Optimizing Delivery with Actionable Insights

Software delivery has always been difficult to manage. There are many moving parts involved in understanding the customers’ needs and translating these needs into technical considerations like latency, errors, security, and speed of delivery.

Modern software development is about people, processes, and tools. DevOps and Agile processes speed the software development throughput. They generally rely on teams to accomplish different parts of each project. These teams require coordination and management.

Knowing what each team and person is responsible for and how they add value to the deliverable requires you to collect and normalize information across teams, projects, and programs. For this, you need consistent measurement tools and processes.

The task is difficult for two reasons. The first is that teams working on the same project may be using different tools. The second is that software tools are developed to serve a specific purpose, such as CI/CD, rather than providing an end-to-end view.

In this article, we’ll look at how tool fragmentation presents a challenge for viewing your delivery progress. Then, we’ll examine how to use the insight delivered by tool integration platforms like ValueEdge to optimize your software delivery.

Tool Fragmentation Slows Delivery

There are several dimensions involved in determining how a software program is progressing. The code’s velocity from requisition to deployment is one metric. So is the quality of the code. You likely find yourself asking questions like these:

  • Are there errors or gaps that need to be fixed post-deployment?
  • Should these errors have been detected in the testing process?
  • Are there elements of the development process that need to be improved?

A mix of internal and contractor teams will bring a variety of methodologies to bear on the final project. Without management guidance, teams might select different metrics to meet their goals or even have different priorities entirely.

In addition to using different metrics, teams might choose to use different tools. Even when using the same tools, teams can adopt fragmented usage patterns. Your teams might use Jira for project planning, Azure DevOps for sprint management, and bring in additional tools for deployment and testing. So, there’s no way you can use a single tool to see the entire process, end-to-end.

Without being able to see this information holistically, it’s difficult to identify where the bottlenecks are. Are they occurring across the organization, or are they localized to certain teams, functions, or processes? You have limited information to guide your decision process.

Solutions to Fragmentation

You start solving the issue of fragmentation by getting teams to agree to a specific set of measurements. Although this can be a process of compromise, it’s difficult to improve if you’re using metrics that are not comparable.

Some organizations immediately look for a tool that views the process end to end. Although it seems logical, this method has a few drawbacks.

First, this demands that your teams replace the tools that they already use. In addition to the cost of the new tools themselves, your teams will incur expenses in training and initial implementation cycles. Furthermore, your teams will likely need to adapt their workflows to the new tooling. It’s a disruption to your primary objective: delivering software.

Choosing to use a single tool also presents another immediate challenge: You need to find a best-in-class tool that meets needs across the entire development process. Most tools are developed for a specific stage of the process, and it’s rare for one to be sufficient in all stages. Compromising and selecting a tool that’s a “jack of all trades and a master of none” may seem convenient, but it leads to problems later. For example, the publishers of specialized tools may improve their offerings for a particular area in the future. Choosing a single, generalist tool locks you out of these enhancements.

The Solution is Tools Integration

The stronger approach to this problem is through tools integration. Micro Focus ValueEdge is a modular value stream management platform designed for end-to-end work. You can use ValueEdge to integrate data from disparate tools and get a clear, single view of the data you need to analyze to improve your delivery process.

Insights is the analytics module in ValueEdge. It integrates with a wide variety of tools your existing tools to provide you with a unified view of your development and deployment processes. Teams can continue to use their existing tools for development, DevOps, testing, or whichever other process they’re part of. So, there’s no workflow change to adapt to.

ValueEdge Insights consolidates the data to give you a single source of the truth, eliminating the need for teams to spend time preparing reports that need to be normalized by the management team.

You have an extensive array of integrations available from ValueEdge Insights. With unified data, you can view the entire software production and delivery pipeline from end to end.

How ValueEdge Insights Delivers Actionable Knowledge

You can observe the progress across various projects contributing to a value stream at any point. ValueEdge collates requirements, backlogged items, and defects in a single view. This allows you to identify common problem areas across teams or requirements. It answers the common question, “Do all (or most) of my teams have to rework a particular requirement area?”

Since teams might use different agile planning tools, like Jira, Rally, or, ValueEdge integrates these into a single view. Additionally, you can use Micro Focus Connect to integrate a variety of third-party tools, such as IDEs, code management, CI, security, and testing tools. The RESTful API enables connecting other third-party applications or CI servers.

Coordinating Testing

A single integrated view of the value stream lets you coordinate your testing efforts. Being able to schedule and integrate the results in a central location reduces the amount of test record-keeping and reporting created by teams, which management then becomes responsible for integrating. Without coordinated testing, teams are responsible for conducting their own tests and acting on those results. To validate that all testing was done, management has to gather the results of those tests and then integrate and analyze them to determine the root causes of problems.

Centralizing the testing function allows management to improve quality by ensuring consistent execution and recording of all testing results, both manual and automated. You can then reuse test cases — especially in versioning and parameterization. Centralized testing also makes it easier to use AI-powered tools to analyze data from disparate teams to determine common problems or root causes, eliminating the cumbersome task of manually normalizing and cross-examining teams. AI gives your teams quick analyses and automated recommendations.

ValueEdge Insights for centralized testing lets you look at different data views to assess a holistic picture of your teams. You can then adjust team behavior, requirement gathering, or processes downstream. For example, if teams consistently run into acceptance testing issues but pass all the other tests, the problem might be that requirements weren’t understood. You can then use these findings to trigger automated actions, such as notifying responsible parties and providing details.

It’s important to note that, in a case like this, the root cause lies outside the DevOps processes. You need to examine organization-wide results holistically to uncover the root cause. In this case, an analysis of DevOps reports without insight from other teams wouldn’t discover poorly communicated requirements as the cause. Especially when dealing with a large number of teams and views, AI tools can dramatically reduce the burden of manual effort.


Reusing modules, services, open source code, and API calls across cloud locations exposes a larger attack surface to bad actors. Even a single vulnerability lets intruders move horizontally or vertically within your organization.

This means that monitoring is a more critical part of your security practices than ever before. Poor security practices like insecure data transport or hardcoded passwords for API handoffs sometimes become habits in DevOps teams under pressure to meet deadlines. Although it’s popular for many reasons, open source software may also have vulnerabilities — especially because the open source landscape has such a wide variety of offerings.

Identifying and mitigating these practices is difficult if your information is fragmented. ValueEdge Insights removes data integration and preparation time from the equation and allows you to instead spend your time analyzing and determining the causes of the vulnerabilities.


ValueEdge Insights provides an integrated view of your end-to-end software development, deployment, and post-release practices. It provides you with a single source of truth across an increasingly fragmented software landscape. Its integration engine allows teams to keep using the tools they already know and doesn’t require any changes in workflow.

Beyond just assembling the information, ValueEdge Insights provides analytics to assist you in focusing on the areas that need attention. It provides project tracking and functionality that helps remove bottlenecks.

Additionally, it centralizes control of all your testing. By centralizing, you reduce the amount of data collection you need to perform and encourage test set reuse. You’ll end up with easier, better-quality testing.

ValueEdge Insights also integrates security testing results to identify problems both within teams and across the organization as a whole.

Learn more about ValueEdge Insights and try it for yourself.

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