Managing software development is a balancing act. Ensuring teams are aligned on requirements, hitting deadlines, and delivering products to drive revenue and adoption is not an easy feat.  Today, most teams rely on siloed data and disconnected tools to help manage the process. 

Many engineering leaders (CTOs, VP of engineering, etc.) monitor their software development cycle at a macro level. If you are one of these leaders, you’re probably responsible for reporting to the Board of Directors or Executive Leadership Team about performance metrics and key deliverables that answers, “how are we doing?” 

However, the inability to aggregate and analyze data across multiple systems leaves engineering leaders unable to forecast current and future outcomes as they relate to larger business goals and objectives.

Product Development Lifecycle Disconnect

How does this happen? Too often, Engineering works on product deliverables while the rest of the company continues to plan and strategize against a predetermined, static deadline with limited visibility into day-to-day or week-over-week changes in software delivery timelines. If engineering and product leaders had tools that gave greater visibility across all teams and all data from the many tools used to build software to get a clear picture of how work is progressing, we could head off roadblocks proactively. Engineering would be in a better position to communicate and align with the C-Suite, Sales, Marketing, and Customer Success.

Making meaning out of all the disconnected data

The challenge is made all the more difficult because at-scale software teams rely on complicated processes with work being done at many stages and in different tools. And of course, very little of this is integrated to give you an accurate picture of what is going on. Your software delivery process and the tools you use might look something like the below, and often, varies by each team in your organization.

software delivery tools

Each of these tools plays a crucial role in the development lifecycle. They can help you see when things are going well and identify certain acute failures, but they rarely enable you to understand when these acute problems will manifest into systemic failures. It goes without saying that developing software is not linear - in fact, chaos and change are almost guaranteed…

software delivery workflow

The challenge many teams face is how best to manage changing requirements and timelines, keep stakeholders informed, and orchestrate profitable go-to-market efforts. The problem with these dispersed tools is that until recently, there was no way to bring them all together in order to perform a meaningful, comprehensive analysis — at least not a way that didn’t take weeks and was outdated the moment you gathered it. This leaves decision-makers in the dark, with questions like, “How can we reduce risks in our software delivery and identify unknown unknowns?” and even questions as basic as, “Are ANY of these projects going the way we expected?”

With the right data in the right hands, you can begin to get a better understanding of what is going on across teams and projects, show progress and manage expectations at a granular level with product stakeholders from across the organization. Heck, you could even be proactively mitigating those risks to ensure on-time delivery…

Enter Predictive Forecasting

In a recent poll, Allstacks asked engineering executives to identify their top challenges. Here are those results:

  1. Visibility in tracking towards business goals.

  2. Ongoing performance improvement

  3. Prioritizing the many moving parts in any development process.

To make better use of all the data available at different stages of software development, you could hire an analyst to compile and crunch the data in a spreadsheet or build queries that tells you how work is progressing — or you could use an automated and predictive solution to forecasting and to be more proactive in responding to changing scope and timelines. Predictive forecasting helps you manage risk in the development process to land at more predictable, reliable, and repeatable business outcomes. 

Allstacks wanted to help companies address those challenges. We bring together historical activity data from 20+ commonly used engineering tools into a single outcome-driven software intelligence platform. We break it down further below.

Software Forecasting Equation:

Product-Engineer Allstacks Equation.png

We developed an equation we use to gather the most useful data and bring it to your attention when and where it is needed most.

Here’s how it works: The Product team determines the scope of the work for Engineering. That scope of work is squared against Engineering’s capabilities (velocity, throughput, etc.) in moving the project forward. Multiply that by the Risk involved. Risk could be anything from an illness or vacation of a team member, to the dynamics of everyone working remotely, to external factors of different teams working on different aspects of the project and creating pull requests or other requirements for data to be shared.  

Predictive forecasting looks at these components to predict the likely outcomes you can expect, based on the data that is coming in related to Product, Engineering, and Risk. We’re using machine learning to look at historical work data and build outcome models.

By using a solution like Allstacks, managers can see the entire software development process in one place and quickly identify issues, locate bottlenecks, and discern other inefficiencies faster. This means that when they report to the Executive Leadership Team or Board, the information they present is accurate, verified, and a true insight into exactly what’s happening in real-time.

Like many companies, Convo, a workforce collaboration solutions company, was running into the same disconnects. They started using Allstacks and the results were dramatic and easy to quantify. John Steinmetz, CTO at Convo says,

“Using Allstacks, I can consolidate and organize all of my engineering processes in one place to quickly make changes and better understand where my inefficiencies lie. I get a clear picture of where we are, so I can determine where we want to be.” 

To go from missed deadlines and unexpected failures to predictable outcomes; that is the power of predictive forecasting. Good leaders are adaptable to change and are often able to report why these changes took place in hindsight. Great leaders, though, will not only adapt to change quickly, but can pinpoint why these changes are necessary - or even occurring - in the moment with the right software intelligence to guide them.

Using a predictive forecasting tool for engineering like Allstacks will result in greater company-wide alignment, savings from misspent time and missed opportunities, and a visible acceleration of development velocity. It really is a game-changer

Listen in as our VP of Customer Experience, Josh Teitleman and CTO at Convo, John Steinmetz chats more about this.

 

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