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Intelligent Workflows – Taking Process Automation to the Next Level

Business Process Management (BPM) solutions have been around since the early 2000’s. Over that ~ 15-year period business enterprises have adopted BPM philosophies and strategies in efforts to gain control of mission-critical processes. The evolution of BPM has been supported by an explosive growth in software solutions that have enabled automation of those processes; automation that improved control, reliability, and efficiency.

The current phase in this continued evolution is taking process automation several steps forward. Intelligent Workflows combine the basics of process automation with advancements in Artificial Intelligence (AI) and Machine Learning (ML).

Intelligent Workflows – Automation Combined with Intelligence

Today’s competitive business environments are putting increasing pressure on companies to improve performance throughout their entire customer engagement ecosystems. Business processes that were considered quick and agile just a few years ago are now often viewed as self-limiting and outdated. To meet these new challenges, AI and ML technologies are being coupled with workflow automation solutions to produce workflow-enabled processes that are dynamic, intelligent, and self-governing.

The advent of intelligent workflows can be viewed as a significant contributor within the broader realm of “digital transformation“. But, what does all of this mean? What tangible benefits do intelligent workflows actually provide and how can they make an enterprise more efficient and more competitive? Consider the following range of possibilities:

Proactive Customer and Market Strategies

As we move into the next decade it will become increasingly clear that the most successful companies will be those that have the ability to predict vs react. Proactivity will equate to increased market edge. Reactivity will increasingly relegate companies to 2nd or 3rd tier players.

AI and ML-fueled intelligent workflows will provide the means by which the enterprise can garner valuable insights, in real time, across its entire customer engagement ecosystem. These insights can then be utilized to:

  • Rapidly deploy decisions and actions across the entire organization to achieve maximum operational impact.
  • Utilize AI and ML-enabled workflows to actively “learn” from the data generated within those workflows.
  • Utilize that “learning” to develop customer and market strategies that anticipate future demands and behaviors.
  • Actively monitor the efficacy of those strategies and implement rapid adjustments based on real-time feedback.

Next-Level Process Automation and Learning

Process Automation

Process automation will no longer deliver maximum value unless it is coupled with the ability to learn from—and adapt to—the information generated within those processes. BPM solutions, combined with AI and ML capabilities, provide a complete ecosystem of process automation, data synthesis, and learning. Distinct advantages include:

  • The ability to create dynamic, code-free, workflows that enable automation of critical business processes.
  • The ability to connect those workflows to IoT-enabled devices as well as to data feeds from a variety of sources (social media, marketing channels, CRM’s etc.).
  • AI-enabled process monitoring and data synthesis that provide those processes with the ability to actively “learn” from that data and to self-adjust to maximize performance.
  • Provision of process stakeholders with deep insights—based on active process intelligence—that enable the enterprise to achieve maximum operational performance and competitive advantage.
  • The ability to reduce delivery times for existing products and time-to-market for new products.
  • Provides the ability for real-time collaboration that promotes organizational learning and helps galvanize organizational focus.
  • The ability to create intelligent workflow-based customer experiences that are engaging, seamless, productive and—most importantly— proactively aligned with today’s customer demands.

Functional Implications

Adoption of intelligent workflows will have implications across virtually every industry. Impacts will be evident within most organizational functions; including:

Sales

Intelligent workflows will radically change the ways in which sales teams work and communicate. Active learning will promote the streamlining of processes, the elimination of non-productive tasks, and the implementation of strategies and tactics that are based on higher levels of forecast accuracy.

The cohesion across internal and external sales channels will benefit from more efficient communication processes and protocols. Intelligent workflows will allow sales organizations to further optimize what works and to discard what doesn’t. Sales communications that add real value vs non-productive “reporting for reporting sake”.

Marketing

AI-enabled marketing workflows will provide much deeper insights into customer and market behaviors; insights that can be utilized to predict the future demands of customers. This will allow marketing organizations to create campaigns that are more dynamic, more relevant, and more productive. The increased dynamism will enable marketers to make impactful campaign adjustments based on real-time assessment of audience reaction and feedback.

Vendor Management

Intelligent workflows will be utilized to enable vendor management processes that provide superior control and closed-loop feedback. Processes such as: vendor qualification and onboarding, contract management, vendor performance analytics, vendor spend allocation control, etc.

Operations

Many operational disciplines will utilize intelligent workflows to maximize internal efficiencies, reduce cost, and improve product and service quality. This will have transformational implications across several operational functions; including: manufacturing, quality, delivery, and service.

Project Management

Intelligent workflows will provide project management functions with enhanced ability to control several mission-critical processes; including: project gating control, project resource allocation and tracking, project budgeting, risk management, and corrective action implementation.

Those companies that are able to combine existing process automation solutions with emerging with AI and ML technologies will be creating business workflows that go beyond mere automation. They will be equipping themselves with workflows that are dynamic, agile, and intelligent; intelligent workflows that provide game-changing competitive advantage.

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