Finance & Accounting (F&A)
Procurement
Human Resources (HR)
Customer Experience (CX)
Facilities Management
Insurance Operations
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Learn MoreIn a previous role I was actively involved with identifying and implementing dashboards and reports tracking key sales department metrics and KPIs for enterprise-size customers as well as high-tech growth companies. These included recognizable examples such as opportunity conversion rate, average deal size and sales velocity (length of time to close, won or lost). Wind the clock forward and in my role as an industry analyst I now talk to customers and have a wider view of the market.
It is unfortunate that business-focused digital communications are sold under three different headings: Contact Center as a Service (CCaaS), Unified Communication as a Service (UCaaS) and Communication Platform as a Service (CPaaS). (And that just counts the cloud options—let us acknowledge the huge, continuing, installed base on premises.) These are terrible ways to describe complex, varied and overlapping offerings.
ERP systems have been the central nervous system of enterprises for more than three decades, handling business-critical process management and recordkeeping. While their basic outlines are unchanged, today’s systems are far more capable in their functional depth, adaptability, usability and manageability. Especially for cloud-based systems, they are far easier to maintain. Decades of refinement and focused development to support specific industries, and even specialized categories within these industries, have increased their utility while decreasing the total cost of ownership, especially in implementation expense and maintenance. Artificial intelligence (AI) is the latest supporting technology to increase the business value of the software. So, when considering replacing existing ERP software, it’s most important to understand and evaluate how a new system can add to the capabilities of the incumbent and how to manage the organizational change that will become possible and necessary with that change.
Compensation practices are currently experiencing a substantial transformation, driven by evolving workforce expectations and rapid technological innovation. This shift is fundamentally reshaping how organizations approach rewards and recognition for workers. Technologies like data analytics enable more precise and personalized compensation management strategies while also fostering greater transparency and equity in how performance is measured and rewarded. These changes reflect a broader effort to adapt compensation practices to meet the dynamic needs of today's workforce and maximize technology to optimize every aspect of rewards systems.
Spring and fall are conference seasons, and this spring I was fortunate to be invited to several software provider events that are part of my coverage of the Office of Revenue.
And while artificial intelligence (AI) and generative AI (GenAI) were front and center, there were other announcements where the focus was more on the potential changes that these technologies would enable within enterprises and their revenue teams.
