This is the open culture session from the how module of the IRG100 program. Its central claim comes from the growth study: overperformers rewrite the culture script rather than accepting the one they have.
The route it proposes is experimentation, treated first as a mindset and then as a set of rituals, with two worked use cases and a template participants fill in.
Key findings
- The culture indexes point in opposite directions for the two groups. Innovation, change, and entrepreneurship indexes at 150 for overperformers against 83 for underperformers, while procedures, structure, and quality indexes at 133 for underperformers against 83 for overperformers.
- External connectivity, meaning an ecosystem of complementary partners, splits 67 percent against 39 percent, and diversity in strategic decision making 72 percent against 48 percent.
- The stakes are put in survival terms: in the last 15 years, 52 percent of the Fortune 500 companies have disappeared, while the fastest growing businesses are customer and experiment obsessed.
- Leaders and their teams do not see the same organization. In one poll, 82 percent of leaders say they enable a growth mindset all the time or often, against 14 percent of teams.
- The same gap shows up with customers. Eighty percent of companies say they deliver a superior experience, against 8 percent of customers, which the session flags as confirmation bias.
Mindset before tooling
The transformation pyramid puts mindset, tooling, process, and strategy on top of people, meaning culture change, talent, and capabilities. The point made is that the upper layers cannot be achieved without the base.
Fixed and growth mindset organizations behave differently. A fixed mindset organization values a small handful of star players and status, plans rigidly, and hires from outside on credentials and past accomplishments.
A growth mindset organization takes a more positive view of potential across a wider range of colleagues, runs a more innovative and risk-taking culture with less fear of uncertainty, and hires from within, valuing potential and a passion for learning.
Three misconceptions are corrected. Being open or positive is not the same as being a work in progress. Rewarding effort is not enough, because what should be rewarded is learning and progress. And it will not happen naturally: implementation, appropriate risk-taking, and psychological safety have to be organized.
The rituals
The first ritual is embracing false positives, reframing a failed test from something that did not work into something learned.
The rest are practical habits: cross functional teams, data-informed decisions, stakeholder alignment, psychological safety, rewarding learning, and dedicated learning time.
They extend into how work is run: qualitative and quantitative research, hypothesis and experiment ranking, sprint planning, visible Kanban boards, escalation paths, retrospectives, participatory budgeting, thinking in incremental bets, impediment removal, and documentation and sharing.
The leading indicators of adoption are being data-informed, continuous experimentation, an incremental approach, psychological safety where it is okay to fail, continuous learning, systems thinking, T-shaped people, and disruptive thinking.
The blockers come from a survey of 465 teams. They include failure being frowned upon, lack of time and capabilities, budget allocations, yearly planning, egos, a we have tried this already attitude, siloed data, and incentives set on velocity rather than KPI improvement.
Two use cases
The first case runs a series of experiments against a two to six month lead time. One experiment paired targeted traffic with a new landing page, new self service onboarding, and an email, and produced a hard conversion on the first day.
The cost was two days of one person’s time plus 130 euros, at 5 to 8 euros per lead, and the reported result was an 800 percent increase in leads and sales. The principle behind it is a limited blast radius.
The second case is about friction in opening a bank account, which the deck counts at more than 50 steps and over eight days, including freeing up 30 minutes plus travel, reporting at a desk, and waiting for verification.
The redesign changed when an account counts as open, removed the worst part of the traditional experience, allowed opening directly through the app, and made the card arrival memorable. Sign-ups rose 22 percent, at a cost of 97 days, 14 people, and 28,000 euros.
What participants take away
The experiment template forces a testable hypothesis: we believe that by doing X the outcome can be Y, with a description of the test, what will be measured in both quantitative and qualitative terms, and the minimum success criteria.
It also asks for start and end dates, estimated costs, and possible blockers, framed as working around challenges rather than being blocked by them. The single measure is described as the one metric that matters.
The capability map behind all of it covers data and analytics, growth and innovation, customer experience, and mindset, from data storytelling and machine learning to service design, behavioral science, and an experiment mindset.
The closing quote is the argument in one line: success is a function of how many experiments are run per year, month, week, and day, and being wrong might hurt a bit while being slow will kill you.
Scope and limitations
Several figures come from outside sources rather than the IRG study. The leader and team poll is credited to Growth Tribe with a base of 376, the blockers to a Growth Tribe survey of 465 teams, the delivery gap to Bain, and the experimenter index to Experimentation Works.
Source
This page summarises HOW Module Open Culture, by Institute for Real Growth, April 2021.