The Skill Graph is a Datagraph

Steven Forth is co-founder and managing partner at Ibbaka. See his skill profile here.

In the May-June issue of the Harvard Business Review Vijay Govindarajan and Venkat Venkatraman have published an important article ‘The Next Great Digital Advantage.’ The article is about datagraphs and how they have transformed the eCommerce business and how they will go on to support changes in how we do business more generally.

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One of the most important of these data graphs is the skill graph, the data model in which Ibbaka builds its skill management solutions. (See Core Concepts: Skill Graph).

What is a data graph?

Govindarajan and Venkatraman introduce the datagraph as follows:

The datagraph concept is inspired by social network and graph theory, wherein a social graph is defined as a representation of the interconnections among individuals, depicted as nodes, and the relationships among them—with friends, colleagues, supervisors, and so on—represented as links. The concept derives from the work of the social psychologist Stanley Milgram, and over the past two decades, it has provided a useful lens for analyzing the structure and dynamics of organizations, industries, markets, and societies.

Two of the key concepts behind datagraphs are ‘Data Network Effects’ and that datagrpahs represent ‘data in motion.’

Data Network Effects

The power of the datagraph does not come from any one piece of data, but rather how data gets connected. To take an example from Amazon’s graph, knowing that [Steven Forth] [Purchased] [Work Without Jobs: How to Reboot Your Organization’s Operating System][by][Ravin Jesuthasan][Co Author][John Boudreau] and that [Steven Forth] [Rated] [Bernoulli’s Fallacy: Statistical Illogic and the Crisis of Modern Science][By][Aubrey Clayton] tells you a lot more about [Steven Forth] than either of these facts alone. Connecting data is where datagraphs get their power. They do this by applying techniques from the mathematical discipline of graph theory. This provides a powerful set of tools to understand connections and the overall properties of the connections.

Govindarajan and Venkatraman don’t stop there. The network effects are in large part created by the ways in which people interact with the system, with each interaction creating both a new node (data point) and set of edges connecting that data point to others.

This is very much how the Ibbaka skill graph works. One of our core hypotheses is that the connections between skills are more important than any one skill. These include the connections between skills (what skills are used together, what skills specialize a more general skill, what skills connect two different skill clusters). Skills also connect people. When I claim a skill I create a connection with everyone else who has that skill. When I connect a skill to a project I am working many new connections are created. All of those edges are themselves important connections that can be followed and used for inference.

Data in Motion

Another core concept for datagraphs is that the data is always in motion.

Datagraphs are not static; they do not reflect information at a snapshot in time. They are dynamic, reflecting what data scientists refer to as data in motion. That’s partly why it is impossible to manually draw a datagraph. Technology is needed to gather and interpret in real time the data on the millions of units of a company’s products that consumers worldwide may be engaging with at any given moment.

Change and flow are central to datagraphs. That two skills are connected is interesting. That someone has connected two skills that have not been connected before is a leading indicator that innovation is coming. The same is true for the value graph (the other datagraph we have begun to build at Ibbaka). If a solution connects two value drivers that are not normally connected it may be able to solve new problems.

In this table, Govindarajan and Venkatraman and set out some of the key differences between older models and what the datagraph (and the skill graph and the value graph) make possible.

I want to highlight the final point in this table.

Firms solve customer problems with unique solutions derived from collective learning.

What sort of organization does the skill graph enable?

As it happened I read the Govindarajan and Venkatraman article just as I started to read an important new book on organizational design. Work Without Jobs: How to Reboot Your Organization’s Work Operating System by Ravin Jesuthasan and John Boudreau. This was a fortunate connection (a link in my knowledge graph) as it is datagraphs that make possible the type of adaptive organization that Jesuthasan and Boudreau describe. You can’t do it with a conventional HRIS or Talent Management System.

Remember the old joke about ERP (Enterprise Resource Planning) systems? “An ERP takes your business processes and pours concrete over them. “ The same is true of the current generation of HRIS, Talent Management System and yes even your LMS (Learning Management System) and LXP (Learning Experience Platform). They lock you into an organizational model that is often too brittle to be resilient and too structured to adapt.

The main theme in Work Without Jobs is that we need to deconstruct jobs. Jobs is too bulky and formal a construct for how we work today. Jesuthasan and Boudreau advocate 'seeing the whole person through skills/capabilities. At Ibbaka we share this focus on skills (hence the skill graph) and have found that we need a couple of mediating concepts to help organize how we work. The two most important mediating structures at Ibbaka are Roles and Activities.

Roles come in four flavours:

Job Roles - jobs are a bundle of different roles, some roles can be jobs in their own right or roles within another job. Project Manager is a good examples of this. Many organizations have a formal Job of Project Manager. Many other jobs include the Role of Project Manager.

Team Roles - as more an more work is done on teams, the many different roles we play on teams become central to our work

Ad-Hoc Roles - all those other roles you play in your organization that are not a formal part of your job or performed on a team, ‘I am doing this off the side of my desk.’ A lot of innovation starts with ad-hoc roles mixed with curiosity.

Community Roles - we are more than the work we do and the roles we play in our families and communities contribute to our skills and our ability to work effectively with other people.

The other construct we are finding increasingly useful is ‘activities.’ You can see that in our own roles model for the work we do in pricing and customer value management.

Of course there are other approaches.

One can connect skills to goals and ask ‘What skills are needed to achieve this goal?’ There is also an interest in competencies, “What skills (or Knowledge, Skills and Attitudes) are part of this competency?” Skills are often granular, they need to be in order to be specific to actual work, so one needs a larger construct to organize them. See Generic skills or granular skills in role coverage and skill gap analysis.

Another theme in Work Without Jobs is that one needs to be perpetually reinventing deconstructed work. This links back to data in motion. A good skill graph is always changing as people add skills, find new ways to use them, start to work with different people, on new projects.

The skill graph is the nervous system of the work operating system. It will be one of the most important datagraphs in the future of work.