How to Manage your Agile Team in the Age of Big Data

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How to Manage your Agile Team in the Age of Big Data

Jason WidesChief Solution Architect at SeaLights | October 10, 2018

Organizations worldwide continue to struggle to adapt to the tumultuous and unpredictable nature of today’s business, economic, and technological environments. The age of big data creates new challenges. To combat this, many companies adopted the agile mindset and practices to enhance their service and product delivery. Agile offers well-structured frameworks and well-tested practices that when implemented correctly, significantly improves customers’ satisfaction, as well as the quality and speed of service delivery.

However, most of these organizations are discovering that agile’s focus on team delivery alone isn’t enough. Although a large number of companies are well acquainted with the efficient implementation and execution of agile team delivery, they are sorely lacking in even more important areas, such as the requisite level of skills and practices required at the management level that will enable the creation of a truly agile environment organization-wide.

This blog presents to you the principles of agile management and how you can develop the mindset and capabilities of an agile leader.

What are Agile Methods?

Agile is a mindset; a set of principles embodied and inseparable from an organization’s culture, which enables the organization to construct processes by anticipating and reacting to change.

Agile methods are characterized by high levels of collaboration and short and continuously incremental development processes. These methods place a lot of focus on building working software as early as possible.

Agile Software Development

The term “Agile Programming” or more commonly “Agile Software Development” was coined in 2001 during a forum organized by proponents of Crystal, Adaptive Software Development, DSDM, SCRUM, XP, and other programming methods. The meeting also resulted in the birth of the Agile Manifesto, a document containing the guiding principles of agile programming.

The four core values of agile software development as stated by the Agile Manifesto are:

  • Responding to change over following a plan
  • Customer collaboration over contract negotiation
  • Working software over comprehensive documentation
  • Individuals and interactions over processes and tools

Defining Agile Leadership

Traditionally, organizations value leadership attributes and qualities that are easy to track through the linear progression of well-defined parameters and whose impact is immediately visible, quantifiable, and measurable. However, the paradigm shift towards agile methods has disrupted this, requiring leaders to learn new skills such as flexibility, learning agility, emotional intelligence, and the often overlooked and unappreciated ability to not only recover but capitalize from failure.

Understanding Agile Management in Software Engineering/Development Environments

Agile methods were introduced into the software development space to shore up the limitations of the waterfall lifecycle, thus transforming and optimizing the production levels of software development teams and how they collaborated on projects.

But the advent and subsequent adoption of agile methods introduced a wrinkle to the mix, upsetting the operational methods and traditional leadership pattern of software engineering managers. The upper echelons of management were faced with a new problem – how were they to effectively manage their team members in an agile environment?

The waterfall concept is a sequential and plan-driven development concept, requiring managers with a command-and-control approach. These managers had problem-solving skills, and most importantly “could get the job done.” However, this sequential approach to management is incapable of handling and managing agile environments, as well as managing big data, which require a more responsive and flexible approach due to the continuously evolving, and fast-paced nature of today’s business environment. As such, a more collaborative and facilitative management and leadership approach is needed.

Agile Leadership Model

Agile leadership requires managers to transition from:

  • Managing for results to designing and creating truly agile environments
  • A predict-and-plan approach to a sense-and-respond mentality
  • Directive control & intervention to conditioning and catalyzing the broader organization

Software engineering managers must dedicate themselves to improving not just their development teams but the organization in its entirety. As truly agile leaders, they must be champions of change, continuously evolving themselves as situations emerge, and committing to the cultivation of passionate and empowered employees and teams. By so doing, they create an organizational culture that is focused on optimizing and improving the entire customer value chain, thus making their companies truly agile.

The Agile Leader’s Compass/Roadmap

Maintaining and keeping the vision of a software development project in view is a critical area of focus for management. Since agile programming calls for frequent release of project deliverables to clients, dev teams tend to concentrate exclusively on activities required to achieve the timely completion of said deliverables. However, the continuously changing nature of clients’ requirements may make dev teams lose sight of the overall project vision.

It is the responsibility of agile leaders to maintain an enterprise-level view of a client’s requirements along with its scope, dependencies, and interlocks and continuously reinforce these parameters with each member of the dev team. There is also a need for iterative risk management since agile environments are inherently dicier than their more traditional counterparts. This calls for regular checkpoints to identify new risks and review mitigation strategies.

Furthermore, software managers should be able to handle and resolve each situation that presents itself in an agile environment. As agile leaders, they must learn to dynamically shift into character, stepping into the specific role demanded by each situation, and resolve using practices that align with both the project and the clients’ needs, as well as the overall organizational culture.

Quality Intelligence Technology: The Key to Agile Leadership

Just as software dev teams need a set of supporting practices and structures to sustain and stimulate their transformation into becoming agile practitioners, so too does the Agile leader need a supporting framework.

This blog presents the principles of agile leadership and offers a framework for managing and leading software development teams into the age of agile programming. Implementing these practices will set your organization up for a sustainable and transformative agile movement.

However, leading agile teams especially in the data-driven age requires a bit more than the above principles. It is ironic how software engineering teams develop solutions that help enterprise clients keep track of key metrics that affect their efficiency, effectiveness, velocity, and production capacity—without using similar solutions to track their own productivity.

The measurement of agile process metrics such as open/close rates, cycle time, lead time, and team velocity can help agile leaders gain valuable insights into critical factors affecting teams and help them make informed decisions about process improvement. As such, agile leaders who want to leverage this data to improve the velocity of their development teams must use the right Quality Intelligence technology platform.

Quality Intelligence technology facilitates the collation and analysis of data from multiple sources thus providing agile software development teams and managers with sufficient visibility and insight into factors affecting the efficiency, quality, and velocity of their software engineering processes and deliverables.

In addition to incorporating the principles of agile leadership, software engineering managers should use the right tools to help them effectively lead their teams in today’s data-driven age.