As we continue to learn with the accelerated advances in technology and a sharper focus on business agility, corporate leaders must demonstrate incredible flexibility in adapting rapidly to a host of dynamics that have redefined how they engage with customers, vendors, and their own talent. Just as businesses must evolve, so too must managed services providers (MSPs). They can no longer sustain progress as intermediaries focused on cost containment alone. MSPs must become agents of order, process optimization, efficiency, automation, agility, and workforce strategy in an era of extreme disruption. The question facing them is “how?”
The Ongoing MSP Dilemma: Evolution or Extinction
In 2019, Staffing.com posed this question to industry thought leader Christopher Dwyer, the senior vice president of research at Ardent Partners. The conversation at that time illustrated a conundrum that modern MSPs still confront: extinction or evolution.
“Unless the MSP can evolve to meet the top needs of enterprise clients, they will become extinct,” Dwyer said. “However, meeting these needs is not as easy as adding services. There are significant challenges that the MSP must overcome.”
In particular, Dwyer’s 2019 assessment of “dinosaur solutions” was a prescient foreshadowing of the challenges that exist in 2023 — the idea that MSPs are “old school” relics from the staffing industry’s former glory days: “Younger executives who are used to today’s fast-paced technology and hell-bent on agility and innovation often reject solutions from the past. For the MSP to survive, they will have to show that they are not the MSP from yesteryear but are agile and innovative themselves.”
MSPs are struggling to find ways of reinventing themselves, staying relevant, and progressing alongside the needs of both business customers and staffing providers. Innovation, at its heart, isn’t simply rolling out new platforms, repackaging solutions under freshly coined buzz words, or presenting answers to questions no one asked — innovation is solving problems. Having program guardrails, compliance oversight, standardization, and workforce curation — particularly in the wild west of direct sourcing — remain essential components; clients still find value in intermediaries who deliver on these practices. Yet seismic shifts in technology and business necessitate the need for MSPs to match the speed of evolution in that flow. The good news is that there are a variety of ways MSPs can achieve those goals.
Innovation Strategies MSPs Can Leverage
Embracing New Technologies
The world of staffing is changing rapidly, and new technologies are emerging all the time. MSPs that embrace these new developments and use them to improve their service offerings will stay relevant. For example, the adoption of AI and machine learning can help improve recruitment and matching candidates to job roles.
Expanding Service Offerings
MSPs should consider expanding their service offerings beyond traditional staffing services. This could involve offerings centered on training and development programs, HR consulting, diversity and inclusion consulting, and workforce planning and management services.
Building Partnerships
Building strategic partnerships with other organizations can help MSPs stay relevant. For example, partnering with a technology company to offer a staffing solution that incorporates their technology, or partnering with a training provider to offer skills development programs. As we outline in our eBook New Talent Strategies for Our New Normal, for example, MSPs have excellent opportunities to align with and leverage Massive Open Online Course (MOOC) programs to enhance ongoing education and development.
Focusing on the Candidate Experience
The candidate experience has become undeniably imperative in the success of staffing programs, affecting retention as much as candidate attraction. But ensuring a delightful candidate experience shouldn’t be left to staffing providers alone. Part of the experience speaks to culture, and MSPs are better positioned to explain and showcase the benefits of their clients’ values, missions, and operating environments. MSPs that can collaborate with their staffing partners to deliver a positive candidate experience — through streamlined processes, personalized communication, and feedback — will be more likely to attract top talent and retain existing talent.
Emphasizing Diversity, Equity, Inclusion, and Belonging (DEIB)
Enhancing DEIB efforts persists as one of the foremost industry trends. MSPs that can demonstrate a commitment to diversity and inclusion through their recruitment practices, training programs, and company culture will be more likely to attract and retain top talent. However, it’s also important to approach DEIB with sincerity and a genuine understanding that diverse perspectives in the workforce lead to unique ideas, innovation, and experiential intelligence of how to market to diverse communities. DEIB is as much a responsible workforce philosophy as it is a rewarding business doctrine.
The Crucial Role of Automation and Technology
By all accounts, the topic of AI has grown from simple chatbots to a sweeping and more encompassing system of data retrieval, analytics, research, business intelligence, process optimization, and overall efficiencies that avail the work of human users. And the latest developments in generative AI models have taken the world by storm. For good reason. Overall, AI can help recruiters save time, increase efficiency, and make more informed decisions when matching candidates to job roles. By leveraging the power of AI, recruiters can identify the best candidates for the job, leading to more successful hires and better business outcomes.
The latest iterations of AI and machine learning have tremendous potential to augment hiring processes for the staffing partners in an MSPs technology ecosystem. Access to a vendor management system (VMS) or comparable human resource information system (HRIS) that has incorporated AI will bolster the effectiveness of staffing providers in the program.
Automated Screening
AI-powered tools automatically screen resumes and job applications, saving recruiters time while increasing efficiency. The system can quickly identify qualified candidates based on job requirements, such as experience, education, and skills.
Enhanced Candidate Sourcing
AI helps identify candidates who may not have applied for a particular job but possess relevant skills and experience. The system can analyze social media profiles, professional networking platforms, and other public sources to find potential candidates who may be a good fit for a specific role.
Predictive Analytics
AI algorithms can analyze data from past hiring decisions and identify patterns that lead to successful hires. This helps recruiters make more informed decisions when evaluating candidates, increasing the likelihood of finding the right fit for the job.
Refined Chatbots
Today’s AI-powered chatbots can interact with candidates and answer their questions in more conversational and natural language, providing an enriching personalized experience. Chatbots can also help schedule interviews and follow-up communications, allowing recruiters to focus on more strategic tasks. The most recent breakthroughs in generative AI have created an interactive and conversational system for answering questions, analyzing data, and even generating original content or code — all based on simple inputs. Users can get more information, more accurately, and more easily by talking to the AI as though they were texting a colleague. Specific keywords, terms, and phrases are not required. AIs have learned to recognize and respond to normal speech.
Bias Reduction
AI can help reduce unconscious bias in the recruitment process by removing personal identifiers, such as name and gender, from resumes and job applications. This helps ensure that candidates are evaluated based on their skills, merit, and experience, rather than factors such as race, age, or gender.
Incorporating AI into VMS Platforms
Incorporating AI and machine learning into existing VMS platforms can dramatically improve their inherent efficiencies. And because VMS is the “operating system” that drives MSP program automation, AI can make a holistic difference when applied strategically.
Candidate Sourcing and Matching
VMS platforms can leverage AI and machine learning algorithms to analyze resumes, job descriptions, and candidate profiles to identify the best match for a particular job role. These algorithms can take into account factors such as skills, experience, education, and job performance data to make more informed matches.
Predictive Analytics
Machine learning better empowers VMS systems to analyze historical data on job orders, candidate submissions, and hiring outcomes to identify patterns and predict future staffing needs. This can help improve workforce planning and enable more proactive staffing.
Talent Pool Management
AI and machine learning can be used to analyze the skills and experience of a company's existing talent pool, making it easier to identify internal candidates for open positions. This can help reduce recruiting costs and improve employee retention.
Chatbots
VMS platforms can incorporate AI-powered chatbots to handle routine tasks such as answering candidate questions, scheduling interviews, and providing feedback. This can help improve candidate experience and free up recruiters' time to focus on more strategic tasks.
Performance Tracking
VMS platforms can use machine learning to analyze performance data and identify trends and patterns that can be used to improve employee performance and inform talent development initiatives.
Integration AI into VMS
Of course, even with the value of leveraging AI to refine and expand a VMS’ existing features, there’s the question of how to integrate AI. While there’s no one-size-fits-all approach, there are some best practices to consider.
Identify Use Cases
The first step is to identify use cases where AI can add value to the VMS platform. This could include candidate matching, talent pool management, performance tracking, and workforce planning.
Collect and Process Data
To enable AI algorithms to learn and make predictions, VMS platforms need to collect and process data from multiple sources. This could include resumes, job descriptions, candidate profiles, performance data, and historical staffing data.
Develop AI Models
VMS developers should consider working with data scientists and machine learning experts to build out AI models that can analyze data and make predictions. This could involve developing algorithms that match candidates to job roles, predict future staffing needs, or identify talent development opportunities.
Integrate AI Models into the Platform
Once AI models have been developed, they can be integrated into the VMS platform. This would generally involve implementing new features or updating existing ones to incorporate AI predictions and recommendations.
Test and Refine
After AI models have been integrated into the platform, VMS developers need to test and refine the models to ensure that they’re producing accurate and effective results. This typically involves testing the models on real-world data and adjusting the algorithms as needed.
Monitor and Update
VMS providers must monitor the performance of AI models over time and update them as needed to ensure that they continue to provide value to users.
MSPs Have Incredible Opportunities Ahead
The MSP model endures as a viable and popular workforce management solution for enterprises across industries. MSPs that concentrate on being adaptable, innovative, tech-savvy, and focused on delivering high-quality service to both clients and candidates will have no problem staying relevant in an ever-evolving industry.
