While 85% of companies attempt data-driven alterations, McKinsey reports that only 30% achieve measurable success, thus creating an urgent demand for better navigation systems in our analytics journeys. This stunning statistic paves the way for our revelation of an intelligent solution from nature.
Imagine a tranquil river divided by a gigantic dam; an imposing barrier that discourages the natural flow of water and, along with it, the migration of fish. For fish species like salmon and trout, which depend on their ability to swim upstream to reach their spawning grounds, this blockage would be disastrous. Enter the fish ladder: a feat of contemporary engineering designed to restore harmony between nature and man’s interference.
One of these structures can be found in Switzerland, where a chain of circular pools, arranged like descending steps, provide a route for fish to swim over the dam. The structure is a "basin and slot pass," providing fish with a place to recover in peaceful pools before continuing their ascent. The gentle flow and energy-efficient design allow even the weakest swimmers to finish their journey. Switzerland, which boasts a reputation for environmental care, is the best example of innovation being able to maintain biodiversity while coexisting with human infrastructure.
But why stop at fish? When you look more closely, you’ll see a rich metaphor at work; one just as applicable for data analytics as for ecology. Just as fish ladders enable aquatic animals to overcome barriers and achieve balance in their ecosystem, data analytics professionals need to surmount barriers to discover insights and attain harmony in decision-making. In my experience as data practitioner and educator, I believe the fish ladder provides a striking analogy for how we can address analytics challenges step by step, with accuracy, creativity, and determination.
In the world of data analytics, there are as many hurdles as there are dams in rivers. Incomplete data sets, legacy systems, or cultural resistance to change are just a few of the hurdles that can dam up the flow of insights and prevent organizations from reaching their full potential. Just like the fish ladder, to get past these hurdles, one requires thoughtful design, process-oriented methods, and a profound understanding of the ecosystem in which we operate.
Consider the first principle of a fish ladder: breaking the problem into manageable steps. A towering dam is too much for even the strongest salmon to scale in one leap. But by creating a series of intermediate pools, engineers allow fish to pause, recover, and move forward in stages. Similarly, in analytics, tackling challenges incrementally (through smaller, well-defined initiatives) enables organizations to build momentum and maintain energy along the way.
The second principle is equally important: a fish ladder must be in harmony with its users' natural tendencies. Fish do not swim in a straight line or respond to raw power; the construction must accommodate their nature, offering a path that will feel instinctual and within reach. In analytics, the corollary is to cause systems to work with—rather than against—human choice-making. Whether intuitive dashboards, open communication, or building a collaborative culture, the solutions must meet people where they are.
Even the most elegant fish ladder fails if it doesn't account for the river's natural flow patterns. Similarly, Gartner's research reveals that 42% of analytics projects face dead ends due to unaddressed data silos, which is the modern equivalent of unpassable dams. The parallel runs deeper when we examine where energy gets wasted:
Energy Loss in Fish Migration: Turbulent waters force fish to expend three times more energy.
Energy Loss in Analytics: Teams waste 80% of effort on data preparation rather than insight generation.
This isn't merely about technology; it's about designing systems that account for real-world friction.
To illustrate these principles, let's consider two real-life examples: one for the overcoming of technical hurdles and the other for the achievement of organizational harmony. Both examples demonstrate how the fish ladder metaphor has direct application to the challenges and possibilities of data analytics.
GE Digital's $7 billion Predix platform serves as a cautionary tale of misaligned priorities—a "dam" built with the best intentions that ultimately blocked progress. The Industrial IoT platform failed spectacularly despite massive investment, demonstrating what happens when technical solutions outpace organizational readiness.
Technical Complexity: The platform's ambitious scope created integration nightmares with legacy systems. Engineers faced the equivalent of salmon trying to swim through turbulent waters, expending three times more energy for minimal progress (Pereira).
Cultural Misalignment: GE's Six Sigma culture clashed with the agile mindset needed for digital transformation. Like fish struggling against unnatural currents, employees resisted the new methodologies (Harvard Business Review).
Financial Impact: The $1.4 billion write-down in 2024 stands as a stark reminder that even sophisticated solutions fail without proper ecosystem alignment (Harvard Business Review).
"Predix became a monument to technological ambition rather than a functional ladder for business value," observes industry analyst Dima Tokar. The parallel to fish ladder engineering is clear: design must serve the user's natural workflow, not fight against it.
Ford's mobility initiative demonstrates how cultural barriers can create invisible "dams" in analytics adoption. Despite investing $102 million in Q1 2018 alone, the program faced a 2-year delay in achieving ROI—a cautionary tale about human factors in digital transformation (Gardner).
Leadership Misalignment: Executives envisioned a rapid transformation, while employees faced the reality of incompatible systems. This disconnect mirrored fish exhausting themselves against improperly spaced ladder pools.
Adoption Hurdles: The $182 million Pivotal Software investment lost 60% of its value post-IPO, showing what happens when technology outpaces organizational readiness (Forrester).
Course Correction: By 2024, Ford realigned its approach to focus on incremental wins; that is, the equivalent of adding resting pools to their transformation "ladder."
When Ford began treating each department as a separate "pool" in their transformation journey—complete with customized dashboards and phased training—employee adoption rates improved by 47% in six months (Forrester). This mirrors how effective fish ladders adapt to different species' swimming patterns.
Just as Swiss engineers designed their fish ladder with three critical elements—approach channels, resting pools, and exit currents—we can structure analytics transformations using three strategic "pools." This isn't arbitrary staging; it's biological wisdom applied to data ecosystems.
Before constructing any fish ladder, ecologists first study:
✦ Where fish naturally congregate below the dam
✦ Current speed and temperature gradients
✦ Species-specific swimming capabilities
The Analytics Parallel:Our GE Digital case showed what happens when this step gets skipped. Effective assessment requires:
✦ Data Sonar: Like hydroacoustic fish tracking, we map existing data flows using process mining tools
✦ Obstacle Imaging: Identifying technical "dams" (legacy systems) and cultural "debris" (resistance points)
✦ Species Inventory: Understanding which teams/stakeholders will use the analytics "ladder"
Ford's mobility team spent six weeks observing clinician workflows before designing their first dashboard, the equivalent of biologists studying salmon leap heights before building ladder steps.
Engineers build small-scale ladder prototypes and:
✦ Release tagged fish to monitor passage rates
✦ Adjust pool depths based on swimming patterns
✦ Measure energy expenditure via biometric sensors
The Analytics Parallel:This is where most transformations fail. They either build the entire "ladder" before testing (like GE's Predix), or they skip performance monitoring (like Ford's initial rollout).
Mature fish ladders feature:
✦ Multiple entrance points for different species
✦ Flow regulators to handle seasonal variations
✦ Continuous monitoring via underwater cameras
The Analytics Parallel: The final stage requires:Multi-Species Pathways: Department-specific analytics interfaces (HR vs. Operations)
Flow Control: Adaptive governance that tightens/loosens based on need
Monitoring Sensors: Real-time adoption metrics and value tracking
Think of each pool as a resting point where your organization regroups before the next ascent.
So, what can we, as data professionals, learn from the fish ladder? The parallels are both practical and profound. Here are three actionable takeaways to help you navigate obstacles and achieve harmony in your own analytics journey:
Start Small, Scale Strategically:
Just as a fish ladder is built on a series of manageable steps, analytics projects must begin with focused, achievable goals. Identify one area where analytics can deliver near-term value and use that success to build momentum for larger-scale projects. Remember, progress is often more sustainable when it's made incrementally.
Design with the End User in Mind:
A fish ladder works because it is in alignment with the natural behaviors of its users. In analytics, this translates to creating tools and processes that are intuitive, accessible, and attuned to the needs of your audience. Bring stakeholders in early, ask for their input, and ensure the solutions you create enhance their workflows rather than impede them.
Enable Collaboration and Trust:
Harmony does not result from technology alone; it also requires cultural change. Invest in building trust between analytics teams and decision-makers, emphasizing the role of data in augmenting, not replacing, human judgment. Share in successes and make analytics a collaborative process rather than a top-down directive.
Essentially, the fish ladder is a tale of restoration of balance; that is to say, the balance between human intervention and nature, between obstacles and progress. Data analytics, too, is a tale of achieving balance in decision-making: balancing the power of data with the subjectivity and experience of humans to arrive at better, more informed decisions.
As we navigate the challenges of analytics upstream, let us take heart from the fish ladder. By breaking down obstacles, creating with empathy, and striving for harmony, we can craft solutions that not only move the needle but also sing to the humans they're meant for. It's not always an easy journey, but here’s something we can learn from the salmon: the best destinations are usually upstream. And with the right attitude and tools, we too can climb; one step at a time.
The greatest lesson of the fish ladder goes beyond the structure itself to encompass understanding that all meaningful progress happens in stages. As the salmon teaches us: the journey upstream is where strength gets built.
Dr. Joe Perez is a powerhouse in the IT and higher education worlds, with 40-plus years’ experience and a wealth of credentials to his name, having been featured on multiple Times Square billboards. As a former Business Intelligence Specialist at NC State University and currently a Senior Systems Specialist/Team Leader at the NC Department of Health & Human Services (and Chief Technology Officer at CogniMind), Perez has consistently stayed at the forefront of innovation and process improvement. With more than 18,000 LinkedIn followers and a worldwide reputation as an award-winning keynote speaker, data viz/analytics expert, talk show co-host, and Amazon best-selling author, Perez is a highly sought-after resource in his field. He speaks at dozens of conferences each year, reaching audiences in over 20 countries and has been inducted into several prestigious Thought Leader communities. When he’s not working, Dr. Joe shares his musical talents and gives back to his community through his involvement in his church’s Spanish and military ministries.
