Analyst Perspectives

One of the many things I learned while I was accountable for multiple HCM systems and tools deployments in my pre-analyst and advisor days relates to crafting what I referred to as a “winning business case.” In this context, I define “winning” as not just securing the funds, but actually realizing the expected benefits and ROI that underpinned the major elements highlighted in the business case. Critical to all this, as I came to learn after a couple of HCM systems implementations, was the ability to not only achieve but sustain adoption and usage.

I’m not referring to obligatory or casual usage that emanates from corporate mandates attached to standard HR processes and tools. A winning business case generates the type of usage where business benefits to the individual user are so clear and obvious that two things invariably take place: the use of unofficial and non-sanctioned (“rogue”) spreadsheets and other HR data repositories voluntarily wane and ultimately cease entirely; and the vast majority of the new system’s impactful capabilities are known, used and enjoyed, unlike the unfortunate, all-too-frequent scenario with enterprise software applications where users either forget what they learned during system training, or were never even exposed to important product capabilities or user experience nuances in the first place.

Maximizing the benefits of HCM systems assets and investments, as my teams and I came to learn, started with explicitly highlighting all of the dependencies that had to be accounted for and effectively managed in order to leverage the compelling strategic and operational advantages we had envisioned. These included improved attraction and retention of top talent, more effective and timely decision support, actionable insights and guidance on a broad range of workforce-related opportunities and risks, enhanced productivity and organizational agility, and offering a superior employee experience. Indeed, a clear pattern became evident: When business case dependencies were explicitly highlighted and frequently reinforced in communications, change management, and process improvement efforts surrounding the new system, the organization considered the business case to be adequately thorough and realistic, and therefore the critical decision tool it was intended to be. When dependencies were not addressed directly in this manner, the negative consequences often extended to future proposed spending on HCM initiatives of any kind being met with cynicism and spotty support.

Since data is the foundation of all enterprise software applications, the ability to always ensure high data integrity should be priority one. System functionality that included processes such as robust front and back-end data validations, suspected error or missing data alerts and exception reports was simply not enough. Frankly, even adding today’s AI/ML-based error detection capabilities to the mix would not ensure the highest level of data integrity and reliability. The missing essential component is a combination of well-defined people data ownership and accountabilities across the enterprise, from employees to business leaders, and year-round training around and reinforcing of appropriate data management processes, both standard and exception driven. Before data ownership rules were established in relation to every data field, and associated expectations clearly communicated, data reliability efforts were typically centered around the core change management principle of “what’s in it for me” using levers with employees such as a greater ability to support their career goals, and with managers likely making better decisions with more timely and accurate information. Of course, these behavioral levers were still employed, just backed by everyone in the organization knowing their role in ensuring people data quality and signing-up to fulfill it as a matter of formal corporate policy.

Data integrity has many dimensions. One is the ease with which HR readily uses and leverages “people data” in conjunction with data from other functional areas and their supporting systems. As conveyed in the assertion or prediction from my 2021 HCM Market Agenda, by 2023, one-third of HR and Office of Finance leaders will co-sponsor initiatives to better integrate their functions’ data and analytics in real time, resulting in improved organizational agility and labor cost management. It should also be noted that today’s enhanced ability to curate data and other non-structured information quickly from heterogeneous sources within and outside the organization can be a double-edged sword. More data means more processes and more education around how to best harness the power of that data and content. Even something as straightforward as training around data standards and definitions, or the rules underlying headcount reporting, should be viewed as a business imperative when mining the value of all the high-impact people data potentially available today.

A word of caution for all the HCM systems enthusiasts (users, advocates and sponsors) reading this: In some ways, the set of data-, systems- and process-related dependencies, some of which are highlighted above, while others might relate to skills needed or other aspects of organizational readiness, are not static, but a growing list. As highlighted in another of my 2021 HCM Market Agenda assertions, by 2024, over one-third of organizations will use HR-focused intelligent virtual assistants (IVAs) that serve as “digital hubs” to interconnect to other IVAs, applications and knowledge systems to support managers, not just employees. IVAs fueled by the ML phenomenon have only recently become prevalent as an extension of the HR team’s human contingent for many business entities. Given that HR departments typically only comprise roughly 1% of the total workforce, IVAs have been a real boon for HR departments and service desks trying to scale to meet all incoming questions. The caveat is a potentially countervailing phenomenon known as “HR bot proliferation” that arises when multiple systems are utilized with their own bot as one of the primary user interface channels. Organizations must include this potential dynamic when coming up with their list of dependencies that could potentially undermine ROI on an HCM systems deployment. I see the notion of a digital hub or “uber bot” as eventually being the best — or, perhaps, only — way to mitigate this situation.

HR teams or leaders that put forth a well-conceived business case aimed at securing sustained support and funding for their new system should be sure to pair particular business benefits with their corresponding operational (people, process, data and technology) dependencies, as well as a plan for proactively managing them. The one that often undermines HR/HCM enterprise software deployments is the need for a multi-pronged approach for ensuring data quality and reliability. This approach should start with forging a common understanding and mindset that everyone across the organization has some responsibility for achieving this critical goal.