In a world where IT can often be a cost center, IT leaders have an opportunity to provide real value to their lines of business with People Analytics.
What is People Analytics?
Broadly, it is the use of big data and analytics to better understand your own employees. Over the last 10 years, marketing departments have utilized data-driven approaches to understand customers better and now those same data techniques can be applied to employees. This improved understanding of employees will span the entire employee lifecycle, from candidate sourcing and hiring, to onboarding, to ongoing employment and development, to eventual separation.
The CIO and IT department are uniquely positioned to answer questions about people in the enterprise since they have visibility into user behavior across different departments and geographies. We can expect a lot of innovation in the next several years as companies look for data-driven insights that give them competitive advantage finding, developing, and retaining top talent.
Questions IT can Uniquely Answer About Your People
One of the key questions that enterprises struggle with is employee engagement. Many studies have shown that higher employee engagement levels are strongly correlated with stronger performance and productivity, reduced risk of attrition, and overall increased happiness levels. Traditionally employee engagement is measured, if at all, via annual or semi-annual surveys where employees will self-report on how engaged they feel.
Analytics can bring a different approach to understanding employee engagement using data that comes from the communications and collaboration systems used in the enterprise. As people communicate and collaborate with each other, they leave digital breadcrumbs in the systems they are using.
By collecting, aggregating, and normalizing this person-to-person interaction data from systems such as PBXes, email and calendar, messaging, and web collaboration, a map of interactions across the enterprise can be created. This interaction map shows how each employee engaged with other employees, when, and how long they engaged. By looking at this interaction map we can empirically tell what the engagement levels are for our employees.
Creating this interaction map today is challenging since the interaction data is stored in multiple disparate systems in many cases. The good news is that this may become easier over time as the market trend is towards more consolidated communications platforms, in particular cloud-based platforms which provide multiple interaction types in the same platform.
Once this data is consolidated and aggregated, the enterprise interaction map provides insights around overall employee engagement levels and how they are trending. It also allows for the identification of outliers. People with extremely low engagement levels may be more likely to attrite, whereas people with extremely high engagement levels are likely to burn out. This will be very valuable for line of business leaders, as they have historically had no data-driven visibility into these aspects of their organizations.
In more advanced scenarios, the interactions between people in the enterprise can be modelled as a graph, much like a social network. Looking at the most central nodes in this graph will identify important people in the org. Analysis of our own data shows that there are often surprises when management looks at the list of people that are central in this graph. The graph will identify informal experts that many people rely on and who help boost the performance of the team even if they don’t have individual performance levels higher than their peers.
People analytics can answer questions beyond employee engagement. It can be used to predict sales performance. For example, we can combine historical sales bookings data with interaction data to model what interaction behaviors are correlated with top performance. This model can then be used to predict sales performance based on looking at present interaction patterns, and ultimately prescribe what sales people should be doing more of to maximize their productivity.
I believe this type of analytical prediction and prescription based on employee interaction data will drive a lot of productivity improvement in the future.
The Role of Privacy
By now you may be feeling slightly uncomfortable about this use of employee communications data to answer questions of engagement for particular people. Is this use of the data justified? Will our employees accept this use of communications data or will they feel that their privacy has been compromised? These are all valid questions, and they parallel many similar questions that have been asked by customers when providing personal data to enterprises.
Many of the same points that inform a customer-facing data privacy strategy need to apply internally to your own workforce. Enterprises need to have a policy which clearly states how employee interaction data will be used and under what conditions the data will be disclosed within or outside the organization. For organizations highly sensitive to using employee interaction data in this way, an alternate approach is to anonymize the interaction data. Aggregated anonymous data can still be used to answer questions about overall engagement while preserving individual employee data confidentiality.
IT Holds the Key
People analytics is going to change the way companies understand their employees. CIOs are sitting on a treasure trove of employee interaction data that is too often locked away in separate email, calendar, PBX, messaging, and web collaboration systems. Consolidating and aggregating this interaction data to understand overall employee engagement is only a starting point for a whole class of business insights that are possible.
Future insights will combine business KPI data with interaction data to model what employee interaction patterns result in the best outcomes.
(About the author: Derek Yoo is chief technology officer at Fuze)
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