A Nimble organization makes experiments but pivots quickly
The International Institute of Business Analysis (IIBA) introduced us to the concept of a nimble organization: an organization’s capability to sense and respond to change. Inspired by the webinar series about nimbleness from The Brazilian BA (Fabricio Laguna), I believe there is room for knowledge about how an experimentation mindset is always present in a nimble organization and how to make decisions about those experiments.
Nimble organizations navigate through uncertainty (in this “VUCA world” — Volatility, Uncertainty, Complexity and Ambiguity) and in a flow paced. This means that they have a steady pace in their day-to-day routines, but are prepared to pivot once change happens.
What is a Nimble organization?
In 2023, the IIBA published a research report about how organizations capable of being “Nimble” have a much higher performance than their peers, called “Being Nimble: The Scalable Capability for an Organization to Sense and Respond to Change” (you can find it here). The IIBA describes the term “nimble” as a business capability, in which the organization aims to navigate in uncertainty, without necessarily being related to a specific practice or methodology (such as agile). The report presents 3 imperatives for an organization to be “nimble”: Addressing Stakeholder Expectations by being customer-value driven; 2) Being a Data-Driven Organization and using data to improve decision-making or automate processes; and, 3) Digitally Transforming to modernize technology operating models.
The types of inputs that BAs can provide have different usage perspectives depending on the Agile Planning Horizons. They were originally defined in the Agile Extension of the BABoK®: Strategy, Initiative, and Delivery. The latter is the horizon where BAs work with the team with very fine-grained information in a very short span. As the work goes from the Delivery to the Initiative and then at the Strategy horizons, both the granularity of the information and time grow. The scope becomes wider.
- The Strategy Horizon: refers to the decisions that impact the entire organization, with a focus on short-term goals, initiatives, and risks that align with organizational strategy, and articulate the problems that must be understood to make strategic decisions
- The Initiative Horizon: refers to decisions that impact a particular goal, initiative, or team with a focus on solution options, features, priorities, and lifespan.
- The Delivery Horizon: refers to decisions made about how to best break down work, how to deliver and test the value the team is creating, and how to learn from the work the team is doing.
Between each horizon, there are upstream and downstream feedback loops, which means that the outcomes within the three horizons are in constant movement.
They have an experimentation mindset
To continue to innovate and lead changes, nimble organizations must be aware that experimenting will come with risks. We look at the 4 risks presented by Marty Cagan in his book “Inspired”:
- Value risk (whether customers will buy it or users will choose to use it)
- Usability risk (whether users can figure out how to use it)
- Feasibility risk (whether our engineers can build what we need with the time, skills and technology we have)
- business viability risk (whether this solution also works for the various aspects of our business)
For each risk, you may tackle it by applying different product discovery techniques. For instance, you can use a proof of concept to assess the technical feasibility. You can use prototypes to check the usability of a new product (Design Sprints is a good example). MVPs have the purpose to fast checking whether customers see value in a new product. Lastly, techniques like A/B testing or a “fake door” quickly allow organizations to assess business viability with little effort associated.
Of course, these are just examples of techniques applicable for tackling each kind of risk, but it is possible to use a technique for another kind of risk, or use a group of techniques for one risk, or even the same technique for different risks. What matters is that neither of these risks should be neglected.
How to prioritize experiments
Some techniques allow nimble organizations to prioritize which experiment could they pursue, either in terms of value for customers as well as the associated risks.
Opportunity solution trees are a visualization of potential solutions to a customer problem. They involve breaking down the problem into smaller opportunities, generating multiple solutions for each opportunity, and then evaluating and selecting the most promising solution.
The model of the opportunity solution tree also addresses prioritization. Your top priorities concerning opportunities range from the left side to the right side. Thus, the opportunity(ies) to address within the experiment are placed on the left side.
The decision as to which opportunity to address first may combine opportunity solution trees with assumption mapping. Assumptions Mapping is a team exercise where desirability, viability, and feasibility hypotheses are made explicit and prioritized in terms of importance and evidence.
List all of your assumptions. we recommend that teams write these down as best they can using the “We believe that…” format (similar to the “How might we” from the Design Sprints). This format helps you shift mentally to the idea of testing. The idea that you might be wrong in your beliefs.
We use the labels of “have evidence” and “no evidence”. It’s not about who is the loudest or who gets paid the most. It’s about having observable evidence, qualitative or quantitative, to support your hypothesis. On the y-axis, we use the labels of “important” and “unimportant”. not everything is the most critical. By asking yourself “which hypothesis, if proven wrong will cause our business idea to fail” you’ll be able to determine which are the most important.
They gather data
Once the experimentation is scoped, prioritized and built, nimbleness is about quickly validating if the experiment provided the expected feedback or if a pivot is necessary as quickly as possible. For this task, nimble organizations must be backed up with data for such decision-making, rather than hunches or guesses.
Although surveys are a common research technique due to their ability to handle big datasets, they aren’t the best suited for validating the experiments. Heavily because it’s easy to write questions in a survey even just a little biased, and because answers are always impersonal.
Conducting customer interviews gives feedback with an in-person approach. Techniques like “continuous discovery habits” and “The Mom Test” advocate stakeholder interviews but with a different structure. The main shift in doing interviews is that questions don’t focus on what customers want. Rather, questions should focus on their past experiences to discover an opportunity or their feedback about a prototype, MVP, etc. It should be noticed also that this data relates to the Initiative Horizon.
Thus, nimble organizations also monitor data regarding the Strategic Horizon. It requires that each experiment is linked to a business objective, a business outcome, or an OKR, for example. So, the idea is to measure the outcomes related to the experiment in question and validate if the outcome was met or not.
In the delivery horizon, data will commonly refer to technical feasibility. This data will come from a delivery team’s day-to-day and the tests performed during their iterations (when working in an agile way).
In conclusion, there are many ways to support experimentation required for an organization to navigate through complexity and uncertainty. These organizations, that aim to be nimble, should have in mind the risks to tackle during experiments (Value risk , Usability risk , Feasibility risk, and business viability risk) framed together with the 3 agile analysis horizons (strategic, initiative and delivery).
Let’s not forget the feedback present between the horizons. Between Strategic and Initiative, the business outcomes to achieve have experiments associated with them, which are then under the discovery process to determine the technique(s) to perform the experiment. Between the Initiative and Delivery, the feedback relates to the scope of the experiment (prototype, MVP, or other) and the actual build of it.
If you want to know more about the Nimble webinar series from The Brazilian BA, you can find them here.
