documents containing relevant data, such as extracting and digitizing data for a bill of materials, a purchase order, an account opening form, a permit application, proof of residency, or a medical claim.

To see transformative improvements, however, usually requires some combination of automation software, possibly from multiple vendors, or solutions to be built in house. This can be challenging given stretched IT resources and a business imperative to act quickly. This is why cloud-based automation platforms with comprehensive, pre-integrated tool sets can become a competitive advantage, allowing businesses to grow and scale into the future.
Finding the right starting point to scale digital business automation
Even with the right software tool set or platform, figuring out which initiatives to focus on first is no small task. It’s tempting to dive in and focus on the squeakiest wheel without looking at the wider picture. Without a user-centric, pragmatic strategy, well-intentioned projects can quickly go off the rails, no matter how best-of-breed the technology. So, how do you start? Better yet, how do you start in such a way that you can scale? Design thinking can help.
On July 18 at 11am ET, one of our clients and a couple of our automation experts are going to talk about how the practice of design thinking plus the right cloud-based tools can get your business to a quick, scalable win. Learn more and register here.
Need to get started right away? Learn more about where your company can apply digital business automation for better business outcomes by downloading the quick and practical guide to digital business automation.
The post How to start scaling automation projects with design thinking appeared first on Cloud computing news.
Quelle: Thoughts on Cloud