How data and AI are redefining business process

But imagine what could happen if the work of these siloed teams was seamlessly connected. Imagine if one decision on pricing could trigger a dynamic ripple effect across the organization to automate and optimize decisions in every function — from the front office to finance — for the best business and customer outcomes. That would be what we call a Living Process.

A Living Process constantly predicts, senses, acts and adjusts to fluctuating conditions, creating new connections across the business that enable new levels of performance. In its truest form, a Living Process is powered by five characteristics and capabilities:

• Customer-centric activities: Modular process steps that work across lines of business — in other words, breaking the silos — so that key changes are dynamically scheduled and triggered by events.
• Natural interactions: Simple, natural dialogue between humans and machines for seamless collaboration.
• Contextual insights: Hyper-personalized insights that are timely, context aware and actionable.
• Cognitive automation: A human-like virtual workforce that continuously learns and evolves.
• Relevant and integrated data: Intuitive knowledge representation fed by relevant real-time internal and external sources.

Today's billion-dollar unicorn start-ups have the advantage of building these capabilities into their process design at the outset. In contrast, businesses running on more-established processes may find themselves encumbered by inefficient legacy systems, rigid silos and fixed schedules. Most were designed and built decades ago to solve for specific needs, with a premium placed on consistency and simplicity rather than on speed, scale and agility.

Fortunately, the evolution of technology has lifted a lot of the constraints facing seasoned enterprises, so the past doesn’t have to dictate the future. Mature companies can incorporate today's rapidly advancing and increasingly accessible tech enablers to create Living Process. Cognitive automation powers on-demand and perceptive processes that adapt in real time and minimize the need for manual tasks instead of performing predefined and sequential tasks. Decision engines and natural interactions enable a new level of flexibility, making it easy to rewire process steps while fostering human and machine collaboration. Consolidated and intelligent data foundations create a single source of truth for the business, breaking through business silos to create seamless connectivity across the enterprise. Machine learning enables processes to continually adapt and learn. And the list goes on. With more connected and intelligent systems, companies will proactively produce outcomes that would have been far more difficult (or impossible) to achieve before. In doing so, they will enrich their credibility as tech-savvy brands, even if their storied roots are nowhere near Silicon Valley.

In the example at the beginning of the article, the outcome was customer loyalty amid a challenging pricing environment. But let's look at Living Process as applied to another area: finance. A well-oiled finance operations team can manually process dozens of invoices daily, validating its compliance with the agreed contractual terms and documenting its decisions in the procurement system. But Living Process can read the invoice documents automatically and store them in a structured and searchable format. Not only that, but it can comprehend the contractual terms, validate compliance of the invoice and provide an approve/reject recommendation to the financial analyst based on the analyst’s past decisions and preferences. It will then inform all business stakeholders both within and outside the finance team about necessary follow-up actions or escalations through natural interaction channels such as email or even chat. The outcome? Radical simplification of the process and maximum workforce efficiency.

Adopting Living Process: Where to start . . . and how to keep going

Starting a process revolution isn’t easy. Businesses should anticipate obstacles before moving forward and should create a plan for how to overcome them. Leaders may be reluctant to pursue a process revolution if they believe their business is already operating efficiently and effectively. Company employees, meanwhile, may be reluctant to change how they work, especially if this is radically different from the past and disrupts old process models. If they're accustomed to operating within their silos and only focusing on impacts within their business functions, they may be even more skeptical; the "borderless" nature of Living Process means decision makers must also consider how their actions impact functions beyond their silos. Finally, there can be apprehension around adopting new technology, especially in the data and AI domain. Will AI be effective in identifying the right data trapped in legacy systems, and then interpreting and analyzing it to inform important decisions? Even then, how can one be sure they can trust the quality of the data and validity of the recommendations delivered?

A measured approach to Living Process can help you clear such hurdles. If we had to create a checklist for Living Process, it would look something like this:

1. Prove value with low-hanging fruit: In every company there are too many processes that need to be overhauled in order to deliver outcomes. Don’t try to boil the ocean — begin with a pilot use case to prove value quickly. Early results will provide momentum and encourage the adoption and expansion of Living Process later on.
2. Prioritize based on projected ROI: Beyond the first pilot use case, identify which capabilities would most benefit the company and in which business functions. Depending on the industry your company operates in, you might want to enable cognitive automation to accelerate process execution and reduce OPEX, or you might want to focus on natural interactions to revolutionize how decision makers interact with data and systems, etc. Prioritize the business functions and required capabilities where value can be demonstrated and scaled quickly — whether that’s because of existing infrastructure, executive sponsorship, employee readiness or something else.
3. Clarify the definition of success: Make sure that shared accountability for KPIs is clear. The cross-business function convergence that comes along with Living Process could create confusion (or conflict) if previously siloed groups are misaligned on shared or contingent KPIs. Success may look different — in a good way — with Living Process.
4. Design for the user: Create and design new solutions that put the human at the center. If a new process or tool is intuitive and easy to use, employees will be more likely to adopt it, even when it means embracing new ways of working with different technologies and departments.
5. Take a phased approach: Build a plan that lets your people get comfortable with new technology. In addition to building tools that users want to use, your long-term success will require them to trust the data and new AI-powered capabilities. For example, if there is hesitation to allow automatic implementation of AI recommendations, management may mandate that users review all recommendations at first. After enough of those recommendations prove valuable and the AI system has been trained and tuned to the right outcomes, the team could begin automatic implementation.

Above all else, it's important to keep in mind that there's no one-size-fits-all approach to Living Process.

Accenture has developed a maturity framework to help our clients better understand what capabilities they should prioritize and where.

But even after you determine where to begin, don’t rush toward the ideal end state. Living Process is both a destination and a journey. Companies can continue to fine-tune their processes to achieve better and better outcomes over time. The Living Process framework will make this easier to do — it's exactly what it was designed for.