Artificial Intelligence (AI) and Machine Learning (ML) have been more and more omnipresent in the fields of logistics, production, operations, and HR today for its capabilities to mimic human decision-making processes and efficiently perform tasks like humans. For talent acquisition, in particular, many organisations are moving towards integrating AI and ML to manage the recruitment process at a scale.

Having been at the receiving end of the cumbersome corporate talent acquisition process, Bipul Vaibhav together with his co-founders Anan Kumar and Kumar Sambhav, developed Skillate, an AI-powered platform that would make recruitment easy, fast, and transparent. Now available on SAP App Center, SAP customers can leverage the power of AI and ML in their hiring process with Skillate.

Skillate integrates with the SAP SuccessFactors Recruiting and Onboarding, cloud-based software that provides a comprehensive, guided solution to help recruiters and hiring managers source, engage, nurture, and hire the best talent.

Bipul Vaibhav, CEO and Co-Founder of Skillate, stated:

‘‘We are happy for our recruitment platform to integrate with SAP SuccessFactors solutions to save time and recruitment costs while offering a more transparent process for enterprises across sectors.” 

Skillate is a smart recruitment product to optimise the talent acquisition process by leveraging artificial intelligence and machine learning algorithms. It integrates seamlessly with any homegrown system and Application Tracking Softwares (ATS) such as SAP SuccessFactors and Taleo. The platform provides out of box integrations with a host of third-party applications to source candidates directly from Job Board – Monster, Indeed, IIMjobs and the likes. The integration with SAP SuccessFactors brings Skillate’s solutions to a global scale, reaching more industries and enterprises to improve hiring performance. 

As a partner in the SAP PartnerEdge program, Skillate is empowered to build, market, and sell software applications on top of SAP Cloud Platform.

AI Transforms Talent Acquisition

Leveraging AI, Skillate is able to perform HR recruitment tasks such as identifying, interviewing, and hiring the best candidates at scale. In a click of a button, Skillate‘s AI algorithm is trained with over 20 million diverse profiles to screen and shortlist resumes. 

Skillate features AI-based matching, state-of-the-art resume parser, intelligent chatbot, in-depth reports, and analytics. It has self-learning capability that customises the algorithm for each enterprise, giving it a unique capability to ‘Think like an experienced recruiter’.

The B2B solution utilises chatbot in combination with AI-powered matching in efficiently finding the best candidates, significantly reducing screening time and allowing the recruitment team to engage more with applicants. The chatbot also has the capability to schedule follow up interviews after the initial screening.

Optimising Value-Chain of Recruitment

The AI-based talent acquisition platform advances and transforms the hiring process, optimising the entire value chain of recruitment- from creating job requisition to candidate engagement. Skillate boasts to deliver the following: 

• 30{aa282f308afcc222aaa21b0478c79e01a8fedd01972e2180867097bd93930f22} lower cost per hire
• 50{aa282f308afcc222aaa21b0478c79e01a8fedd01972e2180867097bd93930f22} reduction in time to hire
• 85{aa282f308afcc222aaa21b0478c79e01a8fedd01972e2180867097bd93930f22} matching accuracy
• 100 {aa282f308afcc222aaa21b0478c79e01a8fedd01972e2180867097bd93930f22} industry agnostic
• 2.2 x candidate conversion 

Founded in 2016 as a start-up and a member of SAP Labs incubator progamme, Skillate’s customers now include big brands such as Sopra Steria, Saint-Gobain, OYO Rooms, L&T Construction, L&T Financial Services, and SoftwareAG.

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Channel Asia asked eight leading cloud computing experts based in Southeast Asia. They have shared that the abovementioned factors impact the market on top of the changing market dynamics in Indonesia and Singapore. This is creating an ecosystem of cloud providers that is more collaborative with VMware as the glue.

The cloud computing experts came from emerging startups and established technology providers. They represented the entire cloud ecosystem in Asia and had skills in platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure, Oracle, SAP, ServiceNow, and VMware.

Workloads

Varoon Rajani, Blazeclan’s CEO, acknowledged the existence of multiple battlegrounds in the cloud market.

He said:

“I believe enterprise workloads will be the biggest battleground for the next three years. AWS aligned with SAP early to become platform certified for running SAP workloads, but now Microsoft Azure and GCP have got platforms certified for SAP also.”

He further emphasised that the top vendors are united in pursuing enterprise resource planning (ERP) systems.

CloudGo’s founder and CEO, Rory Fitzpatrick, believes that the replacement of legacy on-premise applications is the priority of customers. And so will be the movements of workloads to the hybrid platform-as-a-service (PaaS) or infrastructure-as-a-service (IaaS) environments.

He said:

“Many organisations are looking to lift-and-shift to the first two options and need to step back and consider whether PaaS platforms are a better way to go. We find with the secure infrastructure, pre-configured database, identity, and role management and workflow automation of ServiceNow we can often get a far better result, far faster.”

Cloud specialists’ say on AI

Establishing itself as an emerging technology, some market leaders have turned to AI to achieve their business outcomes. Bijjala Radhakrishna, CEO of Total eBiz Solutions, said that AI would be cloud’s next battleground.

“The rise of cloud has created lots of data that no-one owns. This abundance of data is going to make AI, and machine learning models work better and democratise AI, which removes the need for a qualified or experienced data scientist. Instead, this can be done by automation and AI.”

He said:

Additionally, Rajani of Blazeclan said that AI, ML, and server-less services generate “insignificant” revenues despite representing key innovation areas. He pointed out that it will evolve into a battleground within the next three years.

Syner-G Technologies’ CEO, Roger Siow, said that cloud could create a platform that will facilitate the growth of AI and ML.

He said:

“Cloud vendors must also compete in user experience to gain market share. Security can also be enhanced using AI and ML to prevent complex viruses and spyware. A good example is Google Cloud using AI to improve the cloud experience of users. Gmail now can predict what you want to say in an email and help you type even before you even think of the statement. Therefore, I believe the fight now is centred on gaining market share by providing more advanced and safer features through the development of AI.”

Pro-Datech systems’ executive director and co-founder, Siew Kheng Chew, shared that customers have placed more focus on cost control over security.

“The priority is around who can provide the most cost-effective cloud. Whether hybrid cloud or multi-cloud, the conversation is still about cost. The market talks about security, but it’s no longer the main concern given the amount of solutions now available.”

Dynamics in the market

On another note, Cloud Comrade’s co-managing director and founder, Andy Waroma, identified the “three distinctive areas” that will define cloud managed service providers (MSPs) in the ASEAN market within the next 1 to 2 years.

Waroma stated that the Singaporean government would push towards the public cloud. This will be followed by the ASEAN financial services sectors’ adoption of cloud services, and then, Indonesian organisations will migrate to cloud after AWS and Google Cloud open regions in the country.

He added:

“While it can be thought of as battleground, the market will be so big that cloud MSPs will start running out of capable resources and therefore, they need to start thinking about resource optimisation through coopetition. Each cloud-focused MSP will have their own unique strengths, and rather than going head-to-head in every deal, there will be new synergies that will emerge to benefit customers, cloud platform providers, and of course, the MSPs themselves. Let the battle commence.”

Taking the next phase with multi-cloud

ViBiCloud’s COO, Ramon Hadypratomo, cited multi-cloud as the next phase for the expanding cloud market in Indonesia.

He shared not only how Indonesia’s market is growing and emerging, but also the need to improve the infrastructure and awareness of digital transformation.

He added:

“Indonesia is pursuing a multi-cloud strategy because customers are uncertain about cloud reliability. It’s like the market wants to put their eggs (cloud) in some of baskets (cloud platform) which is managed by one MSP such as ViBiCloud.”

Cloud Ace’s cloud solutions architect, Avinash Bodapati, shared that at an enterprise level, a ‘one single cloud fits all’ approach may not be able to cover everything. He emphasised how every cloud provider in the market has its own strengths, but cannot be expected to give up on its existing investments in the form of on-premises environments.”

Rajani of BlazeClan agreed with Bodapati stating that “Hybrid cloud is a reality.” There is no all-in-one single cloud platform, and large-scale businesses will opt to work with a multi-cloud approach or deploy workloads based on the cost of the underlying resource.

He concluded that although cloud players have signed up with VMware, leaders in the market have released AWS Outposts, Azure Stack, and Google Anthos, which provides individual hybrid offerings.

The post Cloud Computing Experts’ Say on the ASEAN Market appeared first on InsideSAP Asia.

The study, ‘Making the most of Machine Learning: 5 Lessons from Fast Learners’, asked 360 senior executives across four geographic regions – North America, Europe, Asia Pacific and Latin America about their machine learning adoption.

According to the study, ‘Fast Learners’ – defined as those companies that are already seeing substantial benefits from machine learning – hold five key traits.

1. They make machine learning a C-level strategic priority.

Fast Learners have senior management who understand the strategic value of machine learning and are more open to embracing change. This is demonstrated by the fact that 75 per cent of Fast Learners plan to retrain employees displaced by machine learning to perform higher-value tasks that will retain them in the organisation.

2. They use machine learning to drive competitive differentiation and innovation.

Rather than being a threat, it’s a way to stand apart from the competition. Thirty-one per cent of Fast Learners say machine learning has already resulted in business model or business process innovation. For example, Ocado, an online grocery retailer based in the UK, created its own machine-learning based logistics platform for automated warehouses that it plans to license to other retailers.

3. They recognise the potential for new revenues and profitability.

Fast Learners know that machine learning can contribute to revenue growth opportunities, in part due to faster, more accurate and cost-efficient processes.

4. They keep key processes close to home.

Fast Learners are increasingly sourcing business functions such as finance and HR locally, rather than outsourcing to low-cost regions. Business relevance and customer value are expected to overtake cost in sourcing priorities.

5. They implement an enterprise-wide strategy.

Rather than dipping the toe in machine learning through individual business units or functions, leaders are adopting a holistic strategy across the organisation. This includes integrating machine learning into key customer-facing and product development functions, with 41 per cent saying machine learning is translating into higher customer satisfaction.

“Machine learning is creating results for businesses – both on their income statement and with their customers,” said Mike Flannagan, senior vice president, SAP Leonardo and Analytics. “Executives need to view machine learning not as a quick fix but as an integral part of a larger strategy to give their business a competitive edge. This requires looking past the initial investment and focusing on the potential for long-term business value.”

The full study can be accessed here.

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Together the two companies will harness the power of big data, machine learning, analytics and the Internet of Things (IoT) in this latest step of a process that began 18 months ago, when they began working together to accelerate and simplify their customers’ digital transformation journeys using SAP S/4HANA.

“Every CEO in the world is focused on digital innovation,” said Bill McDermott, chief executive officer, SAP. “With SAP HANA and SAP Leonardo, we are alone in delivering the power of in-memory computing together with a rich combination of modern digital technologies. We could not be more pleased to announce an expanded partnership with Accenture to create a new wave of industry-specific digital solutions for our customers.”

“Today, we’re at an incredible tipping point,” said Pierre Nanterme, chairman and CEO, Accenture. “We’re face to face with an era of tremendous business transformation where the fundamental rules of how we create value are being rewritten. What we’re announcing today is a bold step in defining the rules for the intelligent enterprise,” he said.

New offerings will enable customers to tailor predictive models to their specific businesses, providing improved results through real-time insights leading to better business decisions. Accenture plans to integrate more than 50 of its proven enterprise analytics applications to help customers reduce capital costs and optimise supply chains.

Accenture also plans to use its Industry X.0 approach and Industrial Internet of Things (IIoT) expertise to help organisations leverage SAP Leonardo to achieve new levels of efficiency, uncover new sources of growth and deliver hyper-personalised customer experiences.

The company will develop analytics and Industry X.0 solutions based on SAP Leonardo at its Industrial IoT Innovation Centre in Garching, Germany, at its Innovation Hub in Houston and at Accenture Liquid Studios around the world.

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With Gartner predicting that smart machines will be a top five investment property for more than 30 per cent of CIOs by 2020, SAP is helping organisations get ahead of the curve.

A new solution, “brand intelligence” developed by the SAP Innovation Center Network, will analyse brand exposure in video and images by leveraging deep learning. The solution will be released in beta by the end of the first quarter of 2017, and is designed to help advertisers gain accurate, real-time insights into sponsoring and advertising ROI.

SAP has also launched a new partner program for SAP Application Intelligence. Participants will include SAP global services and technology partners and solution extension partners, as well as technology providers and machine learning startups, with the program designed to smooth the path for customers to consumer partner solutions based on ML and artificial intelligence by promoting interface certification and platform compatibility.

Finally, a new massive open online course on ‘Enterprise Machine Learning in a Nutshell’ will also begin on openSAP on November 14. Present by Dr Markus Noga, vice president for machine learning at SAP, and Dr Daniel Dahlmeier, leader of the Natural Language Processing team at SAP Innovation Center Network, focusing on how to leverage machine learning for business outcomes.

“SAP’s vision for machine learning and artificial intelligence goes way beyond one business application. It’s about creating business value by infusing our entire set of solutions with more intelligence, and providing a platform for our employees and an ecosystem to build machine learning solutions on,” said Juergen Mueller, chief innovation at SAP.

IoT Application Enablement solution released

SAP also introduced an SAP Internet of Things (IoT) Application Enablement solution, based on the HANA Cloud Platform, to help customers and partners develop IoT solutions efficiently.

The solution allows users to create an enhanced virtual representation of a product, service or process, by combining sensor data, business data and contextual data. The product includes development environment and tools, micro services and smart data storage, and integration to business processes and applications.

“SAP IoT Application Enablement provides a powerful virtual model that shows how a thing will operate with real time data over its lifetime,” said Tanja Rueckert, executive vice president, digital assets and IoT, SAP.

“It also delivers an IoT tailored development environment that promotes development efficiencies and provides a common foundation across all apps. Customers are now able to develop IoT solutions efficiently, with a reduction in errors and ultimately an increased time to market.”

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