Six Building Blocks for Effective Benchmarking
There are six essential building blocks that need to be applied to elicit meaningful and insightful recommendations.
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Learn MoreSelf-service has changed immensely in recent years. It has gotten better, qualitatively, in delivering answers and resolutions to customers. But it has also gotten extremely complex, relying on a basket of new technologies to achieve results. It helps to look at it through the eyes of the three main constituencies that are affected by it: customers, contact centers and the businesses they sit in.
Enterprises are embracing the potential for artificial intelligence (AI) to deliver improvements in productivity and efficiency. As they move from initial pilots and trial projects to deployment into production at scale, many are realizing the importance of agile and responsive data processes, as well as tools and platforms that facilitate data management, with the goal of improving trust in the data used to fuel analytics and AI. This has led to increased attention on the role of data operations (DataOps) and its role in the application of agile development, development operations (DevOps) and lean manufacturing by data engineering professionals in support of data production. I assert that through 2026, more than one-half of enterprises will have adopted agile and collaborative DataOps practices to facilitate responsiveness, avoid repetitive tasks and deliver measurable data reliability improvements.
Until recently, dedicated consolidation software had been a sleepy category. First introduced in the 1980s as a tool designed to run on personal computers (freeing the accounting department from reliance on its IT department), offerings basically achieved feature and function parity by the next decade. The last major technology innovation—moving the software to the cloud—began in the mid-2000s. Cloud-based software reduces the cost and complexity of ownership, making dedicated software a more practical and attractive option for companies with between 500 and 2,500 workers.
The evolution of HRO has turned into a revolution. Two decades ago, we saw the first transformational HRO deals involving multiple HR processes. These were focused on the consolidation and standardization of transactional HR activities delivered from centralized service centers, using a single HCM application that replaces fragmented islands of HR technology. The primary aims were the modernization of transactional HR systems, compliance assurance, and the reduction of the cost of HR functions through efficiency savings and labor arbitrage. However, back then, HRO solutions only partially achieved improved and insightful workforce management.
In the past year, as the world continued to recover from the challenges and restrictions implemented to manage the COVID-19 situation, leading life science companies and the providers that support them made significant advances in incorporating technology solutions into the DNA of their operations. This sector has historically been reluctant to embrace innovative approaches at scale, but the pandemic has catalyzed a permanent change. For starters, the pandemic made many formerly standard processes, such as in-person patient visits and justin- time supply chain practices impossible, which created an unprecedented demand for innovative solutions. Leading solution providers not only intervened with existing technology solutions but also demonstrated their readiness to collaborate, innovate and invest with greater flexibility and customer-centric focus than ever before.