Mergers have played a significant role in the history of First West Credit Union, often triggering increased resignations. The HR team faced challenges with data in multiple systems that did not communicate with each other, making it difficult to track metrics across branches and divisions for workforce functions such as compensation, staffing, recruiting, and retention. The leadership team recognized the need to strengthen its focus on workforce analytics to understand the impact of mergers on its workforce and build a data-supported culture within HR.

Until 2011, Merck KGaA's talent processes were managed locally, leading to inconsistent data and analytics across regions. This lack of standardization hindered the ability to correlate data and derive meaningful insights. The company aimed to standardize and integrate its talent processes globally to enable a unified data view. This involved moving recruiting, performance, compensation, and succession planning to standardized global processes. The goal was to create integrated processes that would allow for better analysis and decision-making. Additionally, Merck KGaA needed to address data privacy and regulatory issues, particularly in collaboration with their Works Council.

Experian faced several challenges in implementing a people analytics solution. Firstly, they needed to address the workforce data needs of leaders and translate potential value into terms that leaders care about. Secondly, they had to define key metrics and attain global alignment on definitions. Thirdly, engaging HR business partners as business champions and keeping them engaged was crucial. Lastly, they needed to combine data sources from multiple systems and remove the reliance on static lists of data and Excel-based analytics tools. Despite being an analytics company, getting buy-in for a people analytics solution required extensive pre-work to show how workforce analytics could address workforce issues. Sales leaders, in particular, wanted better insights about their employees, and turnover reduction was a significant concern for business leaders.

The organization faced challenges due to an accelerating pace of change in healthcare, policy changes, and consumerization trends. The Workforce Planning and Analytics Team's senior director recognized that the organization was not optimally positioned to lead these changes with the right talent in the right places. Additionally, leaders needed faster and more complete access to workforce data for analysis and future planning. The organization underwent an HR transformation, moving to an HRBP model to support people leaders, but the HRBPs lacked the skill set to leverage analytics effectively. The director advocated for a strategic workforce planning and analytics function to empower HR and organizational leaders to proactively position the workforce to achieve strategic priorities.

As with many organizations, Alere did not have a consolidated data source that could tell them where they had overall turnover, where they specifically had new hire turnover, nor how many of their highest contributors were leaving the organization. Furthermore, the Company did not have sufficient information to determine expenditures on getting replacement talent. Additionally, as with many forward-thinking organizations, Alere wanted to upskill the HR community to be more analytical.

The organization needed to match staffing levels with growing demand from customers, including both employees and contract staff around the globe. It had been using spreadsheets to build people strategy and workforce plans. However, planning with spreadsheets made it difficult to establish a consistent process, keep track of versions, and ultimately, ensure the workforce could meet its new goals as it evolved. Workforce planning was driven largely by the Finance department. Analysts in Finance partnered with business groups, which in turn had their own processes, calculations, and timelines for creating plans. When the organization tried to create a consolidated plan, the results were chaotic—due to differences in data, manual errors, and version control issues. The organization wanted to do monthly forecasting, but it proved to be too difficult.

The healthcare organization faced a significant challenge in managing employee turnover, which was impacting their operational efficiency and financial performance. The HR team needed to shift from reactive manual reporting to a more strategic, analysis-driven approach. They aimed to provide leadership with insights into future trends rather than just analyzing past data. The primary objective was to understand the cost of turnover and quantify the savings associated with reducing it. This required a comprehensive analysis that could present retention initiatives in financial terms meaningful to the leadership team.

Pitney Bowes faced challenges in gaining visibility into critical workforce trends such as hiring, movement, performance, and retention. The process of manually bringing data together from disparate systems was lengthy and resource-heavy, limiting data insights to expert users. Additionally, the data was inconsistent and difficult to reconcile with Finance’s numbers, generating a lack of trust. HR struggled to answer questions from senior leaders in a timely manner and to get buy-in for key programs due to the lack of precise data needed to quantify ROI.

This American financial services company has over 8,000 employees and three core lines of business (retail banking, business banking, and wealth management). In 2016, an organizational review conducted by a consulting firm revealed that the company was performing well below the industry benchmark for organizational efficiency vis a vis span of control and layers. Acting on the consulting firm’s recommendations, the company brought the percentage of its manager population down from 30% to 15%, reduced the layers of the organization from 10 to 8 and reduced the number of administrative employees per manager. While this new optimal structure helps the company avoid costly organizational bloat, maintaining the targets requires continuous monitoring.

At a financial organization employing over 5,000 people, the HR team faced a tough choice: build a people analytics platform to meet their data needs—or purchase one. Their HR Technology and Analytics Leader had implemented a custom solution created in-house at previous employers, so he knew the high cost of a bespoke solution and the demand this project would place on IT. At earlier positions, the leader said their custom data warehouse with Workday and best of breed applicant tracking and learning management system integrations took approximately two years to complete. Between this long lead time and the resourcing challenges, building a custom people analytics solution internally at the organization just didn’t make sense. Instead, HR chose Visier to meet their people analytics needs.

McKesson had a need, driven by their CHRO, to make more data-driven people decisions. They had completed an HR transformation several years ago, part of which was designed to further develop HR business partners into true strategic partners for the business. As part of this transformation, they had to inform and arm the business with data they needed to make people and business decisions. McKesson stood up a workforce intelligence group of about five analysts, situated within the corporate Talent Management organization. The group existed as a centralized resource, primarily supporting Corporate HR at first. As a result, McKesson began to go from making decisions about the workforce based on intuition to gaining the ability to come to the table with data, just like other functions such as finance or their major business units. However, these workforce insights were not yet embedded in the business. At McKesson, each business unit had very capable analysts working with business leaders to help them make data-driven decisions. However, they were disconnected. Furthermore, each analyst was focused on their business unit and not necessarily on the enterprise. Each group also had different goals, often with their own dashboards and metrics. This was further complicated by the challenge that there were different approaches, different analytics tools, and different information being used across the groups. While each had good governance, there was a lack of efficiency and an inability to scale analytics efforts. This ultimately meant it was difficult to drive results across the enterprise.

To remain at the forefront of science and research, this American biotechnology company needed an accurate and efficient workforce planning methodology to ensure they have the right talent in the right place–and at the right cost–to deliver their life-changing products. The Talent Acquisition (TA) analytics team developed a comprehensive end-to-end TA Operations strategy known internally as the Total Talent Solution (TTS). This all-encompassing methodology is enabled by a data-driven core, drives the workforce plan and internal talent resourcing strategies, and keeps stakeholders at the forefront of their talent strategy. On a monthly basis, the team uses this model to conduct a turnover and growth analysis that is compiled into a scorecard report. A workforce plan is created in parallel, paying attention to anticipated headcount for the year, month over month headcount changes, and predictive model overlays, as well as business initiatives such as M&A, product launches, and patent expirations. These numbers are shared with HR business leaders and their respective Finance teams, who align on projections, identify challenges, and then recalibrate projected numbers for the planning process.

Anglo American faced significant challenges in hiring, retaining, and managing its workforce with agility in response to unpredictable economic cycles. The company's workforce data was contained in disparate HR systems, including six SAP environments, one SuccessFactors Employee Central HRMS, an internal database, and a SQL data warehouse. This fragmentation made it difficult to standardize data and data management practices, which was necessary to achieve data accuracy and improve efficiency. Additionally, the company had distinct business units with unique workforce data needs and varying levels of expertise in reporting and analytics, making it challenging to generate consistent and aligned reports and analytics. Obtaining reports from these different business units could take days, and if a different question needed answering, analysts had to start anew.

Enbridge Inc. faced challenges in creating a cohesive view of employee experience data to inform HR program redesign and continuous process improvement efforts. The data that mattered, such as employee experience leverage points, wasn't centrally defined or measured. They required a single place to store, trend, report, and communicate employee experience data and metrics. Given the growing demand for custom analyses and employee experience insights, it was difficult to scale early successes more broadly.

A leading industrial manufacturer is committed to achieving a workforce that reflects the communities where it works and serves. With that, it has identified two goals to ensure it achieves that commitment. The first is to achieve 50% female parity in leadership roles by 2030. Secondly, it aims to create a globally diverse workforce with inclusive leaders and teams. Therefore, an accurate picture of their current workforce diversity mix and the recruiting pipeline are key to how the company measures and tracks progress. The team measured retention and promotion rates of women leaders to see how it is changing and where areas of opportunity may exist. They also looked at their recruiting pipeline to better understand how women and minorities move through the full pipeline from recruiter review, to meetings with the hiring manager, to offer extension. The company found that women perform as well as men–and occasionally outperform them. Women also tend to stay longer. However, a review of the talent acquisition process uncovered the amount of women applicants is disproportionately lower than their male counterparts. Further, as women moved through the hiring process, more were dropped during the interview process.

The confluence of three factors–the COVID-19 pandemic, Black Lives Matter, and an economy negatively impacting women and minorities–generated the need for a heightened sense of action to improve diversity and inclusion at this organization. In fact, the CEO’s number one request from the people analytics team is for diversity and inclusion metrics and analysis. They have been dedicated since their inception to raising quality of life for all. This includes continuing work on their public pledge to achieve gender equality by 2030. The organization has also committed to matching its employee populations in terms of gender and ethnic diversity to the areas they have locations and the people they ultimately serve. Operating in over 50 countries, they recognize they must have different diversity improvement strategies across their global locations. With limited resources, the organization has chosen to first establish goals for improvement in the top ten countries where they have operations. They are doing benchmarking in their locations to establish and meet these goals. With gender, their goal is 50/50 by 2030. However, mirroring the ethnicity of their workforce to the communities they serve is more complicated. For example, in the mid-west U.S., the ethnic demographic mix is less diverse.

Sabre, the leading technology provider to the global travel industry, faced a significant challenge with a constant hiring/downsizing project cycle that led to an increase in regrettable attrition of high potential employees from 5% to 9% between July 2017 to March 2018. The company needed to identify the pain points for high-performing employees who were leaving and find a way to retain them. The analysis revealed that voluntary turnover was highest in technical roles, particularly in Krakow, Poland, where there is intense competition for talent. With 20% of its developer workforce residing in Krakow, a higher attrition rate would directly impact Sabre’s operations.

NCI needed a solution to address concerns over employee turnover, identify key talent, and tie employee engagement work to business results. Their existing HCM solution, Workday, had limited analytical capabilities and could not provide the necessary insights. Additionally, data inconsistencies and lack of standardization made it difficult for stakeholders to agree on key metrics, such as days-to-fill. NCI also faced challenges in quickly responding to customer contract proposal pricing, which required detailed analysis of current personnel and associated costs.

To remain competitive in providing research services, this global organization must attract and retain a workforce of qualified consulting and technical staff who work on multiyear projects. With the workforce as the largest expense at the company, its HRIT team plays a key role in helping the business better understand the interplay between workforce factors, productivity, and cost—and, therefore, in improving profit margins as it grows revenue. For its services work to be as profitable as possible, this organization needs to quickly understand in detail the cost of the people required for a contract before preparing a bid. Furthermore, to deliver quality service at the right cost, client projects must be staffed with the optimal mix of junior and senior people in the right locations. However, because the company used a number of workforce systems and analysis tools, there was significant manual effort involved in reconciling costs and headcount, as well as inconsistency in the insights across organizational units. Key stakeholders could not gain a clear picture of how costs by region and role impacted profitability. With data in multiple systems, it was also difficult to quickly provide clients with key information—such as performance rating averages broken down by job level— when responding to Requests for Information (RFIs) and Requests for Proposals (RFPs). HRIT was struggling to produce basic metrics and couldn’t meet the demand for strategic insights at the speed required by the business.

This consumer goods organization sought analytics to consolidate its workforce and business results data so it could easily connect HR initiatives to the bottom line (and vice versa), while also reducing the amount of time the team spent on data gathering and report generation. Additionally, the company wanted to increase the use of data by its HR Business Partners (HRBP) and the rest of the business. Having limited resources, the one-person analytics team knew she’d need a robust solution that would do a lot of the heavy lifting. The organization chose Visier because it could integrate the data sets they needed, and provide out-of-the-box analytics and powerful visualizations that would help business partners better understand and use the data.

Biola University faced significant challenges with their budgeting process, which was performed in Excel workbooks. The process was unwieldy and difficult to manage and control, leading to manual spreadsheet and data collection issues that slowed down the budgeting and planning process. Version control issues resulted in inaccurate numbers, sometimes identified only after the budget was submitted. These challenges necessitated a more efficient and reliable solution to streamline their financial operations.

The company faced significant challenges due to the lack of integration between multiple, disparate financial systems across different lines of business. This fragmentation made it difficult to create effective and detailed budgets for the main corporation and its seven regional offices. The heavy reliance on spreadsheets led to tedious manual efforts, resulting in data accuracy and integrity issues. The need for a more streamlined and efficient budgeting process was evident, as the existing methods were not sustainable for the growing demands of the business.

NAMI faced significant challenges with their previous budgeting software, which lacked the flexibility to keep up with the growing needs of the organization. The finance team struggled with version control and accountability issues due to managing over 70 spreadsheets with multiple contributors. This led to a significant amount of time being spent on collecting, distributing, and reviewing spreadsheets, leaving little time for actual analysis.

Manual data collection from 31 global offices was too time-consuming and potentially error-prone. Data security was an ongoing concern due to sharing budget templates and reports over email. Maintaining existing Excel investments was crucial for Cumming, a feature that competitors couldn't offer.

Tacala, the largest Taco Bell franchise owner in North America, faced significant challenges in centralizing their budgeting process across 277 retail locations over 13 different reporting periods. The existing system was plagued by version control issues between spreadsheets, SQL queries, and legacy software, leading to costly, time-consuming, and error-prone manual data collection. The need for a more efficient and accurate budgeting process was evident, as the current method was not sustainable for a company of their size and complexity.

The month-end close process at Capstone Infrastructure was plagued by manual data collection and reconciliation against printed spreadsheets. This manual data entry and consolidation were becoming increasingly time-consuming and error-prone. The overall process lacked version control, an audit trail, and data accuracy and integrity, making it difficult for the company to ensure reliable financial reporting. The inefficiencies in the process were causing delays and increasing the risk of errors, which could have significant financial implications for the company.

Navigating a system of competing interests: students, alumni, donors, regulators, etc. Accreditation board mandated closer ties between annual budget and strategic plan. Budget to actual reporting process was too manual and time-intensive.

The Finance team at a leading private university faced significant challenges in managing their budgeting process. They had to create and distribute dozens of spreadsheets to hundreds of organizational departments. These spreadsheets were then completed and emailed back to the Finance team, who manually consolidated them over several weeks. If the total budget was not balanced at the end of this process, spreadsheets had to be re-distributed and re-collected via email. This manual process increased the likelihood of user errors going unnoticed and required extensive communication through emails and phone calls. Additionally, there was a need for better control and insight into user activity, as well as improved data accuracy and visibility.

The finance team of a leading North American mining company faced significant challenges in managing their forecasting data. All forecasting data was stored in a single, complex workbook that was prone to being lost or damaged. The use of uncontrolled spreadsheets allowed unauthorized changes to data, formulas, and calculations, making it difficult to track the status of the forecast or determine which user made specific changes without exchanging emails or phone calls. Additionally, making real-time changes to the forecast was cumbersome because relevant information was scattered across disparate spreadsheets that required manual sorting and review.

The Finance team was manually distributing and collecting Excel spreadsheets from hundreds of users across more than 200 departments, leading to email overload and issues with version control. Managers had no insight into the process of data collection; it was difficult to know which users had started entering their numbers, which had finished, and which needed assistance without sending emails and waiting for a response. A small team manually copied the data contained in user-generated spreadsheets and pasted it into Oracle’s front end to create reports. The abundance of manual work extended the budgeting process by weeks and increased the possibility that human error would negatively impact budget numbers and the firm’s bottom line.