Managing Where the Light Isn’t Good
Anyone who manages people knows that this is a vastly under appreciated skill. Effective managers facilitate and catalyze execution by ensuring resources are aligned to priorities; balancing how they're utilized; and removing obstacles that hinder execution. The best managers assemble high-performing teams who generate brilliant results and make it all seem effortless. For these teams, work is fun and rewarding and each new day is a welcomed challenge.
Ineffective managers are markedly different and so are their results.
What makes the difference? Many books and PhD dissertations have tackled this question and I won't attempt to take it on with that level of rigor. But I will offer a perspective based on what we've seen inside of today's software development organizations, which I believe represent an ideal laboratory for studying management practices. Software development is a perfect example of a process "where the light isn't good" -- it's complex, dynamic, often ambiguous, and dependent upon the superhuman performance of relatively autonomous individuals. It's controlled chaos.
For software development teams, the key difference in management success is measurement.
Simply put, those who manage by the seat of their pants -- by instinct and qualitative assessment, rather than proof -- tend to run into trouble. You know these managers when you see them: They're rushed, frenetic and spinning in a perpetual state of crisis. They're always unthinkably "busy." Why? Because they're trying to manage a complex, interdependent and dynamic process using outmoded and ineffective practices -- practices that never worked on their best day.
According to a report by Forrester Research, manually plugging data into traditional project management tools is the common practice today. Forrester refers to this as a "state of the art 40-year old process." Albert Einstein once famously noted that the definition of insanity is repeating the same behavior and expecting a different outcome. I'll stop there, lest I implicate anyone!
Aside from depending on a toolset unfit for its function, today's managers face the additional challenge of managing teams that are dispersed from hither to yon. Despite advancements in communication and collaboration tools, the geographic distribution of teams through offshoring and outsourcing renders managers effectively blind. Tom Koulopoulos, founder of Delphi Group and author of the book Smartsourcing, uses analogy to capture the new reality of distributed work: "Companies whose instincts have gone stale are like patients with local anesthesia let free to wander the world. They are rational, coherent and aware of their predicament, yet numb. They can no longer sense the world around them."
In this new world, instincts are no longer sufficient to get the job done -- measurement is required.
One of the key requirements to managing where the light isn't good is measuring how time is being spent. This enables you to analyze and act on the "investment profile" of your teams -- are they aligned to the right priorities, activities, best practices? How is their performance and productivity? Are there environmental factors that are getting in the way?
There are several ways you can measure where time is being spent:
- Ask your team to tell you -- but this is time consuming and they're pretty busy; and you know the data recorded in time sheets and PM tools is often little more than Friday afternoon conjecture
- Walk around and ask -- but that is intrusive and jarring to your team (believe me, they don't like it), and it's simply impossible when your team is located ten time zones away
- Automate the collection of activity-based data -- applying the "best-use" principle* of automation to collect data about how and where time is being spent across your teams
Of course the last option is clearly the rational choice. Applying automation to the process of data collection creates the visibility you need to more effectively manage your distributed projects. It creates light where the light has never been good by revealing the investment profile of your projects and the development process as it's executed. It empowers managers with the data they need to effectively lead.
Imagine you're based in Boston and responsible for a team of developers in Bangalore. Not only are you nearly 8000 miles apart, but a 10+ hour time difference means that you have no overlapping business hours. I suspect this is what Koulopoulos means in his poetic illustration of instincts gone stale. You simply can't know where time is being spent -- it's largely unknowable.
This is the ideal scenario for automated collection of activity-based data. Rather than guessing where time was spent, you arrive at work with an accurate and up-to-date picture of where investments were made while you were sleeping. It gives you the power to know -- which empowers you to effectively manage where the light isn't good.
[* The best-use principle suggests applying automation to tasks and activities that are more effectively and efficiently handled programmatically, rather than by people.]
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