Winner: Best Use of People Analytics
When it comes to people analytics, Manulife has got it covered. Through a team of HR professionals, it proactively provides data and analysis that link to strategy and business priorities.
“We are not driving our people business decisions by publishing an exhaustive list of general statistics and reports, we are influencing our leaders by sharing and promoting key actionable people metrics and relevant data stories linked to business priorities,” says Charles Caouette, vice-president of global HR and business solutions and workforce analytics in Montreal.
The team also partners with an advanced analytics team and a group of data scientists and statisticians to help solve business problems and predict future ones using statistical models, algorithms and machine learning.
Manulife is a very customer-focused organization and for the “analytics partner” team, this means understanding business needs and priorities, says Lisa Ryan, interim head of shared services in HR at Manulife in Boston.
“We’ve developed a comprehensive set of people metrics that we’ve curated and improved over the years. We deliver an evolving set of dashboards and analysis which includes results for key people metrics that are aligned to the overall company strategy and are relevant to leaders and their business.”
The analytics team gathers data from numerous sources to produce quarterly metric results, as well as ad hoc analysis in the form of visualized dashboards, trended analysis, and data stories.
“People analytics help our leaders make more informed people decisions. They’re also essential for tracking our progress toward key people and culture goals across the organization,” says Ryan.
Using a set of more than 50 standard metrics, the team focuses on areas that include employee engagement, diversity, organizational design, employee development and turnover — with splits across different lines of business, location, business leader and organizational levels.
The team also creates new metrics based on business needs. For example, in 2017, it introduced a “build vs buy” metric to show leaders the extent to which they were developing talent internally through promotions and lateral development moves (building) versus bringing talent in from the external market (buying).
“We’re also often asked for insight into what’s going on in the business: Are we providing enough development opportunities for our employees; why are certain employees more engaged than others?” says Ryan. “We love these questions, and digging into the data to uncover trends and observations that are meaningful to the business. To do this, we use both our existing metrics as well as the exploration of new data and/or metrics to think about the business questions in different ways.”
“We often include visualizations to help draw attention to the findings and what the data is telling us, as well as include an accompanying narrative which supports the explanation of why it’s important.”
As an example, Manulife’s CEO, Roy Gori, asked for a dashboard of each member of the executive leadership team, to track how they were doing on key people and culture metrics such as turnover, employee engagement and diversity. The dashboard was designed, built and tested within two weeks.
“This concise, one-page visual view replaces what was a lengthy package of results and has led to more meaningful conversations with both leaders and HR partners,” says Ryan.
The analytics team is also working to increase the breadth of data used so it’s not just limited to the core HR systems. One such area is around employee behaviour and competencies. So the team piloted the use of a competency measurement tool based on game theory. In measuring a user’s interaction with three games, it creates a behavioural profile outlining their natural inclinations to problem-solving. This can help with creating individualized models for career pathing and development plans.
An example of the team’s consultative approach can be seen in a diversity and gender analysis it did in 2017. It partnered with the diversity and inclusion team to create a gender diversity dashboard with a number of different views comparing results on various touchpoints in employees' careers.
Once the dashboards were shared with leaders, recommended actions were adopted, with greater emphasis on leader accountability and coaching.
Going forward, the analytics team at Manulife is pooling its data with data from other sources.
“We’re building out our workforce data and pooling it with data from other reliable sources and creating a new data model so that it can all be housed in an enterprise data lake,” says Ryan.
“This will help to eliminate any silos of data that exist and start to democratize access into a single unified view across the organization. With an increase in the volume and variety of data available, we’ll be able to dig deeper and produce better algorithms and analytical models to recognize areas of interest sooner that will help empower more real-time decision analytics.”