英文学习：Workforce Analytics: what employee data can tell us now
Workforce analytics—or analysing employee data to solve business problems—isn’t new, but it’s earning more attention than ever. This thanks to a stream of technology tools promising to shed light on how employee performance can improve business outcomes, coupled with mounting pressure on HR units to play a strategic role in overall business planning.
Champions of workforce analytics say analysing data taken from HR systems (e.g., payroll, engagement surveys, talent suites) and business operations reveals insight that helps companies raise the quality of new hires, build high-performing sales teams, predict future staffing needs, implement more effective training solutions and drive up customer satisfaction rates, among other things.
Skeptics point out that the benefit of the approach is limited by the amount and quality of the data.
Both sides agree workforce analytics (also referred to as “HR analytics” or “people analytics”) has the potential to offer great strategic value even though widespread adoption still has a way to go. The 2018 Deloitte Global Human Capital Trends report, for example, which was based on a survey of 11,000 business leaders globally, showed that 85 percent of companies believe people analytics is important, but only 42 percent said they are ready to address it.
Workforce Analytics in Practice
The following are examples of how this technology is being applied show the upside of data-driven decision making.
Crunchr, an Amsterdam-based startup, offers a tool it says measures the preferences of employees and applicants, which in turn enables companies to attract and keep the right employees. Using gamification, it asks users 16 questions about what they value most in their workplace, covering areas such as salary, benefits, career growth opportunities and job security. The surveys are anonymous, but the tool also collects data such as academic background, experience and gender. The results rank the preferences of employee groups and sub-groups.
“Understanding what these preferences are helps companies design an employee value proposition where money is spent wisely,” explains Dirk Jonker, Crunchr founder and managing director. For instance, a company might offer a lower-than-average salary but include higher-than average training benefits if that is shown to matter more to a candidate.
Another Crunchr tool that tracks high-potential employees also predicts flight risks, says Jonker, giving companies a chance to intervene before an employee jumps ship. OLX Group, an online classifieds operating company belonging to Naspers, is experimenting with the tool to stem flight risks among key product and technology employees. It identified two flight risk markers: reaching the 12-month employment mark and working in a unit with below-average aggregate employee satisfaction levels. When these employees get flagged in the system, the company checks in to assess their engagement level, says Brad Porteus, OLX Group CHRO.
“In a perfect world, great line managers would do this instinctively, but with data and insights, we are able to be more targeted in our outreach, especially to ensure that individuals don’t fall unexpectedly through the cracks.”
Workforce analytics providers say their technology also addresses the thorny issue of gender pay gap by comparing salary, employee and performance data to exposewage discrepancies.
Beyond traditional HR areas, people analytics has been deployed to improve customer satisfaction and sales. McKinsey describes in a case study how its software helped a large restaurant chain pinpoint ways in which staff performance affects these levels. It collected and analysed front-line employee data in three areas: personality traits, day-to-day management practices, and behaviour and interactions on the job. One surprising insight was that financial incentives were less effective than career development opportunities in boosting employee motivation. Changes here and in other areas have driven up customer satisfaction, revenue by outlet and speed of service.
The Limits of People Analytics
Those cautious about workforce analytics point to its limitations.
For one thing, data analysis works best with large data sets, yet companies have limited amounts of information on employees. Jonker admits that “advanced questions” companies want answers for, such as “can you predict which of these candidates will make the best salesperson?” simply cannot be answered with the data they currently have.
There are also restrictions on how much data companies can collect beyond what’s gathered internally—EU’s tighter privacy laws prevent employers from looking at social media profiles without the owner’s consent. Employee data cannot be legally moved or examined across national borders in some cases.
Data quality matters, too.
“You can only apply statistical analysis when you have a large number of homogenous units” (like sales teams that do the exact same kinds of work), argues Alec Levenson, senior research scientist at the Center for Effective Organizations at the University of Southern California and author of “Strategic Analytics: Advancing Strategy Execution and Organizational Effectiveness.”
For data to be meaningful, it must be “cleaned” so that, for instance, job titles or salaries in different currencies are consistently standardized across data sets. That’s a feat in itself.
“For OLX Group, with nearly 5,000 people working in 25 unique countries, to get even basic reporting has been more challenging than meets the eye,” says Porteus.
More broadly, most companies fail to do data analysis across decision-making centres—business operations, finance and HR—says Levenson, which diminishes the value of HR insights into company strategy.
“Even in really big companies, the number of times it happens is astonishingly low. Decisions get compartmentalised.”
Currently, investment in HR analytics is concentrated among large multinationals that have both the data and the skills to extract value from it. Smaller companies aren’t prioritising it, Levenson comments. But most organisations can begin extracting value with people analytics in simple but high-impact areas, says Jonker. He suggests companies look at failed starters (employees who leave within 12 months after hire). By analysing data from these employees and the managers who hired and supervised them, a company gains insight on which managers may need coaching for making hiring decisions, what triggers new hires to leave (e.g., problems with selection, onboarding or development), and the best recruitment channels.
Porteus believes people analytics can raise employee satisfaction by prompting human interaction.
“Data analytics can help us stay in front of the curve and ideally ensure that we are on our front foot instead of our back foot.”
Browse human resources courses for executives
Kate Rodriguez is a former senior career search researcher and government analyst who covers career development and higher education marketing for The Economist Careers Network.
人力资源和工作流程——生产力系统 HR & the flow of work – Systems of Productivity文/J Jerry Moses
以下是Josh Bersin在TechHR 18会议上对人力资源技术趋势的一些见解：
On Day 2 of TechHR18, Josh Bersin,Founder of Bersin by Deloitte, presents a research-based analysis of how a new generation of recruiting, management, learning, career, and employee experience tools are radically disrupting the marketplace
Micro trends are driving change – changes in the HR technology landscape, the way we work, and particularly, the changes in how organizations are being managed and are managing. The world of HR and HR tech is undergoing a significant shift. HR is now over Cloud, Social and Mobile – this is the time for a new breed of systems - intelligent platform strategies that are making HR and its processes real-time, productive, agile and data-driven.
But “Nothing in technology makes sense unless its aligned with the business problems we are trying to solve” as Josh Bersin says. Here are a few insights on HR tech trends from Josh Bersin’s session at TechHR’18.
Technology, Automation, Robotics are here and they work!
According to Bersin’s research, 45 percent of companies are still focused on basic process automation. The business ecosystem is almost a decade into the economic growth, and has a plethora of generations working together in it. We are living longer, the average career spans 70-75 years, and technology is disrupting where we work along with our daily lives. Most of HCM trends, technology, robotics, AI, automation, is actually becoming real. However, we don’t know what to deal with it all because most companies are still struggling with the challenges of the right skills, structures, organizational design, and rewards systems.
Productivity is an issue!
Productivity is lagging. The real key for HR going forward is becoming the Chief of Productivity. If employees use products and tools that the organizations provide to them, employes will feel better, happier, and engaged. And this is the secret of what is going to happen to HR technology – building systems for the HR that make people productive. With agility, team-centric organizations, burnout is becoming an issue while employee engagement and communication tools are overwhelming employees. This is the time for businesses to build HR software that really improves productivity and helps teams work better together?
Business as a social enterprise!
CEOs are now being asked to take social positions on topics and act on behalf of communities, stakeholders, shareholders, and employees and customers. The future of business is in becoming a socially conscious enterprise and here, the most important thing would to be to develop a technology strategy that provides purpose, meaning, transparency and fairness. Businesses can no longer afford to buy technology that implements practices that someone else coded.
Continuous Performance Management has a huge impact – get the tools
Continuous performance management is transformative. It really and truly works! Ratings will not go anywhere but the crucial part will be to build newer and continuous processes for goal setting, coaching, evaluation, and feedback. This is time for organizations to reconsider performance philosophy. Even with the success of the cloud HCM vendors in the market, a comprehensive solution for performance management is not available. “Team-centric” tools will be the future of HCM market in the future.
Big HR Tech vendors are not keeping up
Most of the ERP vendors are struggling to keep up with the evolution and changes in the business ecosystem. ERP vendors are not getting good marks for ease of use, integration, or value to the end users or employees. There is a stiff competition in the ERP market and it is becoming crowded.
Talent management is done!
The whole idea of Talent Management was about pre-hire to retire. But we don’t work like that anymore. Most of us work at many companies during our careers and organizations are also going through change, disruption and reorganization. Managing employees through the entire lifecycle is not really the problem but managing employees in a new management environment that is about teams, empowerment, mission, purpose, clarity and transparency of goals. It’s a totally different management environment and we need tools to deal with that.
How we pay people will be disrupted
The most disrupted area of HR to come is the way we pay people. Only 1 in 5 companies believes that their rewards system is actually aligned with their corporate strategy. We are still paying people the way we did in the past — salary bands, annul reviews, policies of secrecy and who is getting paid what – all this will be disrupted and we will have a whole new set of tools for employee experience.
Corporate Learning is the real deal!
Platforms like Degreed and Edcast are transforming corporate learning — experience platforms, micro-learning platforms, modernized LMS systems, AI-based systems to recommend learning, find learning, and deliver learning, and Virtual Reality-based learning are giving employees and organizations all the things they need.
Employee wellbeing market has the true potential
It’s all about the moments that matter. There is a need to improve productivity but there is a significant impetus on employee wellbeing, reducing the cognitive overload and augmenting human performance. This vendor market is moving fast. The new world of work will be about “engagement, productivity, and wellbeing” all in one.
ONA software market is now growing
With the explosion of HRMS data, wellbeing data, networking data, among many other forms of structured and unstructured data, HR is struggling to deal issues of ethics, privacy, and becoming more transparent about the analytics they are doing. The Organizational Network Analytics is growing and so is a new world of “relationship analytics”. People Analytics will guarantee success.
Getting into the Flow of Work
Employee experience is the buzzword and we are trying to reform it in a way that applies and improves the work experience of every individual in an organization. Organizations define employee experience as a project of looking at the moments that matter, transitions, periods of time in career where one is stressed and what can HR do to make that easier. But none of the tools are designed to measure or map something like this. All tools are designed for the HR function, not this. There is a new category of software being built to help HR with the employee experience - to shield employees from the complexities of the backend HR systems and deliver all the different things the HR does in the flow of work.
如何为人力分析专业人士创造职业道路-How to create career paths for people analytics professionals（续）文/David Green
LEADING THE PEOPLE ANALYTICS TEAM
7. Turning towards your role as a People Analytics Leader, what would your advice be to someone who is new to this role or who aspires to be a Head of People Analytics in the future?
I think everyone has different strengths and experiences, which means their approach will vary with regards to them proving successful as a people analytics leader. But based on my personal experiences and observations of others, I can share five attributes that I think apply universally and are important to being an effective leader in this space.
Prioritise: Whether you have a small or large people analytics team, it will never be big enough to meet all the demands of your clients, particularly as awareness of the team’s capabilities grow. So, it is critical for the people analytics leader to learn (and teach!) how to relentlessly prioritise the projects on which the team will spend its time and effort. A good rule of thumb is to think about the magnitude of business impact that an analysis has the potential to deliver, or a key relationship that it can help build in the business for future collaborations and sponsorship. Many teams even use formal prioritisation grids to help the process, but ultimately the leader needs to ensure that the criteria used to allocate resources to projects aligns with the vision and mission of the people analytics team (which in turn, should align with the objectives of the enterprise).
It is critical for the people analytics leader to learn (and teach!) how to relentlessly prioritise the projects on which the team will spend its time and effort.
Position: A critical skill for a people analytics leader is the ability to effectively position analyses before the right decision-makers at the right time to maximise positive outcomes and build a strong people analytics brand. This is probably one of, if not the most, important part of being a people analytics leader. On many occasions, brilliant workforce analyses have been underutilised in their original scope, but a good leader knows how to find the right opportunities to repurpose, combine and present this work. This is not only important in gaining prestige and recognition for people analytics, but also for boosting the morale of the team.
Connect: There is a small, but growing, community of people analytics leaders globally who collectively have a spectacular amount of experience and knowledge. Fortunately, this community is inclusive and generous, in terms of sharing their knowledge and connections with others in the field. The group is a great resource to learn about new technologies, techniques, vendors, and also receive tips and tricks that can help a new leader to avoid mistakes and grab the right opportunities. Most importantly, as you build new professional connections you also begin building friendships that are a support network to help you navigate this fairly ambiguous, new(ish) space of people analytics.
Evolve: Since a people analytics leader needs to have some depth in analytical methods, it is always a good idea to read, listen and learn. Thanks to social media there are amazing resources available, many of them free, that any analytics leader can and should leverage to keep oneself updated and evolving. There are some extremely prolific writers (like David Green!) who share both original and curated content on various forums including LinkedIn. Whether you are looking for detailed tutorials on advanced data science methods or want to learn about the latest technological breakthrough and its application to people data, there is a publication, podcast, or video out there on it. Another reason why this mind set of curiosity and awareness is important is because the people analytics space is sensitive primarily due to ethics and privacy reasons; and keeping a handle on that also demands a leader who keeps their eyes and ears open. An important part of being a strong people analytics leader is to keep up with the pace of change externally and bring that learning back to your business.
An important part of being a strong people analytics leader is to keep up with the pace of change externally and bring that learning back to your business
Develop: Last, but certainly not the least, a critical part of being a good people analytics leader is simply being a good leader. This implies being someone who invests in the development of their team. It is of particular importance because it is a space that has attracted a lot of exceptional talent, but still has somewhat limited opportunities for advancement. Therefore, an effective leader needs to invest time and effort in building their own internal and external network; and share it with their teams for their advancement. They should also be committed to actively finding or creating opportunities for their team members to learn new skills and develop themselves as multi-faceted professionals.
An effective leader needs to invest time and effort in building their own internal and external network; and share it with their teams for their advancement
8. One of the challenges I’ve observed in being a people analytics leader is that you have to balance the significant challenge of building capability internally whilst keeping an eye externally on what is a fast-developing field. As a people analytics leader, how do you juggle these two priorities, and how do you keep abreast of what is happening outside the organisation?
I strive to practice the same behaviours that I would advise new people analytics leaders to try. For example, I follow and subscribe to content by certain thought leaders in people analytics and read as many varied publications as possible (blogs, articles, whitepapers, books) which keep me connected to the different aspects of people analytics; from social science to artificial intelligence.
In addition, it really helps to connect with other practitioners in the field from different industries, which I do via both informal and formal peer networks. This helps to broaden one’s worldview, spark new ideas, and offers a forum to ask questions of your peers. Most likely, if you are facing a people analytics quandary, there is a leader out there who has faced it too and would be willing to share their experience.
Finally, there are a plethora of great conference events out there, and the quality and number of these keeps rising every year. I try to participate in at least a few such events every year to learn new things and meet new people.
THE FUTURE OF PEOPLE ANALYTICS
9. What do you believe will be the main trends moving forward in people analytics?
I think that a number of “hot areas” in people analytics will continue to get “hotter” in the future. The idea of employee experience will grow even wider with focus on the end-to-end experience all the way from being a prospective candidate stage to becoming an alumni of the company. This is likely to grow simultaneously with the focus on managing and optimising a new, fluid workforce that may at any one time be full-time and freelance, human and robotic.
I also think that the power of networks will be fully explored and unleashed as research grows and more organisations invest in this space. The applications of network analysis are so varied and relevant, that it should continue to gather steam in the future.
Finally, from my perspective to enable all these types of analyses, one of the most critical areas that will grow in importance will be the study of ethics relating to data use, privacy and security in the space of people analytics.
10. Finally, how do we balance what we can do with what we should do? How concerned are you about areas such as ethics and privacy?
This is a great question, and a difficult one to answer. The frontiers of what is possible are being pushed at a break-neck speed thanks to ever larger datasets being at our disposal faster, and at cheaper cost. And that pace makes it tough to process the implications in real time. In fact, this often leads to an overreaction or the inclination to adopt an overly conservative approach that can hamper some great work in the people analytics space.
That being said, I believe that an extremely important fact to understand about the space we work in is that we should not do something just because it is possible. Besides being legally compliant, the type of work being undertaken in this field needs to put ethics at the very top of the agenda even before beginning work on an analysis. Working closely with the appropriate experts in the practices of employment law, privacy law, ethics, communications, business partners and workers councils is a good way to ensure that besides the legality of the work, its potential impact on people is also being considered through the lens of ethics, privacy, and empathy. Most established organisations have extensive reviews involving these types of stakeholders already in place.
Another way to pressure test the approach from an ethics lens is to share possible outcomes of an analysis with the internal clients beforehand and ask them to articulate what actions they would take in each scenario. Obviously, this method is not possible in every situation, but when applicable it can be a useful “stop and reflect” moment.
The type of work being undertaken in the people analytics field needs to put ethics at the very top of the agenda
如何为人力分析专业人士创造职业道路-How to create career paths for people analytics professionals文/David Green
根据德勤于2017年11月发布的“高影响力人力分析研究”(High-Impact People Analytics study), 69%的大型机构(10,000多名员工)现在拥有一个“人力分析团队”。
Geetanjali Gamel在旧金山举行的“人民分析与未来工作会议”(People Analytics & Future of Work Conference)上的演讲这个话题。Geetanjali是默克公司劳动力分析的全球领导者。在2017年9月在费城举行的人民分析与未来工作会议上发言。
MERCK & CO.的人力分析团队
问3、德勤(Deloitte)的“高影响力人物分析”(High-Impact People Analytics)研究发现，在创造高级能力方面，最重要的因素是需要创建数据驱动的文化。你在默克公司是如何做到这一点的?
According to Bersin by Deloitte’s High-Impact People Analytics study, which was published in November 2017, 69% of large organisations (10,000+ employees) now have a people analytics team.
It is a surprise then that many organisations overlook the need to develop the careers of their people analytics team. Given the pace of evolution of the field and the high-demand for talent in the space, this is an oversight that needs correction.
As such, it was refreshing that the main focus of Geetanjali Gamel’s presentation earlier this year at the People Analytics & Future of Work Conference in San Francisco (see key learnings here) was on this very topic.
Geetanjali is the global leader of workforce analytics at Merck & Co., Inc. (NYSE: MRK, known as MSD outside the United States and Canada). I caught up with Geetanjali recently to ask how she has created career development paths for her team as well as discuss other related topics in the people analytics field.
Geetanjali Gamel speaking at the People Analytics & Future of Work Conference in Philadelphia in September 2017
WHY PEOPLE ANALYTICS?
1. Hi Geetanjali, please can you introduce yourself, describe your background and explain what attracted you to the people analytics space.
Like many of my colleagues in people analytics, I’ve had a non-linear path to my current role. I am a trained economist and began my career in research at the Federal Reserve Bank of St. Louis studying topics like macroeconomic forecasting, unemployment and inflation. With this foundation in social science methodology and research, I soon transitioned to business forecasting, predictive analysis and scenario-planning to drive customer growth and revenue projections in corporate planning and finance departments in the energy sector. The most intriguing part of my work was in understanding, measuring and predicting human behaviour and its impact on business outcomes such as sales and revenue. So, I was naturally attracted by the opportunity to bring scientific methodology to people data and help shape how an organisation can drive value for its investors along with enhanced experience for its employees. I began by building a predictive analytics function from scratch in HR in my previous role at Mastercard and since 2016 I have led the advanced workforce analytics, consulting and reporting organisation in Merck HR.
THE PEOPLE ANALYTICS TEAM AT MERCK & CO.
2. Please can you describe the size and structure of the workforce analytics team at Merck and how it aligns to the business
Merck’s workforce analytics team (WFA) has 15 members who support 69,000 employees in over 80 markets worldwide through a rich portfolio of people analytics products.
The team consists of three primary pillars; Consulting, Advanced Analytics, and Reporting & Data Visualisation (see Figure 1 below).
Figure 1: The Workforce Analytics team at Merck & Co (Source: Geetanjali Gamel)
Consulting - Each consultant is aligned to one of our business divisions like manufacturing, research, sales, etc. They work closely with leaders to understand and anticipate burning business questions, utilise the right methodology to find the answers; and convert the analyses into actionable insights.
Advanced Analytics - The advanced analytics team is a nimble group of data scientists and specialised professionals who focus mainly on ad hoc projects requiring advanced technical skills and/or initiatives of enterprise level significance. They are organised around business questions and may support several divisions at a time, in contrast to the end-to-end approach that the consultants take with each initiative.
Reporting & Data Visualisation – This team forms the backbone of all the amazing work we are able to do, as well as the internal customer satisfaction we drive. They work directly with internal clients from all parts of the business to ensure that the right people have the right data at the right time.
The three WFA teams work closely with each other to ensure that any synergies between business initiatives are identified and leveraged.
CREATING A DATA-DRIVEN CULTURE
3. The recent Bersin by Deloitte High-Impact People Analytics study found that the single biggest predictor in creating advanced capability is the need to create a data-driven culture. How have you achieved this at Merck particularly with regards to HR Business Partners and the wider HR function?
I agree that culture can be the strongest catalyst or impediment for people analytics. It is also ridiculously difficult to identify and alter, particularly because organisations at any given time tend to be collections of sub-cultures. But there are some patterns of behaviours, decision-making, and incentive-rewards, which distinguish data driven cultures from others. These behaviours can be purposefully incubated through a combination of upskilling, training and mind-set building.
At Merck, we believe that a leading HR function is one where analytics capability is not only for the analytics team, but the whole HR team. This does not imply that every role requires equal depth in analytics, but a new baseline of data interpretation and communication skills is critical to being effective partners to the business. To this end, we started out by democratising data within our HR community by rolling out a cloud based workforce analytics platform. This is helping us drive greater familiarity and reliance on data among our HR users. We have also developed and deployed a capability-building program with modules focused on metric selection, hypothesis testing, data visualisation, recommendation development, and more.
Another channel that we have been leveraging to accelerate a data driven culture in HR has been to engage members of our wider HR community as analytics “Champions”. These superheroes are critical to spreading the adoption of data informed insights, since they live and breathe the daily challenges of their colleagues; and can share relatable examples with their counterparts on how data can unlock value.
Finally, we also have an HR leadership team that is aligned and strong advocates in relaying the message of building data and analytics capability in HR. Needless to say, sponsorship of senior leaders is imperative to the success of a people analytics function.
Sponsorship of senior leaders is imperative to the success of a people analytics function
CREATING CAREER PATHS IN PEOPLE ANALYTICS
4. You are passionate on the need to create career paths for people analytics professionals. Why do you believe this is so important?
I firmly believe that the goal of people analytics is to drive value for the business as well as provide a better experience of work for employees. So naturally, I am equally passionate about building a better work experience for the people who make people analytics possible! I find a sad irony in the fact that the team which enables decision-making on areas like career pathing, succession planning, and talent movement for the larger workforce, is often stuck in a position of having nowhere to grow. From my discussions with many colleagues in this field, I have learned that the typical people analytics team usually tends to have a group of individual contributors (analysts, data scientists, consultants) and a director or senior director level leader. This leaves only one spot for the entire team to aspire to, at least for upward movement.
In addition, most people analytics teams sit within HR and tend to be branded as a highly-specialised “HR-lite” centre of excellence (CoE), which limits the opportunities to move laterally or upward into other HR roles in CoEs or business units. And this reality of being “boxed-in” can be very frustrating for bright, highly-employable individuals.
If you are a leader in people analytics, and if you have had to recently recruit new talent for your team, I would guess you are acutely aware of the gaping chasm between talent demand and supply in this field. In my opinion, an organisation and a leader who can offer development and career growth can be a key differentiator in attracting and retaining the best people analytics talent.
Broadening that vision, if we enabled more fluid movement of people analytics talent, it would add to the diversity of skills, approaches and perspectives to other parts of HR and the business, and would create additional value for the enterprise.
An organisation and a leader who can offer development and career growth can be a key differentiator in attracting and retaining the best people analytics talent
5. What program have you put into place at Merck regarding the career development of the people analytics team?
From the first day of my role at Merck, one of my top priorities was to understand the strengths and aspirations of my team and align their development to meet their career goals. After multiple discussions and numerous iterations on ideas, I arrived at a Capability-Capacity-Connectivity model to power a sustainable development program for our people analytics team. The underlying idea is that if we can build the right capability within the analytics team and its clients; reallocate capacity that is being consumed by suboptimal tasks; and drive connectivity between people analytics teams and other parts of the business; then we can potentially discover and create new career paths and opportunities. But please bear in mind that a key driver of success for such a model is sponsorship from your leaders and partnership with other teams. In our case, we were fortunate to have both. This has empowered us to be inventive and co-create development opportunities for our team.
6. Please can you provide more detail on what comprises each of the Capability, Capacity and Connectivity elements of this approach. What have been the key benefits and learnings from the career development program?
The “3C” approach is built around tackling barriers and creating bridges that promote career development for people analytics teams. At the outset we knew that the team was faced with a high volume of requests needing significant manual effort. (see Figure 2 below):
Figure 2: Challenges in accelerating maturity in people analytics (Source: Geetanjali Gamel)
Since the day-to-day work was time and effort intensive, there was not much room to hone more sophisticated skills or build knowledge sharing relationships with others, leaving the people analytics team stuck in a loop. So, we put careful thought and purpose into adopting the following model.
The first “C”, or capability, had to be addressed at two levels. The first was to empower our broader HR team with the right tools and training to have greater autonomy to perform analyses. We moved to an intuitive analytics platform and organised workshops, office hours, and learning sessions to improve data literacy among our internal HR clients. This type of effort is important to free-up time for the people analytics team to build their own skillset (and path to growth), while also creating a greater awareness in other parts of HR about analytics.
Figure 3: Capability - Level 1: building data, technology and analytics savvy clients (Source: Geetanjali Gamel)
The second area of capability building had a more direct impact on the team. We held a team strategy session where we identified areas that needed focus for internal functional, technical and strategic competency building. These focus areas were carefully selected to create dual impact – provide us with a skill or knowledge we could use immediately in our work; and more importantly, help us practice a new behaviour that would develop us as well-rounded professionals. For example, on the technical side, we organised an in-house R-training curriculum, created and delivered by some of our own colleagues to the rest of the team. This helped us build a technical skill we could immediately put to use to do better work, and also built coaching and confidence skills for those who led the program. Another great example was of an external guest speaker series that we launched, which brought recognition to the team for bringing new insights to the company, and also helped the team gain experience in organising an event successfully end-to-end.
Figure 4: Capability - Level 2: Upskilling the people analytics team (Source: Geetanjali Gamel)
At first, capacity building measures may not sound like a natural fit with developing career paths. But it is impossible to focus on the next steps in one’s career if there is no time to step away from the daily barrage of activity to have a conversation; listen to a webinar; learn about a new project; or simply, chat with colleagues over lunch. As such creating capacity for the team is critical to allow them to develop their skillset to be more widely applicable, as well as to build the networks they need to find new opportunities.
As mentioned before, our journey began with democratising data and providing a range of workforce metrics and even results of our enterprise voice survey in accessible cloud platforms to our HR community. We continue to supplement our efforts to empower our internal clients, and in the process unlock capacity for our team, by forming global communities of practice for analytics. Another effort to scale our analytics delivery and save precious time has been by finding opportunities to utilise process automation on repeatable tasks.
It is impossible to focus on the next steps in one’s career if there is no time to step away from the daily barrage of activity
Despite efforts in building capability and reallocating capacity, there can’t be much career development if there is nowhere to go! This is when the third “C” of connectivity comes into play. In fact, it could just as easily be C for creativity, because we need a great deal of innovative thinking and risk taking to create opportunities where they don’t always exist.
We started with small yet effective steps rather than trying to construct huge, formal programs. Connecting the people analytics team with other HR, data science, technology, and business professionals builds an awareness and appreciation for different types of work on both sides. We leveraged opportunities to co-create part-time assignments with other teams, participate in cross functional events, invite guest speakers to team meetings, and collaborate on projects to expose the team to other areas of analytical work.
Connecting the people analytics team with other HR, data science, technology, and business professionals builds an awareness and appreciation for different types of work on both sides
To create development assignments for the people analytics team we were creative and went with “quasi-experiments”. The first was an opportunity for a team member to take on the role of an HR business partner on a part-time basis for a few, smaller client groups. This gave the individual an opportunity to apply their analytical skillset to the role and get much greater exposure than before to business clients and business issues. Such an experiment has a multiplier effect. Where typically a business partner track is not easily available to a people analytics professional, creating such an opportunity internally can open up a new career path. Moreover, even if the individual does not end up pursuing this new career direction at the end of the experiment, it is still a valuable learning experience for them to be in the shoes of their internal client, i.e., the HR business partner. Finally, it may help to lay the foundation for what I like to call the HRBP 3.0 model.
Where the original HRBP role had a heavy component of operational (and even transactional) work, the HRBP 2.0 model that many companies follow today aims at strategic business partners who enable key business decisions. The HRBP 3.0 model takes it a step further by envisioning an analytical HR business partner, who relies on both data driven insight and business acumen to support their client.
Another “experiment” in creating new career opportunities was a mini-assignment we created for one of our people analytics team members to lead a large, remote team in the service delivery space. This was a completely different line of work from people analytics, and was heavily focused on operational and organisational skills like identifying and escalating issues on short deadlines, supplier relationship management, building relationships with a variety of HR and non HR stakeholders, and leading a service centre team to drive customer satisfaction. Clearly, this would not be a typical career path for a people analytics professional, but that is exactly why we need to be bold and creative with such experiments. This assignment not only exposed the individual to a different type and pace of work, but also gave them an opportunity to bring their analytical skills to the table to significantly elevate the usage and interpretation of transactional data.
While many mature organisations have good-sized people analytics teams, there are still many where the teams are pretty lean. This model may work well for most purposes, but it usually limits the opportunities for team-members to have people management experience. This is not always necessary for upward mobility, but it many cases it is difficult to move upward without some kind of experience of leading a team. Keeping this in mind, we built more depth in our people analytics team, creating enterprise advanced people analytics and data visualisation and reporting sub-teams within the larger group, which are led by two of our team members. Taking a chance on subject matter experts and giving them the opportunity to lead and delegate not only helps to open up doors for them, it also gives them a chance to coach others on their team to be future experts and leaders.
Lastly, we also created a new learning analytics role on our people analytics team which is a step toward building greater synergies between people analytics and learning practices, but also our small contribution in creating a new capability (and career path!) that is still evolving in many organisations.