The world of human performance data and technology is a massive puzzle, with many pieces that we try to fit together comprehensively. Different types of data and technologies, even similar technologies from different vendors, all offer additional information and solutions, with each organization striving to find how to best fit the puzzle pieces together.
Regardless of the puzzle pieces themselves (data, tech, or vendors), the most essential aspect of this puzzle is how well things are connected.
We often hear terms like "aggregation," "integration," and "interoperability," but what do they really mean, and how do they differ?
You're collecting information from various sources and putting it in one place. This is useful because you can see everything in one spot… but the data isn't actively talking to each other or doing much else. This is where we have all our puzzle pieces in one place, flipped over to the correct side, allowing us to organize them by color or shade.
Example: An athlete management system compiles data on fitness metrics, medical records, and performance history in one repository. It offers an overall view of health and readiness but doesn't facilitate active data exchange.
Many different human performance point solutions bundle human data measurement hardware and native software together with this level of integration. This allows us to connect some of the puzzle pieces together, but usually only in one, often the most obvious, part of the puzzle. Each part is still disparate and disconnected, though the overall picture may be becoming more clear.
Example: During a training session, the GPS tracking devices transmit data to a centralized software. Professionals can access this system to review metrics related to load, velocity, accelerations, and other relevant GPS metrics. While the technology may facilitate real-time tracking and alerts, the integration only focuses on the data from the specific device.
To complete the puzzle, we must connect the parts (surface-level integrations) into a cohesive whole by filling in the spaces between. Technology supporting interoperability acts as the connective tissue to complete the puzzle.
Example: Load and exercise data from training environments, health and medical data from sports medicine, and relevant performance data can be seamlessly shared between leaders, coaches, medical staff, and individuals. Stakeholders can zoom in and zoom out on different areas, keeping context intact. Information flows automatically to ensure the entire team is on the same page and supports interdisciplinary real-time decision-making.
Though the puzzle analogy is flawed and overly simplistic, it helps to clearly differentiate between having some surface-level integrations and a deeper level of connectedness, like interoperability. The gaps between disparate solutions often cause costly lags in communication and misalignment, requiring (also costly) consistent manual effort to ensure organizations can still "see the forest through the trees."
There is nothing wrong with aggregation or surface-level integrations. Still, it is crucial to understand that there are levels of connectedness to aspire towards. While deeper levels require a more systematic approach, each step can exponentially improve your organization's ability to support human performance holistically and scalably.
When parts of the whole are disparate, it is easy to zoom in on specific components and put in immense effort with little payoff. Being connected improves an organization's ability to identify where more investment may be needed and where things are "good enough."
Cleaning and preprocessing data, creating and sharing reports, alerting, and (some) communicating can be automated, significantly decreasing manual efforts. These things make supporting human performance optimization less limited by the bandwidth of individual contributors wearing too many hats.
So, when you hear terms like "connected data" and "interoperability," remember it's all about making technology and data work together in real-world environments.