Research Topics

What does our latest data say about how to enable performance?

I'd like to see some research around comparing in-house L&D versus outsourced L&D - Looking at cost, effectiveness, distribution of in house vs outsource across different companies/industries, etc. L&D is getting pressured on cost and spending and those in the executive ranks who may not have as much familiarity with the capabilities of L&D may be looking to reduce cost. This research would provide L&D teams with data to support the most foundational question that executives might have "Could we achieve the same or better outcomes for less cost?"

Federated, Centralized, or Decentralized: which structure makes sense, and what roles belong in each?

The use of Generative AI in the workplace may level the playing field when it comes to skills. What will be the new category of KSA's needed to succeed?

Everyone's all a buzz about generative AI and its impact on HR Tech. But what is real and what is hyperbole? And what can we realistically expect to see coming soon? We will explore this and more in this report.

How are organizations truly enabling talent mobility, in each of the 5 models we identified in 2021?

As the economy works to find its footing, how are organizations making decisions about what talent is critical, and how to develop that talent?

What does the performance tech landscape look like? What are the trends in the space, and what should organizations be looking for when purchasing tech? This will be our Q3 2024 Tech Consortium webinar.

The 2020 murder of George Floyd kicked off a host of pledges by corporations to support DEIB efforts more strongly. Fast forward three years, and organizations have laid off DEIB leaders in droves, layoffs have disproportionately impacted employees from diverse backgrounds, and DEIB budgets (never large to begin with) have been slashed. What is a leader to do? This report is designed to understand the current challenges and how leaders might navigate them effectively, as they continue to support DEIB efforts.

Too often, organizations try to boost employee wellness by adding more to employees' plates: An app to interact with, a program to follow, a class to take. These efforts, though well-intentioned, don't address a fundamental and underlying driver of employee stress and burnout: There's just too much to do. This project would look at how organizations are simplifying, redesigning, and / or automating work to make workloads more manageable--and the effects those efforts have on employee wellbeing.

With high turnover and a tight labor market in many industries, many organizations face pressure to very quickly get new employees up to speed and performing at full capacity. This can only be done if employees know the right people, have access to the right information, and feel motivated to work well. Building on RedThread's existing research into the different types of connection that are important in organizations, this research will dive into how organizations can help employees form the right connections, quickly.

Organizations that put purpose at the center of what they do are experiencing challenges on a number of fronts: economic, social, cultural, and political. How are they weathering these challenges? What changes are they making? And how are these new dynamics affecting organizational culture and performance?

The recent Supreme Court ruling has resulted in greater caution among many corporations as they review their DEIB data and analytics efforts. This report will leverage RedThread's position as a confidential advisor to understand what organizations are really doing and how they are working to continue their DEIB work while being mindful of potential ramifications of their work.

There are tons of great analytics tech out there, but how do they all fit together? And how might a people analytics practitioner think about making decisions on which type of ecosystem to stitch together?

How should organizations consider their ethical responsibility when it comes to employee and company data?