- Technology and Infrastructure
- People and Workflow
- Content Input and Output
I think it's important to note that while we are approaching this from the perspective of learning it would be narrow-minded to believe that this is the only angle we should be looking at an ecosystem. If we are to truly build an environment for employees to live, grow, and develop their expertise, themselves, and the organization's goals we need to collaborate with the other groups within our organization that also share our common purpose. Here's my observations about the three perspectives above.
1. Technology and Infrastructure
Systems that track and reward employees should talk to each other where there is a need to consider the data flow a continuum for the workflow, employees and reporting, in order to provide meaningful stories and information for business planning. Examples of systems that should be connected could be those in human resources management (performance, talent management, recruiting, payroll, learning) and other systems that help to manage information like performance support systems, knowledge repositories and communication portals that connect employees to experts as needed.
These systems should record data in a way that data scientists can help to make meaningful and relevant stories for those who do not have data and analysis expertise. Notice I haven't said provide data in reporting; that is intentional. I don't think that an ecosystem should narrowly define information as 'reporting' because sometimes it isn't the data but the trends one needs to develop and observe. More than exact data, correlative information that can help tell the story of an employee's performance and development is often more relevant in helping them to progress and achieve their work goals.
Technology that should also be included might also include systems that are used to measure other human-interface business metrics. Examples of this might be elements of pipeline or portfolio management, error rates, billable hours, client satisfaction ratings, or complaints customers or peers.
2. People and Workflow
There is a storm brewing in learning and development that is miles away but still coming. I am referring to the blowback from the desire to measure every click, action and reference someone in a workplace makes to better themselves and their colleagues and the need to understand that an autonomous human being has to be able to operate without the constant observation of their supervisor or employer. As we move from having our X and Y generations occupy the bulk of employment demographics, we will see an increase in the desire for the next generation (what are they called, Z?) to preserve their privacy and autonomy. Trends are already being seen in the exit of this generation of people from places like Facebook and other data mining environments. While we may be wishing to record (for the benefit of employees and recognition) all instances of learning, it is called 'informal' for a reason! The inclusion of new learning recognition with standards that include xAPI and CMI5 will certainly help us track those learning opportunities and activities that we genuinely believe to be learning but can't be tracked in something like an LMS. These standards will also help to make the tracking of these activities more automated by recording the acquisition of a magazine article, a blog post, or a contribution to a discussion board directly to the system LRS as the employee does them, rather than having the employee formally track their activities in a portfolio or development plan. But what about genuinely informal learning and the genuine wish to not have everything tracked to allow for lateral thinking and innovation? Workflow and people in the ecosystem has to allow for some 'outside the walls' activities as well in order for the ecosystem to be voluntarily engaged.
When looking at how people work and interact with the world around them, it is very important to map actual workflow and groups who will interact in such a way that impacted groups (HR, technology, sales, C-Level) understand how their changes cause changes in other places in the workflow. (Sprout Labs has a great set of resources for this if you're interested, including a Learning Model Canvas)
3. Content Input & Output
Content into the ecosystem might come from learning and development course completions and assessments, from talent profiles and from mapping of role competencies to skills and tasks in a performance system. Content should also come anecdotally and informally from expert blogs and contributions, discussion boards to share best practice and centres of excellence (or competency) to provide standards and templates for exemplars of performance.
Content out of the ecosystem might be reporting and metrics from individual systems or might be data stories (aggregated and correlated information) in a dashboard or data visualization system.
What is important to understand is that whatever is contributed to the system (input) has to be of sufficient quality that it will be useful to measure and report on once people interact with the systems and workflow. Just like learning content, a snazzy display can't help really boring or inaccurate information - it remains inaccurate or boring but in a nice display.
I think this is the most important piece to consider when looking at an ecosystem - the inputs and output. It is important when starting to map the systems and workflows to understand where the data is coming from and to build good data going in. To this end, it makes it imperative that all of the stakeholders be considered and brought in to consult and collaborate before making the move in only one area (in this case, learning) to an ecosystem perspective.
