In any rapidly growing organization, the engineering leaders often find themselves wondering when did things get so complex. It appears as if suddenly it is no longer the small-ish team where everyone knew what everyone else was doing; back when there were just a few trusted tools and simple processes. Now the leader is faced with a group of teams, a bunch of new tools, and lots of new processes. It is impossible for one person to track.
This gradual change is an inevitable side-effect, of course. As the organization grows, it is imperative to divide the functions and bring in the specialists. The specialists in turn, bring in their own tools and processes. However, this doesn't make things easier for the leaders. The home-grown Kanban variant is now by-the-book SAFe 6, product managers are using new analytics tools, software engineers have introduced new CI tools, marketing has ambitious campaigns planned, top management wants to roll out OKRs starting this quarter.
Each change is necessary to make the organization deal with growing complexity. But this brings up a new challenge: How is a Director or a VP expected to track all of these?
Expecting every leader to be an expert in every function is completely unrealistic. So usually the fallback is to have the various functions collect the data and present it in weekly meetings. More often than not, the tools, initiatives, and processes grow independently of each other, without an overarching structure. This makes things even harder to understand. BI comes to the rescue and before anyone can blink, there is a whole team trying to squeeze data sources into the BI tool.
However, the fundamental problems remain unsolved...
1. Data is spread across various sources
And it is probably best if we let the data be. Asking the teams to copy over the data or manually scraping the data is not a good use of anyone's time!
2. Data Snapshots are usually stale
Let us say the leader has all the time, resources, and tools to harvest all the relevant data into nice dashboards every week (or even, every day). These snapshots will age rather quickly and are often stale before the actual decision-making happens.
3. Cognitive Load of Dashboards
One graph can inform. A dozen graphs are more likely to confuse. Cramming every pixel of the BI Dashboard with data and graphs only increases the leader's cognitive load. How is one expected to distill something that's actionable from a dozen graphs, each one screaming for attention?
4. Loss of Context
Metrics, tables, charts give a sense that things are in control. That things are being measured. However, they don't always guarantee context. The onus is on the viewer to understand. Someone with a software background may understand what the Jira Cumulative Flow Chart is saying more easily than say, what a User Flow Google Analytics chart is saying. That's not because the person can't understand what a Sankey Diagram is - it is because the person doesn't know how the flow is defined. Context is important!
5. Lack of Cohesion
Another major issue is that as the teams, tools, and processes grow, they also tend to diverge. While it is important to have autonomous teams, the data from their output should not be siloed. After all, their output may be a part of the overall organization's machinery to achieve a collective goal.
Even if organizations use a mechanism like OKRs to define these high level goals, they are seldom linked to what the teams are doing on a daily basis. The goals become one more thing to track, one more tool to manage. This leads to lower engagement.
How Axon helps leaders
Insights first, details when you need them
Axon highlights the areas where the leader needs to pay attention, such as People, Productivity, Planning, Quality, etc. Axon's Insights talk about the outcomes that may be impacted as per the signals received. Instead of drowning in data, Axon helps leaders identify the problematic areas and drill down to get to the root cause.
What's more: The insights are not snapshots - they are generated and updated using real time data.
So the leaders can:
Manage by exception by focusing on the problematic areas
Use meetings to solve problems, instead of identifying them. This is what leaders do best!
Make the data work for you
Most organizations don't suffer from a lack of data; the problem is that there is just too much of it! And more data doesn't necessarily make it easier to take action. It is humanely impossible for any leader to keep up with the data exhaust from the tools used by their teams. All this data has only one purpose: To help leaders make better decisions.
Instead of drowning the leaders in data, Axon has a conversational way of helping them see what the data is saying. The "conversational" bit is where the context is added in, which a dashboard packed with charts doesn't quite deliver.
We believe that leaders should not burn countless hours wrangling the data, the data should adapt itself as per the leaders' needs. This is where Axon acts like a radar for the engineering leaders, identifying bottlenecks and problems early.
Unified intelligence, take the guesswork out of the equation
Axon opens up data silos and connects the dots to show a holistic picture. Leaders can now link their organizational goals with actual work items like Epics or Marketing Campaigns or Revenue markers (like ARR). Axon also enables tracking KPIs at the organization or team level - making it easier to track things objectively, with tailored parameters.
For Engineering Leaders, Axon unifies the git and project tracking metrics to give a proper pulse of how things are progressing. It tracks leading metrics (e.g., Cycle Time, First Time to Engagement, High-Risk Pull Requests, Unplanned work trends, etc.) to generate warning signals predicting drop in quality, poor planning, potential team burnout, decreased throughput, etc. The leaders can take well-informed corrective actions before it is too late.
And yes - all this without asking the teams to change their existing processes!