Functions Driving HR Business Intelligence
Executive management is the number one driving force of business intelligence implementation. The main reason being that operational decisions are a top-down process wherein senior leaders are the ones who decide the priorities. Therefore, it’s not a surprise that executive considerations lead the charge among the functions and roles responsible for deploying HR AI across organizations no matter the size. In smaller organizations, there aren’t better evaluators available without reaching out to costly external consultants.
As the size of operations increases, executives who receive analytic reports relinquish control over business intelligence decisions to focus on operations requiring examination at their leadership level.
Therefore, in middle to large organization sizes, upper and middle-level leaders are the key business intelligence decision makers and managers. Smaller organizations are pressed to carefully budget for AI, while larger organizations with bigger budgets have less flexibility to make adjustments in their BI implementations. The main HR management considerations for all organizations are recruitment, onboarding employees, developing talent from within, retention, and managing the overall budget around human capital management.
Fortunately, there are machine learning and artificial intelligence solutions for all facets of HR these days. Most of the solutions available are affordable and supplement accurate analytics in place of human judgment or bias.
The average cost for recruiting an employee is six to nine months salary and that cost can add up, causing budget leaks in organizations of all sizes, if recruiting practices don’t line up with the needs of the roles filled. Collecting and sorting through the resumes for open positions can compromise the quality of candidates due to losing resumes in inboxes, overlooking qualified candidates in efforts to get through every resume received, and losing resumes in the document storage process.
The time that it takes to interview and select final candidates is just as vital as sorting through resumes to identify the most qualified candidates. Interviews are pivotal in providing candidates with more information on the organization and positions being filled. Though interviews may go well, references are often times the final determining factor of who is selected for the job. Recruiting AI is helpful in screening resumes for keyword skills, experience, and education, automating communication with candidates, using recruiter bots to conduct interviews, and assisting with job offer communication.
The most valuable way that organizations invest in their greatest asset – employees, is through training and onboarding is the first level of training that should be offered. Employee onboarding not only introduces new team members to the culture and processes used to keep the workplace functional but also helps new hires feel valued. Everyone wants to show up to work for an organization where they feel they are wanted and needed.
Introduction to organizational culture, mentorship, onboarding follow up, clarifying goals and objectives, total team participation, buddy systems, and external support should be the focus during the onboarding phase of HR management. Through standard onboarding procedures, businesses can measure the amount of continued training necessary for a team member to succeed. Onboarding AI can answer common new hire questions and provide information through resources that support cultural competency programs.
Development and Training
Learning new skills is a motivating factor for team members to remain on the job and enjoy the work they engage in on a daily basis. Successful organizations offer development programs to their team members, helping them realize career goals and track their long-term career path within the company. Training facilitates and fortifies employee loyalty, and professional development of teams leads to company profits. Talented team members crave advancement and are grateful for support during that process. Young employees in particular want training and mentoring in order to gain new skills.
A comprehensive employee development plan considers business goals, cultivates communication between leadership and team members, differentiates between potential and readiness, uses diverse development and training assessment tools, and creates 360 wraps around strategies for before, during, and after the training takes place. Career development AI capabilities can scale programs and company coaching to customization necessary for every employee. These tools often times are paired with employee relations communication platforms.
While there is no one size fits all solution for retaining employees, there are guidelines and standards that organizations can implement to reduce turn over. It’s not enough to recruit the right team members, onboard them, and assist in their career development. Salaries, benefits, and incentives are additional merit-based compensations used to influence people to remain with the company once hired.
Retention strategies should include benchmarking employee retention rates, using employee retention processes that work, implementation of reimbursement arrangements for costs such as health, education, and/or childcare, personalization of employee benefits where possible through flexible schedules, conference and event attendance, consideration of employee feedback, rewards and/or celebration programs, and conducting exit interviews. Employee retention AI and machine learning can pull together all data necessary to evaluate individual and team performance. Business intelligence software that serves to limit bias during performance evaluations is key in retaining team members.
HR budgets begin by collecting data across several measures and making sure that funds are spent in discretionary fashion to cover the necessary expenses. Some of the areas an HR budget should cover are the number of employees projected for current and following year, benefit costs and projected increases, the projected turnover rate, costs incurred in the operational year, new benefits and/or employee recognition programs planned, and other changes in policy, business strategy, law or regulation that may impact costs.
HR budgeting business intelligence tools have their own unique rules about storing information on the cost of salaries, training, uniforms, staff welfare, and new employee set up such as laptops and software. Implementing software designed to transform data into organized budget reports is required to successfully manage any business.
Start-Up Organizations (1-100)
The primary concern of startup organizations is not only acquiring talent but developing that talent through agile operations management while implementing employee retention practices. Businesses of this size cannot afford to lose and retrain employees as the average cost to hire and train an employee is roughly 50%-60% of a team members salary. One way for startup companies to prevent spending excess funds on recruiting employees who most likely won’t stay is by deploying AI software at a cost of around $550-$1000 per year.
That’s a fraction of the cost to hire and train new staff no matter the size or your organization. Employee retention is the other primary focus of startup efforts means that spending a percentage of HR costs on recruiting software is explicitly beneficial to team growth. Tools used to retain employees of organizations this size can be developed from within utilizing databases and spreadsheets until revenue stabilizes.
Small Organizations (101-1,000)
Organizations who survive the initial start-up phase to increase their size to that of a stable small business have critical HR management needs surrounding budgeting and employee development. It’s reasonable to ascertain that smaller businesses can implement BI initiatives in shorter timeframes compared to their larger counterparts, due to greater agility stemming from fewer employees and fewer complex processes. Learning Management Systems (LMS) implementation is recommended for small businesses to assist with employee development.
These systems not only store and sort information by an individual employee but assists with tracking skills and evaluating progress. The possibility of small stabilized organizations to pervasively deploy HR AI adds to their ability to realize tangible business intelligence benefits quickly.
Mid-Size Organizations (1,001 – 5,000)
Businesses this size continue to struggle to successfully implement business intelligence. The HR concerns that midsize businesses need to focus on are onboarding and employee retention. Onboarding can be chaotic enough for small businesses, but midsize businesses are at greater risk of having employees in the workplace that have varying ideas on how to identify the organizational objectives. Succinct onboarding tools with departmental or role function resources can assist employees in locating information without delays in completing their routine tasks. Unfortunately market study of organizations this size report that only 21% of their analytics initiatives are a success.
This indicates that it’s better to implement HR business intelligence at a smaller company size with plans to expand the software toolkit as the organization grows. Upper and middle management are targeted to deploy business intelligence in midsize organizations. As the workforce increases, more upper and middle management level leaders are required to take on AI-related bottom line duties. Although revenue may be robust, midsize organizations lack the abundant resources of large companies as well as the flexibility of smaller companies, which is reflected in the reduced AI adoption rates of organizations with between 1000 and 5000 employees. HR automation failure indicators center on the need for organizations to change the staff and leadership culture prior to implementation.
Theoretically, it’s more difficult to change the culture of a midsize than smaller organization and more risky to attempt to change the culture of a midsize than large organization. ( http://www.personneltoday.com/hr/five-reasons-hr-software-implementations-fail/ )
Large Organizations (5,001-10,000)
Larger organizations, within the 5000-10000 employees category, can afford to have the most aggressive business intelligence expansion plans. Organizations of this size are more likely to have huge budgets to cover expansive infrastructure and operational costs. It’s safe to assume that larger organizations generally have the necessary funds to support dedicated machine learning departments that often govern AI on behalf of individual departments and entire organizations. Relatively, organizations of this size tend to identify a greater overhaul of operations as a priority.
This reduces the resistance that organizations of smaller sizes may face when implementing HR AI. It’s interesting to note that large organizations have the capacity, funding, and ability to hire outside consultants to manage complex implementation strategies that could take years to complete. ( https://blog.hrps.org/blogpost/Where-Big-Data-and-AI-Might-Lead-HR-in-2017 ). Therefore, any and all scopes of HR AI implementation is recommended for large organizations where systems are missing or are outdated. Despite having larger HR budgets, the adoption rates of business intelligence by larger organizations are significantly lower than that of smaller organizations.
Overall, some degree of value is derived from HR AI across organization size. Almost 90% of all organizations, regardless of size, reported their business intelligence implementations as somewhat successful. When analyzing the degree of HR AI penetration by size, organizations on both extremes of the scale, the smallest and largest companies, have experienced the highest rates of business intelligence implementation success. While smaller organizations have a clear edge in their ability to implement business intelligence more pervasively, larger organizations have significant resources at their disposal. Hopefully, this information informs organizations on what to expect when implementing HR AI.
At the very least, start-up businesses should consider implementing business intelligence accordingly in order to avoid organizational chaos at the HR level. Resolving employee management needs can be costly, but leaving human resource management concerns unresolved can cost organizations everything in the longer run.