With Corbett, teams gain access to intelligence features that allow for the leveraging of AI to deliver improved software. Digital.ai now integrates and centralizes data from more sources from development through to production, so users can avoid ruined reports and analytics and use AI to predict possible outcomes based on past results.

This release brings new persona-based dashboards that can be used to analyze data for every stage of application development and delivery while also showing performance indicators for team and princess efficiencies as well as risk reduction. 

The company stated that this expands on the existing predictive intelligence capabilities that apply machine learning to help teams assess alternatives, manage tradeoffs, and make choices in a more predictive way.

“The release of Corbett underscores our commitment to provide an open DevOps platform built for the enterprise and to deliver targeted solutions that support the complexity and scale of the world’s largest organizations,” said Derek Holt, CEO of Digital.ai. “With the Corbett release we take another big step forward as we deliver all new versions of our market-leading offerings and dramatically enhance the role of data, ML and AI within software development and delivery. As the pace of AI-based innovation continues to accelerate we are excited to harness the power of AI to unlock value not just for individuals, but for teams and organizations.”

Among the key enhancements included in Corbett is an improved Jailbreak Bypass Detection so that users can automatically detect the newest bypasses. This works to frustrate attackers and prevent jailbreaks.

Furthermore, teams get Release Manager and Platform Engineering Intelligence which works to cut back on risk by analyzing release dependencies and success trends to improve upon the identification of why releases might fail.

Lastly, Corbett offers the ability to integrate security checks into release pipelines for better governance. This lets organizations automatically check whether or not a list of protections has been applied to a mobile app by utilizing a new integration with OPA.

To learn more, read the blog post. 

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Now, the country is in another period of uncertainty. You’ve read the headlines all year: The Great Resignation, layoffs, a possible recession, Elon Musk’s takeover of Twitter shaking up marketing spending, introductions of things like GitHub Copilot and ChatGPT having workers worrying about their future job security, and more. The list could go on and on, but one thing that would help people through these times is knowing they’ll make it out okay on the other end. 

Unfortunately that level of predictability isn’t always possible in the real world, but in the business world, value stream management can help you with it.

According to Lance Knight, president and COO of ConnectALL, the information you can get from value stream management can help you with predictability. This includes things like understanding how information flows and how you get work done. 

“You can’t really be predictable until you understand how things are getting done,” said Knight. 

He also claimed that predictability is a more important outcome of value stream management than the actual delivery of value, simply because of the fact that “you can’t deliver value unless you have a predictable system.” 

Derek Holt, general manager of Intelligent DevOps at Digital.ai, agreed, adding “If we can democratize the data internally, we can not only get a better view, but we can start to use things like machine learning to predict the future. Like, how do we not just show flow metrics, but how do we find areas for flow acceleration? Not just what are our quality metrics, but how do we drive quality improvement? A big one we’re seeing right now is predicting risk and changing risk. How do you predict that before it happens?”

Knight also said that a value stream is only as effective as the information that you feed into it, so you really need to amplify feedback loops, remove non-value-added activities and add automation. Then once your value stream is optimized, you can realize the benefit of predictability. 

If you’ve already been working with value streams for a while then it may be time to make sure all those pieces are running smoothly and look for areas where there is waste that can be removed. 

Knight also explained the importance of embracing the “holistic part” in value stream management. What he means by this is not just thinking about metrics, but thinking about how you can train people to understand Lean principles so that they can understand how the way they develop software will meet their digital transformation needs. 

Challenges companies face 

Of course, all that is easier said than done. There are still challenges that companies face after adopting value stream management to actually get to the maturity level where they gain that predictability. 

One issue is that there is confusion in the market caused by vendors about what value stream management actually is. “Some people think value stream management is the automation of your DevOps pipeline. Some people think value stream management is the metrics that I get. And there’s confusion between value management and value stream management,” said Knight. 

Knight wants us to remember that value stream management isn’t anything new; It can trace its origins back to Lean Manufacturing created by Toyota in the 1950s in Japan.  

And ultimately, value is just the delivery of goods and services. Putting any other definition on it is just the industry being confused, Knight believes. 

“So people who are trying to implement value streams are getting mixed messages, and that’s the number one challenge with value stream management,” said Knight.

Digital.ai’s Holt explained that another challenge, especially for those just getting started, is getting overwhelmed. 

“Don’t be paralyzed by how big it seems,” said Holt. He recommends companies have early conversations acknowledging that they might get things wrong, and just get started. 

Where has value stream been? Where is it headed? 

In our last Buyer’s Guide on value stream management, the theme was that it aligns business and IT. 

Holt has seen in the past year that companies are adopting mentalities that are less about that alignment. Now the focus is that software is the business and the business is software. 

In this new mentality, metrics have become crucial, so it’s important to have a value stream management system in place that actually enables you to track certain metrics. 

“Things like OKRs continued to kind of explode as a simple means to drive better outcome-based alignment … simple KPIs around objective-based development efforts or outcome-based development efforts,” said Holt. 

Holt also noted that in Digital.ai’s recently published 16th annual State of Agile report, around 40% of respondents had adopted one of these approaches, and that was significantly up from the previous year. 

He went on to explain that companies investing in value stream management want to be sure that their investments are actually paying off, especially in the current economic climate.

He also said value streams can help organizations make small, evolutionary improvements, rather than one big revolution. 

“Value stream management is building on some of the core transformations that happened before,” said Holt. “Wiithout the Agile transformation, there would have been no DevOps, and without Agile and DevOps, there probably wouldn’t be an ability to talk about value stream management.”

So value stream management will continue to build on the successes of the past, while also layering in new trends like low code, explained Holt. 

What sets successful value stream management practices apart

Chris Condo, principal analyst at Forrester, last month wrote a blog post where he laid out the three qualities that set successful value stream management practitioners apart. 

1. Use of AI/ML to predict end dates. According to Condo, development teams with access to predictive capabilities are able to use them to create timelines that are more likely to be met. He noted that the successful teams don’t replace estimates produced by people on their team, but rather augment those estimates with machine estimation. 
2. Bottleneck analysis. Teams can use value stream management to discover what the real cause of their bottlenecks is. “When it comes to VSM, too many clients put the cart before the horse, thinking that they need a high-performing DevOps culture and tool chain to effectively use VSM. None of this could be further from the truth,” said Condo.
3. Strong metrics and KPIs. Development leaders want these metrics if they are going to be putting money into value stream management, so look for vendors that can provide excellent metrics. 

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According to Digital.ai, with this latest version, public sector and enterprise organizations can speed up delivery while still managing risks and focusing on driving value from software investments. 

The added intelligence capabilities work to aggregate customer data across the entire software development and delivery lifecycle, automatically creating a DevOps data lake to create a single source of truth for an organization’s investments from planning to production. 

“Software strategy now underpins every business strategy and business leaders need to navigate global economic uncertainty with agility, automation and security,” said Stephen Elop, CEO of Digital.ai. “We are truly excited to be delivering to our customers our latest release that removes the mystery and complexities in mapping software investments to topline business goals and priorities. Digital.ai believes that the future of enterprise DevOps is being able to turn data into actionable, predictive insights.”

Additionally, users gain real-time insights, historical trend analysis, and predictability in augmented analytic dashboards. This contextualizes data and allows for organizations to observe trends across the enterprise.

Users also gain access to a Hoylu whiteboard integration so users can utilize whiteboard-based collaboration with Hoylu’s visual and iterative approach to achieve better Agile practices, enhancements to the recorder for Testing, expanded application security, and more.

To learn more, visit the website. 

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Digital.ai Agility 21.3 includes usability improvements, such as checking that required fields in tasks are completed before a story or defect is closed, and columns that auto-collapse if empty in Portfolio Item Kanban, story, task, and test boards. 

Updates in Digital.ai Release 10.3 include a new multi-select Listbox for managing multiple application releases and a Kubernetes Operator for Digital.ai Release and Digital.ai Deploy. 

And Digital.ai Deploy 10.3 also adds a new redeployment capability that makes it so that applications don’t have to be undeployed before they are redeployed.

“Integrating tools and tracking progress of work items across complex release processes is challenging for large enterprises. At Digital.ai, we have been focused on improving our ability to provide end-to-end visibility of software deliveries, increasing the efficiency of organizations’ release processes,” the company wrote in a post. 

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AWS Cloud Control API exposes five common verbs (CreateResource, GetResource, UpdateResource, DeleteResource, ListResource) in order to easily manage the lifecycle of  services. In addition, Cloud Control API will continue to add support for existing AWS  resources across services such as Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3).

TypeScript 4.5

Microsoft recently announced the release of TypeScript 4.5 in beta. In order to get started using the beta, visit here to get it through NuGet. The release brings several highlights with it, including: ECMAScript module support in Node.js, private field presence checks, better editor support for unresolved types, and many more.

In addition, this release also brings users: supporting lib from node_modules, template string types as discriminants, –module es2022, tail-recursion elimination on conditional types, disabling import elision, type modifiers on import names, import assertions, faster load time with realPathSync.native, snippet completions for JSX attributes, and breaking changes.

For more information on this and future releases take a look at TypeScript 4.5’s iteration plan. 

Digital.ai announces solution for SAFe

The Digital.ai DevOps Value Stream Delivery for SAFe recently debuted at the 2021 Global SAFe Summit. The solution combines agile planning and DevOps solutions with next-generation AI-driven analytics and metrics integrated end to end and optimized for SAFe.

The Digital.ai Value Stream Delivery for SAFe allows organizations to solve different challenges and deliver on their SAFe initiative goals. With its unified environment the adoption of scalable agile practices are simplified. In addition, it also provides other benefits, such as: simplifying SAFe adoption, scaling agile practices, improving business decisions, connecting end to end, and increasing delivery speed and reliability.

This solution combines four different products: Digital.ai Agility, Digital.ai Release, Digital.ai Deploy, and Digital.ai Analytical Lenses. 

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The digital transformation challenge
Online sales increased 43% year-over-year for the month of September, as commerce and customer interaction continue to move to digital platforms at an unprecedented rate. Enterprises that carefully planned their digital transformation over a span of several years have now seen that timeframe shrink to months, as a result of COVID-19. 

As the pace of change accelerates and organizations scramble to keep up, they are also grappling with the challenges of a remote workforce. With teams no longer working side-by-side, whiteboard sessions and institutional knowledge can’t be counted on to address customer needs and solve business problems. Companies need scalable, reliable systems capable of providing complete information in context, throughout the enterprise. And they need them now.

The value of value streams
DevOps and Agile have been integral to the software delivery process for some time now, but neither methodology is able to deliver the whole picture. According to Gartner ‘s October “Predicts 2021” report on value streams defining the future of DevOps: “As organizations expand usage of agile and DevOps, teams find it challenging to detect and remove constraints to product delivery. This hinders their ability to improve velocity, increase quality and optimize value.” The report goes on to say that “Agile and DevOps teams who focus only on technical performance metrics (at the exclusion of customer-value-centric metrics) will fail to align their priorities with the organization.”

To compete in the new digital economy, organizations must focus on the delivery of customer value. They must integrate DevOps, agile and other tools, and then they must capture, extract, analyze and leverage information from those tools to drive value for the business. Assuming you know which resources are being devoted to a task or project isn’t enough. To truly meet and exceed customer expectations efficiently and at speed, you need to know exactly which resources are being used, where and how, in real-time.

At the software development level, an integrated value stream approach gives teams the insight they need to go beyond optimizing their pipelines for speed and quality, enabling them to deliver measurable value to the business. At the organizational level, a value stream approach provides a single-pane-of-glass view that provides stakeholders visibility into every stage of the software delivery process, improving management and governance company-wide.

A win-win-win for customers, the business and employees
A customer-centric, value-based strategy provides a flow of information from the business to development teams about what customers really need and gives those teams the freedom to make adjustments to ensure that the end product maximizes the desired business value and meets customer expectations. Everyone has visibility into the process, and everyone has the ability to affect the outcome.

This integrated, data-driven approach is critical now more than ever, when so much work is being done remotely. When everyone has visibility into the process, teams work better and smarter. Rather than jumping onto yet another video chat to piece together incomplete information from spreadsheets and conversations, individuals can see what they need to be working on and how that effort will impact the business outcome. Not only does the business benefit, but individuals gain a greater sense of accomplishment, knowing what they’re doing aligns directly with the business goals and the customers’ needs.

The time to act is now
If you aren’t asking yourself: How can I deliver better value with what I have today, you may find yourself losing customers tomorrow. According to a July Gartner research report, “Use Value Streams to Drive Customer Centricity, Design Services and Operating Models, and Technology Platforms,”: “By 2023, 90% of organizations at advanced stages of digital transformation will find that poor customer experience is their biggest barrier to further success.” 

While that might sound like a grim statistic, the good news is that organizations of any size and at any level of process planning sophistication can benefit from value stream management. Start by sitting down and mapping out your existing processes by hand, then ask yourself where improvements can be made and how your organization and the business can benefit from those improvements. How will you — and your customers — benefit when you have end-to-end data in real-time? Then, look for a tool that allows you to gather, measure and present the data you need in a single pane of glass, will which enable the business and the individual user — no matter where they reside in the software life cycle — to leverage information in a way that produces better business outcomes.

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According to Mike O’Rourke, chief research and development officer at Digital.ai, there is a missing link between DevOps and the business. “There is no link between the things the development organization is doing in the DevOps space in terms of the way they are managing their success versus the way the business is managing their success,” he explained. 

Success tends to differ depending on whose measuring it. For instance, success for the development team might be how fast they are able to respond to changes, get a release out or how many bugs they can detect and fix before a release goes out. For the business, success might be getting a 5-star app rating or improving customer satisfaction. Both sides matter, but the business and development teams really need a way to understand whether or not what they are measuring is having positive or negative outcomes. 

This is where the notion of value stream is becoming extremely important to extend the scope of DevOps and achieve business success. “As you go through and you are developing something, wouldn’t it be great to know what the business expects to get out of that?” O’Rourke said. “In most companies out there, there is a big gap between that understanding. What are we trying to do as an organization is dramatically reduce the gap to the point where when the business has an outcome they are looking for, everyone in the development organization understands what it is they are looking for, why they are looking for it, and how they can help.”

The first step in getting there is creating a value stream map, according to O’Rourke. A value stream map maps each individual piece of the process and links it to the entire development organization so teams can identify potential places to improve and add more value. 

“The key is to be able to flow information throughout the development life cycle. That is something that DevOps doesn’t necessarily do today out of the box,” said O’Rourke. “What DevOps does very well is it looks at things like burndown charts and how many releases you did, where you build failed, etc. etc. But actually watching the value flow throughout the development life cycle is something that they are missing.”  

It’s also not just about flowing information throughout the pipeline. It’s about being smarter historically about changes that occurred, how they are linked, and what was the result. Traditionally, the DevOps process has stopped when an item has been delivered. Value stream takes it further and enables teams to gather information about how customers are using an application, which features they are using, why, how it is performing under load, and how secure it is. “All this development information now gives me a much richer set of insights that I can hand back to the business about what is really happening with their app and because I know why they were asking me to do this work, I can present it in ways that are interesting to them,” said O’Rourke. 

Digital.ai helps DevOps teams expand their reach and become a value stream management organization by having context management built right into their platform so everyone can understand what tasks and defects are related to a certain set of checks, builds, pipelines or releases. “This notion of value stream mapping now flows throughout the whole system and as long as you are using some tool whether you are doing OKRs or value stream mapping, as long as you can flow that in to the beginning of the pipeline, we will make sure that flows throughout the rest of the pipeline,” said O’Rourke. 

The company also integrates with popular application performance monitoring, AIOps and ITSM tools so it can gather information regardless of the environment the app is running in. When an app gets deployed, it can collect everything from the operating system to the memory size and bring all that information about what is happening inside the application back to the developer and business. 

For organizations using their own DevOps tools, Digital.ai provides an artificial intelligence add-on, which includes machine learning and analytics built into a conformed data lake.

“We do believe everyone is going to want to go to value stream management overtime, but most organizations are still struggling just trying to get this information back to their own teams,” said O’Rourke. 

Learn more at digital.ai.

Content provided by SD Times and Digital.ai

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According to David Williams, vice president of strategy and platform product management at value stream management company digital.ai, companies often will believe that a value stream implementation is working just because software delivery is faster, customer satisfaction is observable, or performance of systems is going up. But unless the two value streams — the DevOps value stream and business value stream — are aligned, value stream isn’t really a true success. 

RELATED CONTENT: 
State of Agile report reveals an increased interest in value stream management
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Virtual VSM DevCon

“When value stream management is mentioned, it is typically assigned to the development or the DevOps value stream,” Williams said. “That in itself is a bit of a challenge because what it means is that companies may not be seeing the clarity of managing it to the business value stream…If the lens is not on the business value stream itself and how to achieve that objective, then all that’s going to happen is that value stream management will become a better ability to optimize your DevOps-based processes, which will not necessarily actually do anything to the business value itself.”

Often, the business side of value stream understands what they are trying to achieve, he explained, but that might not be properly communicated to or understood by the DevOps teams. According to Williams, what often happens is the business executives will put an objective into the pipeline, and then developers will build a project to suit that objective. Where the disconnect lies is that there is a long lag time before a development team’s efforts are recognized as they pertain to the business objective. 

“That’s the biggest problem,” said Williams. “The business gets it, the DevOps teams believe they get it, but generally businesses understand the difference between these value streams, but they’re not tied together. So the problem is enterprises struggle because the software that’s delivered is not accountable or measurable to prioritize against business outcomes.”

So how do organizations overcome this disconnect? According to Williams, the first step is to have something in place that unifies these value streams. In other words, both teams need context for what they’re doing. For example, development teams should have the ability to directly see how the software they’re releasing is impacting the business objectives. “When I do something in the software release life cycle, as it goes out into the business, it’s actually measured against what it’s meant to be producing. So it’s not something to be discovered over time.”

The human aspect is important to value stream success, Williams said. He believes that contributors will be more motivated when they can actually see how what they’re doing is impacting the business objective. “It helps the person doing the work to understand what their own value is and their own contribution and prioritize their work load accordingly in support of that…So business value, understanding your own worth, understanding how you contribute to the business outcome, all of these help organizations in respect to satisfaction.”

Content provided by SD Times and Digital.ai. 

Hear more from David Williams at VSM DevCon, a one-day, free virtual event all about value stream management. Williams will give a keynote about the miscommunication of objectives in value stream management. 

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“We expect a greater percentage of organizations to embrace VSM going forward, as understanding increases and tooling more capably enables the unification of the ‘concept of cash’ value stream,” the report stated. 

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What problem are we looking to solve with value stream management
D2 Emerge to launch industry’s first value stream event
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Additionally, the report found that agility is still confined to the technology side of business and in order to achieve true business agility, organizations must have effective alignment and coordination across all areas of the business. 

VSM “is a combination of people, process, and technology that maps, optimizes, visualizes, measures, and governs business value flow (in the form of epics, stories, work items) through heterogeneous enterprise software delivery pipelines from idea through development and into production,” the Digital.ai team wrote in a blog post. 

The report also found that organizational culture continues to be a top challenge to adopting and scaling Agile. Other challenges included resistance to change, inadequate management support and sponsorship, and not enough leadership participation. 

In addition, this year’s report took a look at the impact of COVID-19 on businesses and Agile adoption. Some findings here included 55% of respondents say their company plans to increase the use of Agile; 43% say Agile adoption has increased over the last 90 days with 15% saying it increased significantly; and 33% increased or expanded Agile adoption in the last 90 days to help manage distributed teams.

Distributed Agile teams have also become the new normal as more teams are working from home. “While working face-to-face can be desirable for Agile practices, survey respondents indicated that organizations are supporting distributed teams and team members. There is no evidence of a trend toward increased co-location, as more respondents indicated their organizations continue to support and encourage team collaboration across geographic boundaries and timezones,” the team wrote.  

The Scaled Agile Framework (SAFe) was also found to be the most popular scaling method followed by Scrum@Scale. 

“Since the earliest days at Scaled Agile, our core belief has been simple: better software and systems make the world a better place. What has emerged during this global pandemic is confirmation that — given the right environment — remote Agile teams can be highly productive, and enterprises continue to get outstanding business benefits from applying SAFe,” said Dean Leffingwell, creator of SAFe.

Other key findings of the report included: 

• Risk and compliance continue to trend upward
• There is a shift in Agile techniques with product road-mapping increasing and release planning decreasing
• 60% have increased speed to market with Agile
• Reasons for adopting agile include: accelerate software delivery, enhance ability to manage changing priorities, and achieve increased productivity.
• Recommended Agile project management tools include: Atlassian Jira, VersionOne, Jira Align, LeanKit, Target Process and Microsoft Azure DevOps

The Agile report was conducted from August to December of 2019 with an updated COVID-19 questionnaire conducted in May of 2020. 

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