Knowledge industries, like the IT industry, deliver projects or services involving various digital technologies to their clients in diverse industries and institutions. Hundreds or thousands of people with highly specialized skills and domain knowledge work on these projects. Operations of large IT companies take place in many locations across the globe.
Managing resources effectively is the most crucial success factor for IT companies and their clients. This is true in other project based businesses like engineering and consulting as well.
Generative AI technology has taken the world by a storm. It has shaken many business models. This article explains how AI can transform resource management, help implement best practices, cut manual efforts, and simplify complex queries related to resources.
Before looking at how AI can improve resource management, it is essential to understand the complexity and the scale of managing resources in IT companies.
Managing large skilled workforce
Knowledge industries, like the IT industry, deal with skill-hours at the most fundamental level. One must be able to answer questions like
‘How many hours of ‘Java programming’ and ‘ Fintech experience’ are needed?’
‘How many of them are available for deployment?’
Projects, tasks, hours of work, people – everything is connected with skills, competency levels, and capabilities.
Skills must be defined precisely. Skill definitions should be uniform across an organization.
Companies need an up to date skills database of their employees and its real-time skills inventory to find, allocate, plan, train, and recruit resources with requisite skill sets.
Since traditional enterprise software doesn’t cater to the scale and complexity of resource management, managers use a combination of spreadsheets and standalone software for the work mentioned above.
It is impossible to perform all resource management functions reliably and quickly with such a fragmented approach.
Data, the culprit
More precisely, the culprit is the data scattered across the organization – in resumes, payroll, executed projects, training, etc. The culprit is mismatched data e.g. skill definitions in resumes, project requirements, and HR systems can be different. The culprit is outdated data e.g. skills database isn’t updated or the skills inventory doesn’t reflect recent allocations to a new project.
The solution is technology for end-to-end integration of existing software.
Adding AI in fragmented workflows won’t help much.
There are two simple points to consider before applying AI techniques:
- If your data is not validated, the results will be invalid too.
- AI needs guardrails of human expertise and accountability at both ends – input and output.
Kytes PSA-The Ultimate solution
For a clean, validated, single version of data, Kytes, a Professional Services Automation (PSA) software stands out. Kytes is an industry-leading AI-enabled PSA software. Kytes streamlines end-to-end opportunity-to-cash cycles for strategic impact in all areas of enterprises. Kytes’ Resource Management module is the best-in-class solution for all resource management needs besides those covered in this article.
The Resource Management module has capabilities like optimizing resource allocation, bench optimization, and actionable resource forecasting. It supports the operational needs of managing on-contract resources and resources in ODC(Offshore Development centers) and resource shared support services centers.
The Resource Management works seamlessly with other modules on the Kytes PSA platform like Opportunities & Estimation, Project Management, Leave & Timesheets, Project Financials, Reports & Analytics, and Enterprise Integration.
Supercharging Resource Management using AI
Kytes Resource Management module working on the PSA platform has already been well accepted as a standard solution in the services industry. Various AI agents embedded in Kytes’ tried and tested workflows raise your resource management to another level. Here are a few AI use cases.
Constructing the skills taxonomy
You can manually configure the taxonomy using Kytes’ in-built templates. Kytes AI makes it simpler. The AI agent scans your finished projects data resident in Kytes PSA and prompts you with a selection of skills to include in your taxonomy. You have a lot of information about skills used in your projects. Kytes AI generates your ‘universe of skills’.
Finally, it is your judgment, but the AI takes the drudgery out.
Populating and updating your skills database
The most difficult step in constructing a skills database is to populate employee records with validated skill sets. Your skills taxonomy will be useless with this step.
Kytes AI shines here. It provides a list of probable skills of each employee through various methods – scan their resumes, scan their project work, or scan their skills from an external platform like Linkedin. Linkedin, for example, has a feature of ‘endorsed skills’, which can be a good starting point.
Employees get prompts for their skills on their dashboards. They can accept or edit them. Their supervisors can approve or send back the skills information for modification. Kytes Resource Management module provides workflows for authentication of skills depending on the competency levels e.g. ‘Proficient’ or ‘Expert’ levels typically need approval by an internal or external expert.
Maintaining an up to date skills Inventory
Kytes combines data from skills database, project scheduling, and resource allocation to determine skills inventory showing allocated, free, or skills in short-supply at any time.
For example, you instantly find out how many skill-hours of ‘Java coding’ at ‘advanced level’ are in the organization, how many have been booked, and how many are free or in shortfall.
Kytes AI can help your decisions through what-if scenarios. Resource allocation is an iterative process. Power of AI is best used here.
Search & Match
The proverbial ‘searching a needle in the haystack’ – searching and matching resources with multiple criteria becomes very easy now. Your real-time skills inventory is searchable at the most granular level.
Kytes AI agent makes it even more powerful – it can handle new combinations of search criteria without any fuss.
Resource demand forecasting
Kytes’ CRM module brings in demand for various skill-hours from your high-confidence deals pipeline. When it is combined with the skills inventory, Kytes AI is ready to work out what-if scenarios and help you spot potential skill gaps. You can initiate training and talent acquisition to bridge any gaps.
Career planning
Your employees can see their skills upgrade journey and find what more they need to learn to achieve their career goals. There is no better incentive for people to learn and their skills.
There are many more ways in which Kytes power your resource management using AI.
Key Benefits
Kytes helps you achieve goals mentioned in the beginning of this article.
Its benefits are visible every day. Your project managers quickly identify resources, negotiate their release from others, saving hours or days of frustrating work. Your resource management group saves time in rationing scarce resources. Your talent acquisition team gets enough headstart to find fresh talent. Kytes meets global standards of data security and privacy.
Conclusion
Kytes with in-built AI agents helps you in deploying powerful resource management techniques. You can overcome traditional hurdles, streamline processes, and make data-driven decisions with ease. Kytes supercharges your resource management. Kytes helps you to improve customer satisfaction, revenues, and employee engagement.
Contact us at [email protected] for more information and a demo.
