7 Tendências Essenciais de RPA para 2020: Elevando IA e Escalabilidade Estratégica

Peter Walker disseca tendências chave RPA para 2020.

1. Maiores insights de diferenciação fornecedores RPA emergirão

Organizações agora enfrentam escolha bewildering de mais de 150 produtos branded robotic process automation (RPA) — e todos variam significativamente em claims produtividade, qualidade design e abordagem — então maior entendimento urgentemente requerido para entender estas nuances técnicas importantes. Demarcação mais clara de produtos RPA começará emergindo este ano, onde fornecedores caem em duas categorias amplas: aqueles fornecem benefícios táticos rápidos cross ambientes desktop e aqueles entregam transformação mais estratégica cross large-scale enterprise.

Conforme organizações tentam escalar projetos automação, ter esta clareza provará crucial pois muitas ofertas RPA branded newer possuem limitações design. Painful reality pode ser deployments code-heavy requiring extensive debugging efforts e high change management overheads. Esta assertion backed by Gartner’s recent prediction that; “Through 2021, 40% enterprises will have RPA buyer’s remorse due to misaligned, siloed usage and inability to scale.”

Only when RPA delivers on promise of being transformative tool — at scale — will its real value be recognised. This means that organisations’ focus will increasingly gravitate towards RPA technology that’s underpinned by no-code, business-led design principles. This means no lengthy design, programming, build and deployment projects that prevent automation efforts from getting going.

RPA collaboration is key too, so those vendors offering a centralised platform, will enable both humans and increasingly intelligent ‘digital workers’ to deliver, share and expand automation initiatives across the enterprise — thereby accelerating gains.

2. Novos critérios seleção RPA

Haverá re-think de como organizações devem escolher RPA, com assessments mais informed de sua habilidade successfully operar e escalar em large, demanding, enterprise environments – onde security, resilience e governance são mais importantes que just implementation speed. Isso significa que RPA vendor selection criteria will consider more meaningful, real-world insights. These include the overall level of coding required, from zero to high effort, proof of value ‘after’ the proof of concept, scalability potential, collaboration potential, robot capabilities, overall security and auditability capabilities.

These insights will become more important than ever to ensure that organisations see through the market hype to de-risk RPA selection and avoid longer-term issues.

3. Melhores medições valor RPA

Ao examinar experiências e proven outcomes de mature RPA user organisations, we’ll see more meaningful methods of measuring the impact of RPA. These can include;

• Novas ofertas serviço e produto — aquelas atividades sendo performed que previously impossible para humanos perform, ou perform em manner secure e compliant.
• Aumentos produtividade — how much time is being generated back to the business
• Como qualidade serviço e delivery sendo melhorada — this could be due to faster, error-free, execution, quicker time to market, reduced risks associated with longer response times.
• Inovação acelerada e geração oportunidade — how business people are using the additional capacity and technological capabilities to create new value-generating services and products.
• Transformação operacional — how actionable insights from automated process transaction data are being used to optimise, or reinvent business processes that enhance stakeholders’ experiences and create long-term value.
• Staff mais feliz, motivado — how many people are being liberated to work on more intellectually challenging, fulfilling, value-generating work – and gleaning satisfaction in their new roles.

4. RPA torna-se habilitador IA

Throughout 2020, RPA will further evolve towards ‘hyper automation’ — by being an increasingly favoured route for testing and deploying artificial intelligence, natural language processing, intelligent optical character recognition, communication analytics, process optimisation and machine learning deployments — into the enterprise.

We will see easier access for accessing and downloading a wider range of pre-built AI, cognitive and disruptive technologies — via ‘Digital Application Exchanges’. These exchanges will provide a one-stop shop for building out, scaling and adding skills to digital workers with direct access to innovations from partner ecosystems – helping to deliver more intelligent automated innovations.

5. Diferenciação mais clara trabalhadores digitais e robôs

There’ll also be a greater understanding of the vast differences between the differing robots on the market and their capabilities, which is important as they are the catalyst for enterprise transformation. There are those robots that rely on recorded process steps to complete tactical tasks but are unable to adjust to any unplanned changes, and there are more advanced ‘digital workers’ that operate more like humans.

These digital workers are different from other robots, as they’re a pre-built, smart, highly productive, self-organising, multi-tasking resource, that uniquely use and access the same IT systems and mechanisms as humans, without APIs — so are capable of automating processes over any past, present and future application.

Digital workers perform activities in the same way as humans — faster and more accurately, but will also increasingly work with and learn from humans and other robots too. This year, far more organisations will be employing the unique capabilities of human and digital workers that collaborate to perform evermore complex, end-to-end activities.

6. Foco RPA em casos uso mais estratégicos

More organisations will employ a more holistic, strategic approach to RPA by re-imagining processes and organisational structure and other technologies — and there will be a greater focus more on automating more end-to-end process and optimising workflow.

Smart enterprises will also explore a broader suite of process discovery, process mining, process automation and data ingestion to help them deliver the most business-aligned, complex activities that are expected to deliver the most value. These will include legal document validation and extraction, autonomous invoice processing, fraud detection, and similar business and process areas.

7. Abordagem mais estratégica para escalar RPA

Over 2020, automations will increasingly become more carefully planned, modelled and designed to deliver sustained value, longevity and resilience — at scale. Key success factors for achieving success at scale will include integrating RPA into a broader digital transformation strategy, alignment with process governance, key stakeholder support and process optimisation.

Other success factors include partnering with IT and external partners, developing expertise in automation and process optimisation, clear governance and operating model, a centralised framework for IT architecture and infrastructure, and stakeholder communications and change management.