The last few years have been disruptive for engineering teams. With a haphazard, but necessary shift to remote work, teams are still adjusting with the constantly changing engineering ecosystem. Despite companies like Dell, and Walmart calling engineering back to the office, remote work is still on the rise with 48% of employees allowing distributed work for their teams.

Engineering demand is still swelling in terms of requested features, and complex product updates while the supply of the talent pool remains limited, and in fact, scarce. The tech talent pool too presented a structural trichotomy- engineering layoffs, mass hirings and great resignation going hand in hand. Most organizations including Google and Meta hired more and more devs as a measure to counter demand, and reach potential output, but in vain.

As teams went through the interactions of hiring, resigning, and layoffs- they realized the real problem was not the dearth of resources, but lack of visibility into developer workflow, low engineering productivity, redundant, and badly run processes, and stunted developer experience. These issues further snowballed as critical vulnerabilities kept getting exploited, while 80% of IT resources were spent on firefighting.

Another issue plaguing the tech community has been developer burnout. Developers, despite being a critically important asset for organizations, felt overburdened with unsustainable workload, and even underwent chronic stress tendencies.

These pandemic years brought a lot of crests and troughs for engineering organizations, with the critical lesson—take care of your engineering resources (both people, and processes) before it’s too late.

In the current landscape, it is critical to engage in thought-provoking discussions around data-driven engineering workflows. Furthermore, there exists a compelling need for a comprehensive platform that seamlessly integrates all aspects of the software development process, catering to developers, engineering managers, tech leads, and C-suite executives.

It is now time for engineering teams to think about a tipping-point technology— an engineering management platform to help them plug developmental loopholes, while working towards developer well-being.

Engineering Management Platforms: Is the Hype Real?

Last year made huge strides in the typical outlook of CTOs, and directors of engineering in using engineering management platforms. They went from “I might use this platform because my EM recommends” to “I need this tool for end-to-end visibility into the workflows,” even personally investing themselves into their developer success. It’s safe to say that Engineering Management Platforms have become a strategic topic for most C-suite execs.

But what makes an engineering management platform so critical to engineering success today, you may ask?

An engineering management platform enables data-driven transformation of engineering teams through bringing operational efficiency, optimized resource allocation, accelerated time to market, and breakdown of developmental silos. In the last two years, 77% of high-performing teams have used management platforms to track engineering progress, and fulfill development milestones. The number speaks for itself and shows the trust engineering leaders put in data analytics.

The last few years surely paved the way for leaders to start using engineering management platforms. However, they haven’t yet tapped the full potential of work analytics, and management– thus a call for EMPs to reach their full potential.

9 Benefits of Using an Engineering Management Platform

Teams need to enter into a full-fledged engineering management year.

Let’s see why teams should use an engineering management platform.

1. Resource-cost optimization for C-sec executives

The recent years have been tough for the market, especially when trying to extract sufficient RoI from an expensive, and uneconomical developmental process. In some cases, it has even cost as much as 63% of a project’s budget.

Any company has limited resources, but unlimited software requirements: constant upgrades, ongoing maintenance, frequent firefighting, KTLO, unplanned work, and iterative development. Currently, only 8% of companies have successfully met their business goals using their ongoing engineering methods. Without data-backed insights, engineering investments are at the risk of getting pulled towards abstraction, with more time and resources spent on unplanned, or over the surface work- bringing no to minimal value to real project goals.

resource and effort allocation in engineering teams

An engineering management platform brings alignment between business expectations, and engineering work by focusing on what brings most value immediately. With 360 degree visibility into engineering workflow, executives know where their team is headed, the blockers in achieving milestones, and probable outcomes from the investments made.

Moreover, an EMP comes with enough clarity for execs to divert investments towards roadmap, shift low priority into high priority work, and have more strategic discussions with stakeholders. As of now, teams have started saving upto 28x of their budget overruns after using an engineering management platform for allocation needs.

2. Operational Management for Engineering Leadership

Now is the era of a fast world, and faster developments with absolutely NO compromises on quality. This means, leaders will have to keep engineering work on the rails all the time. And that’s where robust process management comes into play.

In an ideal world, business expectations filter down from execs, to engineering teams which then break these goals down into measurable and quantifiable developmental targets. As and when software teams start delivering, tracking process metrics become important to gauge operational health, benchmark with team expectations, and find out red flags way before they start damaging the development cycle.

It’s not just us, 67% of engineering leaders too believe in managing engineering processes with help of metrics. However, only 27% have been able to crack the art of using productivity indicators for operational management. The right EMP platform can help teams with customizing the optimal process metrics, add the right context, and 360-degree profiling to offer a true picture of where an engineering team is headed. Metrics alone cannot optimize a team’s operations. However, when leads have enough insights into where they are lagging (high cycle time, low deployment frequency), it becomes easier to figure out the ‘how’, and ‘what’s next.’

For example- Cycle time is more often used as a metric to infer team velocity, and can act as a warning signal for a fragmented development cycle. High cycle time is not just a team problem, but also affects individual contributors and the way they work. All of this can be streamlined with engineering analytics by digging deeper into data, and looking to optimize the reasons behind a falling SDLC– broken feedback loop, pending code reviews, and unsustainable delivery timelines.

Rising demand came with enough challenges for engineering leaders in streamlining developmental processes–determining the right metrics for teams, accuracy of results, capturing contextual data, and additional time spent by team leads and EMs in feeding datasets.

In our conversations with engineering leaders, we saw a paradigm shift in how teams ship software after using an engineering management platform. Amenify recorded 3x faster project deliveries after using Hatica’s engineering management platform. On an average, teams reduced their cycle times by 25%— a mean reduction of upto 4.2 days.

The numbers have become super important in today’s complex SDLCs where customer demands, and business priorities keep changing– leading to a constant hassle for engineering teams. When a team’s workflows are automatically streamlined, they have enough space to handle changing requirements, and unexpected emergencies without distorting their team pace.

3. Developer Well-Being

2022 was a mayhem when it comes to developer well-being. 83% of devs faced burnout at the workplace, while 42% of devs were fedup of their existing work, and looking to switch, or resign.

The two parallel events point to one phenomenon– Developers aren’t happy, and are in intense pressure to perform. The demand for new software doesn’t seem to slow down, but devs can only perform so fast. Besides, high workload, unsustainable SDLCs and operational bottlenecks too impact devs, and crucifies their productivity.

To build any successful engineering team, it is imperative for EM and leads to celebrating their developer’s work, and ensuring devs enjoy what they work on. Engineering analytics is the key to empowering devs in doing their best work. We already saw how EMPs can take care of the second part of the problem– operational inefficiencies. Let’s talk about the former now.

Data-backed insights empower team members to confidently acknowledge and appreciate a developer’s contributions. By having real-time visibility into their workload, EMs know where most of their devs’ time is being invested– hirings and interviews, handling incident load, attending excessive meetings, or meeting engineering demands by working outside regular office hours.

It also allows engineers to maintain a flow state, by decluttering a developer’s work schedule, combine meetings together, minimize context switching, and offer them space to find their deep work state.

Developer well being dashboard

Using an engineering management platform is the best way out for EMs and leads to fight developer burnout, and take care of devs in real.

4. Sprint Health

A successful sprint is the first step towards building an efficient SDLC. It’s already well-established that teams conducting regular sprint planning deliver 250% better quality projects than teams who don’t. When teams are on the same planning cadence, it becomes easier to enroll members into engineering vision.

An EMP helps teams to conduct well-structured sprints with end to end visibility into how the sprint is moving, and if everything is on track as planned. With data and an engineering management platform in their arsenal, EMs are able to answer the most fundamental, yet troublesome sprint questions:

  • Did we add new issues to the current sprints? Could we have pre/postpone them for another sprint?

  • Is there any scope creep in the sprint? If yes, then what is the status? If the creep is expanding, then what are the reasons?

  • Did we carry forward any incomplete work from the last sprint?

  • What is the weightage of planned and unplanned work this sprint?

  • How many high-priority issues have we resolved this sprint?

  • Where are we spending most of our time? Are we focusing more on taking down bugs, or completing sprint stories?

Project delivery overview by Hatica

An engineering management platform helps teams to dive deeper into their sprint performance along with additional insights into how teams can fare better, and build more efficient sprints, without shifting blame, or stopping current work for process transformation.

5. A Positive Developer Experience

58% of C-suite execs know the importance of Developer Experience to drive work transformations. However, most fail to understand how it can be achieved.

Developer experience is beyond coding; rather it is a culmination of how each process, workflow, or tool, affects developers. A poor DevEx snowballs into sinking results, impact on the business value-chain, and compromised product quality.

So, can the use of an engineering management platform solve my DevEx problem?

The answer is both, yes and no. Creating a positive developer experience requires a bottoms-up approach with all devs eventually becoming the part of decision-making, and being recognized for their contributions, while their work is more streamlined, and communication channels are more active. And an EMP can help teams to achieve so.

In the past, usually a smooth, and transparent DevOps culture was the sign of optimized SDLC. However, as development itself underwent complexities, and stopped being linear; the adoption of DevOps itself started suffering. An engineering management platform helps to resolve inefficiencies of the DevOps cycle itself by streamlining MTTR, cycle time, deployment frequency, and change failure rate, while empowering devs to forgo any hesitation in adopting new tools, culture, and technologies. The overall idea of optimizing DevOps- the caretaker of developer workflows itself, makes devs life easier, and creates DevEx in an organization.

With an engineering management platform, teams can foster teamwork, minimize technical debt, have an optimized SDLC, and address unsustainable workload. These improvements when done in cohesion with each other, and over a period of time is a sure shot way to enhance the overall satisfaction of developers with the work they produce– thus building a positive developer experience.

6. Code Hygiene

Today, engineering teams are not just looking for macro transformations, but reforming even the micro structures, especially the way a code is written, and shipped. A clean code is hardware compatible, has close to 80% test coverage, and is easily maintainable.

However, a major challenge plagues most organizations we work with. More than anything, it is the quality of code written that haunts both reviewers, commit owners, and even tech leads owning the whole project. Devs often skip code best practices, have PRs of upto 500 lines, and most times, even merge unreviewed PRs– just to get work done in time. However, the issue backfires soon when large-sized PRs become difficult to review and merge, often clogging the delivery pipeline, and blocking developers.

An engineering management platform ensures process hygiene by benchmarking the team’s coding performance against accepted best practices. Leaders can visualize each IC’s workmap, and look for themselves into what more can be done for sanitized code management. That way, EMs and team leads can better understand the impact of PRs, navigate risk involved in the process, and empower devs into doing their best work, without accumulating unnecessary tech debt.

7. Enhanced Team Collaboration

Remote work often comes with the challenges of visibility into a developer’s work, and most times, the onus is on devs themselves into how they can drive work visibility. As engineering managers have limited idea of what their devs are working on, it often comes at the cost of rising communication debt, and a downward collaboration graph.

More often, devs are also stuck in their code review cycle because of the overarching reason– poor work visibility, hampering their review collaboration process. This lack of collaboration often manifests in the form of burnout, high workplace stress, and an overall developer productivity crisis.

Amidst rising friction between devs-devs, and IC-EMs, data has once again proven to be a valuable asset in driving collaboration.

Activity log table by Hatica

Using an engineering management platform comes with end-to-end visibility into a developer’s workload, processes, and bottlenecks without putting any extra effort from devs or EMs.

Another way to drive collaboration through EMPs is via data-driven 1:1s. Without appropriate analytics in place, managers end up spending hours sifting through all developmental work to gauge process success, people health, and final deliverables. The constant juggle makes 1:1s seem like a burden more than a call to discuss blockers.

However, when 1:1s are data-driven and have sufficient context around collaboration metrics, productivity signals, and employee experience– the overall conversation turns more structured, action-oriented, and relevant. Data also offers enough groove and agenda around update meetings that ‘actually’ caters to a developer’s needs rather than becoming just another periodic standup.

An EMP not only helps engineering managers to have data-driven 1:1s but navigate bottlenecks, and appreciate each other for work done, and efforts put in. Now EMs have better ideas about: Which devs are at the top of their game, or why some PRs are resolved faster than others. When managers and developers work together to overcome workflow issues, teams unlock meta productivity, and supercharged collaboration. Teams are expected to become 16% more productive when they engage with each other through the power of data and analytics.

Moreover, code reviews too can become efficient with the use of engineering analytics. Managers can use dev workmap to distribute reviews evenly within ICs. EMs can also track which engineer has more PR comments, or the average approved PR changes– all signs of increased collaboration.

EMPs take care of a developer’s journey– right from the planning stage to shipping code to prod, and accommodating customer changes. In today’s chaotic software development, an engineer only codes 33% of the time, with more than 20% of time swallowed by bureaucratic and administrative work. The less effective coding hours doesn’t do justice with the rising demand for good software.

With right engineering analytics, devs have seen an uptick of 10% in their effective coding hours. How? The answer is simple– by bringing method to their chaos through streamlined meetings, data driven 1:1s, working towards SDLC health, and effective code reviews.

This data also helps cross-functional teams to reduce dependencies, and reduce their backlogs without sitting blocked for hours, as in the past. This way, EMPs synergize all the business units including development, DevOps, testing and product management at one place, with holistic tracking of end-to-end product development. We are positive when we say that 2023 would transform the role of stakeholders, from being arm-chairist to getting actively involved in decision making.

8. Streamlined Work Allocation

Ask any engineering manager about their greatest challenges and they’ll be sure to include- workload distribution. As of now, only 29% of engineering leaders were confident of their workload distribution. The others have poor visibility into how and what their devs are working on, or managing their current projects.

As uneven engineering demands rise, so does the uneven work allocation. In turn, most devs become overloaded with code reviews, or incident load, while others have a fair share of coding and grooming time into their workday. Sometimes, the work allotment is done without accounting for geographical barriers, past trends of progress, and existing work share.

With contextual data, engineering managers can figure out achievable ways to allocate work with all devs on the same page. When EMs have full visibility into each dev’s workflow, their strengths, weaknesses, and current day to day work progress trends, they will be effective at dividing tasks without any name-calling, or team friction– even enhancing their collaboration.

Managers, with all data in one place, can see each workload per developer, and how to optimize work hours for a healthy mix of all activities: code, incident management, hiring tasks, and PR reviews.

The greater outcome? Happy, and productive developers.

9. Unlock Developer Productivity

Here comes the blackbox of the engineering world– how to increase developer productivity, and where to start? By now, it’s pretty clear that data is not just the new oil but the key to resolve any hindrance that bogs down developers.

Developer productivity is essentially a product of small incremental steps taken at each step of the development workflow– right from writing legible code, to establishing a strong review process, optimizing processes with help of success metrics, and taking care of developer well-being. We already talked about how EMPs take care of this part of the problem.

Let’s talk about the more covert issues plaguing developer lives.

Status update meetings do not bore sufficient results when EMs lack clarity on their developer’s work schedules. They are more or less futile without data, and using an EMP has the potential to transform boring, and unproductive meetings into on-point, and strategic discussions.

Establishing sufficient maker time for each dev in an EMP can help devs minimize distractions, and reduce cognitive clutter, and context switching. Moreover, building feedback loops through data can help devs in understanding work expectations better, while motivating them to play on their strengths.

In an ideal but aspiring world, devs should also have enough time for grooming, growth, innovation, and training themselves and their mentees. Streamlined work allocation takes care of this problem by ensuring sufficient time in hand of devs for their own growth, and development– all in all increasing team productivity.

Engineering Management Platforms: Breaking Work Silos and Driving Engineering Success

This is the year of engineering transformation. With rise in AI, IIoT 5.0, and data analytics, organizations have a cannot-miss opportunity to build optimized SDLCs, and ramp up productivity ambitions with limited headcount.

In these big shifts, data is the key to break down work silos, and keep energies focused on maintaining SDLC, and in turn, building better products. An engineering management platform removes the scourge of poor work visibility that weighs down not just engineers, but the entire team. High work visibility not only ensures collaborative relationships, but also frees up engineer capacity so they can do what they genuinely love.

A company of top engineers translates into an organization that supports a work environment where devs have the autonomy to work, and freedom to innovate. All this can be realized with the help of engineering analytics.

For C-suite executives too, EMPs have the potential to bring speed, security, and resiliency in engineering systems. In the long-term, using an EMP helps engineering leaders to iterate faster, and iterate better while bringing down costs of software development, and maintenance. The businesses going to survive the cold waters of disruptive technologies are not the ones with best assets or higher headcount; but that can strategically use data to pull more wins, and create opportunities out of adversities.

The future of work is secure, and rising engineering demand is a testimonial to it. With an added advantage of generative AI, GitOps 2.0, and AIOps, engineering management platforms will radically overhaul the way SDLC works today. The next phase of EMPs could act as a harbinger of this paradigm shift, and can unleash the true potential of a diverse yet synergised engineering ecosystem.

Trust us on this one, engineering management platforms are going to be the most phenomenal investment ever made in pursuit of driving engineering success!