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Skill Recommendation Engine

AI-powered HR Use Case: Skills Recommendation Engine (SRE)

In a world permeated by big data your business needs to be data-driven and evidence based. This is considered as the prerequisite to evolve with the redefinition of individual tasks driven by automation. A good workforce is key to success. Managing it becomes increasingly difficult facing the complexity of data represented by your resources’ qualification.

Analyze, Broaden and Empower your view on professional skills!

The Skills Recommendation Engine (SRE) enables you to make better, faster and more cost-effective decisions based on AI.

SRE helps you to

ANALYZE

the requirements of your

expert-areas

BROADEN

the skill-set

of your talents

EMPOWER

the efficiency of your resource mapping

Let the power of AI enable you to manage the intelligent knowledge extraction of data and use our Skills Recommendation Engine to push your resourcing strategy towards a new level.

Gather the big picture of skills and their possible correlation to each other to make a sound decision considering your resources. Foresee the development of expert profiles and strategically align your portfolio with the expertise of your talents.

Obtain both a global overview of your talent pool and a detailed insight into the skill-sets of your expert-areas in order to increase the value of your employees and enlarge the range of potential projects.

Expand your view on resource assignments and optimize your resource capacity while increasing the satisfaction with the right matches.

No matter where you are

on your business journey, Devoteam can support you with AI-powered solutions.

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Intelligent Automation

Predictive analytics, optimisation, enhanced capabilities

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Challenges

Business workflows commonly suffer from ineffective or inappropriate, non-optimal, and reactive utilisation of business resources.

Due to inconsistent and partially unpredictable performance of human operators, business processes suffer, as common human error introduces issues with the quality of service, in addition to being an unreliable production resource and potentially ineffective in comparison to algorithmic approaches to task performance.

Furthermore, there is generally a reactive management or operational mechanism in place, where problems are dealt with as they occur, potentially ignoring signals that would have indicated imminent issues or process breakdown.

Solution and benefits

When incorporating automated information processing, businesses can take advantage of cost-effective, fast, and highly consistent quality of delivery on product or service. By doing so a firm can optimize the reliability and accuracy of service. Through automated information processing, the workforce is partially relieved from repetitive work, thereby decreasing cost for the firm. In addition, such resource-optimized delivery through automated information processing is faster, more reliable, and more consistent.

In addition, when dealing proactively with impending business process breakdown by detecting the appropriate signals, delivery can be kept on target and without interruption of service. Not just detection of known signals, but also new signals can be discovered through machine learning, where detection automatically becomes a learned part of the solution. By dealing proactively with impending issues, resource allocation is optimized, by ensuring that support processes are performed under circumstances of the organisation’s choosing: When and where is convenient rather than under duress. This implies that business process maintenance is performed more cost-effectively and accomplishing higher service quality through decreased downtime and service issues.

Our Clients

Case: Liberty Global

Case: Proximus

Case: Deutsche Telekom

Case: Telenet

Case: API Restauration

Case: BNP Cardif Airbus

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Offer overview

Offer overview

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