The label "Agile" is slapped onto many things nowadays without much detail regarding why and how. For example, how does one apply it to market research, which typically follows the scientific method and is more fitting with a traditional Waterfall approach? In this regard, time and resource utilization are often front-loaded—having a business question, conducting early research, hypothesis development, experiments, etc.—each building on the other.
On the other hand, Agile was born in software development, often to release a minimum viable product (MVP) while having technology, personnel, and processes in place to iterate on it efficiently. Can we transpose it to market research, i.e., how reliable is analyzing minimum viable data?
Waterfall or Agile?
Neither... at least not exclusively. This post describes a blueprint for building an asymmetric hybrid approach, i.e., a Rapid Iterative Insights System & Execution (RiiSE) program. I draw from 30 years of experience in market insights, data science, and innovations, as well as concepts validated by some of my favorite books, including Atomic Habits by James Clear, The 7 Habits of Highly Effective People by Stephen Covey, and The Innovator's Dilemma by Clayton Christensen.
STEP 1: Align organization goals with the RiiSE program.
"Goals are good for setting direction, but systems are best for making progress."– James Clear, Atomic Habits
The goal: A 1% improvement at every stage of the process that leads to exponential gains in outcomes. One of the tools for achieving this objective is the Work Breakdown Structure (WBS), or what I simply put as "Shrink the ask and optimize the task." With the WBS, we discretize each activity to determine its best- and worst-case duration, as well as its dependent activities within the overall workstream.
From the WBS, we identify the Critical Path or series of related activities having the most prolonged duration and multiple dependencies. Any improvements or obstacles within this path significantly impact the overall timing and program success. Hence, it warrants the lion's share of the focus and effort.
STEP 2: Shrink the ask and optimize the task.
The large circles in the model below represent the program pillars—80% of the effort can be applied to completing each milestone. While 20% of the "Holdout" actions still contribute to the desired outcomes, consider this the experimentation sandbox. These initiatives focus on technological and process innovations that could lead to workstream breakthroughs in quality, efficiencies, and scale. In the next step, I outline the thought process for identifying these holdout tasks via the Action Priority Matrix.
STEP 3: Identify the "holdout" activities for innovation.
The following Action Priority Matrix visualizes three habits from author and management guru Stephen Covey's "The 7 Habits of Highly Successful People." These include begin with the end in mind, put first things first, and synergize. By categorizing tasks within the matrix, we identify those most suitable for innovation and optimization while signifying the appropriate management strategy (manage, focus, avoid, or reduce). "Mission Critical" refers to those activities making up the critical path for which failure to accomplish within the planned schedule jeopardizes the chance for success. "Urgent/Not Urgent" represents the immediacy required to ascertain and implement actions to achieve the desired milestone.
The top right quadrant—Mission Critical and Not Urgent—is the ideal area to identify potential "holdout" tasks and solutions. They are essential for program success while having more time to plan, manage, and utilize. Examples in this quadrant may be exploratory data analysis and reporting. Since these deliverables are at the latter stage of the Critical Path, there is relatively more time to test-learn-iterate novel solutions. In this instance, we can harness non-traditional market research tools from data science and machine learning applications such as text analytics or programs such as Python or R to explore and analyze unstructured and structured survey data.
To optimize resources and scale implementation, these can be done via techniques such as Bootstrapping and Parallel Pathing, which I'll cover in more detail in Step 4.
STEP 4: Implement the vision.
There are multiple ways to achieve program milestones. The key is improving 1% at each link of the activity chain, which leads to a multiplier effect in productivity. Methods such as Bootstrapping and Parallel Pathing are essential for developing technological or process innovations, especially when grounded on the Proximity principle.
“The reason why it is so difficult for existing firms to capitalize on disruptive innovations is that their processes and their business model that make them good at the existing business actually make them bad at competing for the disruption.” – Clay Christensen, The Innovator's Dilemma
How do we operationalize?
Bootstrapping represents a resource cost optimization tactic. The closer activities are in a workstream, the more similar; leverage this. Consider data processing (DP) and exploratory data analysis (EDA)—tasks near and related to one another. In this instance, we can bootstrap a technological or human resource in data processing that also addresses EDA requirements. A personal example immediately coming to mind is our recent purchase of DP software which we easily re-purposed to help create reporting dashboard visualizations. Further adding value, the visualizations can be updated and socialized in near real-time, as well as downloaded to editable PowerPoint reports. Thus, for the incremental cost of a DP software license, we achieve exponential value by satisfying other requisite analyses and reporting based on proximity.
Parallel Pathing is a risk mitigation and dynamic knowledge strategy. It entails a mindset of experimentation—a trait essential to not succumbing to the "innovator's dilemma." Regardless of how well current processes are working, exploring other modes or methods for simultaneously completing certain tasks is vital. Doing so reduces the risk of over-reliance on a single approach and allows an organization to learn faster, thus developing competitive advantages through technological or process innovations.
The flowchart illustrates the RiiSE approach to the WBS mentioned earlier. Overlaying the techniques and concepts of Parallel Pathing, Bootstrapping, Proximity, and Critical Path ensures an asymmetric hybrid system optimized for Waterfall and Agile objectives while creating a scalable environment for learning and innovation.
Well, there you have it—the blueprint I used for developing a dynamic insights program. Like this innovation framework, I'm always looking for new ideas, so if you agree or disagree or have other thoughts, let me know. Happy innovating!
You can email me at rsilvestre@strategence-us.com.