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Company Analytics: The New Face of People Analytics
An in-depth look at analytical fields and how collaborative relationships are driving both internal and external interactions, and productive work.
What is Happening to People Analytics?
While I agree that there is a new and emerging product category, her picks are not exhaustive enough to cover what we have in mind. Yaroslavsky lists the core areas of "managers' analytics" as
- employee engagement (for HR),
- collaboration and mental health (for HR),
- employee experience & workforce planning (for HR), and
- productivity (for Managers).
The main gap in the proposed category definition is its total lack of interaction between the company's internal and external environments. Additionally, Yaroslavsky outlines only one narrow area of productivity analytical tools, which is meant to cover the wider needs of business and technology leaders based on her post.
People analytics examines the personal attributes and relationships between employees. There should be a new category, which would include relationships between external and internal parties. It should also include the new ever-growing area of productivity tools, which increase transparency and addresses the information flow in all relationships between individuals, teams, departments, clients and partnerships.
What resonated most to me in Yaroslavsky's article was the quote by RJ Milnor, Head of People Analytics at Uber:
People Analytics has become Business Analytics.
We couldn't agree more. Hence we at Flowtrace have drawn parts of each category to form the basis of Collaboration Analytics, the analysis of relationships which have a direct impact on business outcomes.
The Merger of Interaction, Productivity, and People Analytics
People analytics was coined at Google in 2007, as a practice to analyze teams and people; how people get their work done in a high growth company (Google was doubling its workforce yearly around this time). It includes employee engagement, employee experience and Organizational Network Analysis (ONA) tools.
Interaction analytics (also called customer relationship analytics) is a newer segment of analytics, which analyzes client interactions across different communication channels. Its purpose is to examine external relationships and drive customer insights for better business outcomes.
Productivity analytics is a recently defined category, but one which has seen a definite surge of growth. This category represents tools for improving transparency and optimizing information flows, like meeting efficiency optimization, knowledge management, and horizontally integrated tools, each claiming to improve employee productivity.
Two Sides of a Coin: Company Analytics
Heads – People Analytics
People analytics commonly peers into the internal team, its attributes, relationships, experiences and sentiments, and sometimes includes external stakeholders like job candidates. The primary user of this product category has traditionally been Human Resources. This is echoed by CIPD's definition: "People analytics provides people professionals and their stakeholders with insights about their workforce, HR policies and practices". There is, however, a clear trend towards an expansion happening with people analytics style tools becoming more used by the whole workforce: every employee, manager, and leader.
Tails – Interaction Analytics
Client relationships are often considered a relationship between entities, "B2B", which we know is not accurate, as every relationship is always between real people. This category is not counted as people analytics though. The difference is mainly that the primary user of the tool, communication channels and insights, is not HR, but likes of sales, marketing, customer success, and leadership team. These human interactions have a profound effect on employee engagement and work experience: an employee might spend most of their work time communicating with clients and external parties instead of colleagues.
Predicting Based on the Present – Productivity Analytics
This loop between pulling data from internal and external interaction will only be complete when you bring in the data from so-called productivity tools across the company. Now they are mostly isolated information silos for their core user base. If the tools can't see what interactions are happening outside their system, the platforms cannot create the full value to the organization that they promise.
Analytic tools for managers address different needs than those designed for HR. The budget holder and adoption process are different too. We predict this product category will expand dramatically in the next few years and it will unlock the potential of many more users who can benefit from the power of data.
She is right. And not only that, there is a rush to the center with different analytics tools offering more features and using more data from the other areas. They are also trying to expand their usefulness to other customers than just their core users.
We call this center Company Analytics.
Our vision of the emerging product category is this:
People analytics has enabled the rise in the status of Heads of HR in companies by offering them actionable insights based on employee data.
While I take a knowing risk without the context of RJ Milnor's quote, I want to rephrase it: People Analytics has become Company Analytics.
This means that people analytics tools won't just be under the sole proprietorship of HR and people teams, but instead every leader, manager, and employee is going to have access and a good reason to use those analytical insights to better themselves and business outcomes. Complete picture can be only achieved if the collaboration data is democratised from all the tools company uses.
Combining the understanding of your internal team's workings, how their relationships with external parties are formed, maintained, and concluded will finally give us a possibility to see our companies as data-driven entities bound together by human relationships.
As Yaroslavsky concludes her article, the future belongs to the leaders, managers, and employees who embrace the new technology. I couldn't agree more. Where do you see people analytics heading?