Five keys to freeing your organization from transactional quicksand

by | Mar 5, 2020

With the pace of business accelerating every year, executives are challenged with ensuring their organizations remain agile enough to take advantage of constantly changing and emerging opportunities in the market. How quickly an organization can assess market conditions and make timely course corrections can be the difference between survival and peril.

When it comes to the critical imperative to build a more efficient and responsive organization, front and back office functions often find themselves mired in transactional quicksand, struggling to keep pace with the changing needs and demands of the market. When resources are focused on manual, repetitive and low value-added activities – including anything from financial journal entries to technology support requests – how does an organization adapt?

Businesses heavy on manual transactional processes are bottom-heavy, sluggish, difficult to change and have fewer resources for innovation and forward-looking strategic initiatives (Figure 1). If leadership decides to pursue a new opportunity, it cannot deploy valuable resources to a key initiative without sacrificing one or more other strategic initiatives; there aren’t enough strategic-oriented staff to go around. Simply reallocating resources from transactional work to focus on key projects is not an option, as this would pose operational risks to the organization.

Figure 1: A bottom-heavy transactional organization

If you continue to hear “we need to wait until after month-end close to pursue that initiative,” your organization falls into this group. After month-end, employees take a well-deserved break to recharge from working late into the night – and on weekends – to close the books. Month-end closings, and the ensuing break, eat up most of the bandwidth of transaction-oriented staff leaving precious little time to help with strategic initiatives. The opportunities for strategic change therefore are few and far between. The answer to this challenge is that organizations must “change their shape” or risk being left behind, if it’s not already too late.

Enter Robotic Process Automation (RPA) and Intelligent Automation (IA, not to be confused with artificial intelligence, or AI). When we think about the organizational benefits of automation, reduced staff levels and cost savings immediately filter to the top. All too often, Return on Investment (ROI) becomes the top measure for a project, requiring that any savings be “hard savings.” Redeploying resources to perform other work on the team, or within the company, gets characterized as “soft savings,” diminishing the ROI on the project. Focusing solely on hard savings however ignores the value employees bring to an organization and the value redeployment can have on morale and driving change.

Improved quality, increased compliance, enhanced customer experience and greater insight into processes and data are commonly sought-after benefits of automation that aren’t always associated with hard savings. Very few automation strategies focus enough on the opportunity of redirecting valuable resources away from rote activities. If employees are no longer doing transactional work, they can be driving meaningful change, ensuring the company keeps pace – or sets the pace – in the market.

A strategic-oriented business is agile, resilient, innovative and proactive (Figure 2). RPA and IA enable businesses by automating manual and repetitive work so employees can focus on value-added work. Furthermore, companies become more adaptive to disruptive shifts in their markets and more responsive to opportunities and threats.

Figure 2: A Strategic Oriented organization

Successful organizations don’t just embrace RPA & IA, they excel in the following five areas:

  • Establish robust process discovery mechanisms
  • Automate manual and repetitive processes at scale
  • Deploy process improvement initiatives to standardize and streamline processes before automation
  • Use data and Artificial Intelligence (AI) to replicate cognitive decision making
  • Embrace change management as an essential practice

Establish robust process discovery mechanisms

Traditional process discovery has been top-down. Automation champions within the organization utilize their relationships with senior leaders across the company to brainstorm processes ripe for automation. Usually a few processes emerge as candidates for a pilot, and the journey begins. Once the first few processes are deployed to production, employees in those business areas come up with new ideas that are funneled through the project intake process. This top-down approach usually yields a small set of good processes for automation but lacks the breadth and depth of visibility that a more modern approach using AI can provide to truly discover the best processes for automation.

The use of AI to find patterns within system logs and by analyzing employees’ actions on their machines has enabled a more data-centric method of discovering automation projects that will yield the greatest benefits. Companies that have the most robust pipeline of automation projects are using process discovery tools to identify and prioritize their RPA projects.

Automate manual and repetitive processes at scale

Easier said than done, automating at scale encompasses many dimensions of your business across people, process and technology.

People – Successful companies will build automation programs that are right-sized for their organization. Too many resources and consultants in your program will incur fiscal deficits and make it challenging for your program to recover and show ROI. Too few resources and your program risks leaving automation opportunities undone and business stakeholders dissatisfied. Furthermore, adding the right mix of roles is key. Organizations need to find a balance of inside and outside project/program managers, business/process analysts, automation architects, developers, testers, infrastructure engineers, machine-learning engineers and data scientists – and accomplish this in a tight labor market.

Process – Establishing a cross-departmental governance framework, intake process and program management structure is essential to ensure the organization is focusing on the right processes in order to deliver strategic benefit. Organizations also need to decide whether a centralized, federated or hybrid structure will yield the best outcomes.

Technology – There are dozens of software tools on the market in the RPA and IA space, and market consolidation of these tools has only just started. Finding the right mix of technology that enables your organization to scale is essential. Not only that, developers and automation architects must embrace development frameworks and best practices published by vendors to ensure the maintenance of automated processes does not become unwieldly.

Standardize and streamline processes before automation

Not all processes are ready to be automated, and automating a bad process or one that is currently inconsistently applied throughout the organization is never recommended for obvious reasons. Companies should engage in process improvement initiatives, such as Lean Six Sigma, to either improve or re-engineer processes – prior to deploying an automation strategy. If the results or the steps to perform a process differ by analyst, office location, country, customer or for any other reason, the process should be standardized before automation can be considered.

Use data and AI to replicate cognitive decision making

RPA relies on a process developer to specifically program rules into a workflow to allow the robot to make decisions. Even moderately complex decision making can be an arduous task for RPA developers when replicating the decision patterns. So, naturally, there is a point where RPA alone is not the right means to automate a process end-to-end. Additionally, automating the first part of the process, then stopping for a person to make a decision, then reinitiating the RPA workflow is cumbersome. Companies that have successfully automated processes end-to-end have integrated machine learning and AI models to learn from patterns in the data to make decisions automatically. The combination of RPA plus AI has enabled businesses to scale automation beyond what traditional RPA was able to do.

Embrace change management as an essential practice

Before a company can make a meaningful shift from a bottom-heavy transactional organization to a strategic value-driven organization, employees must undergo change. As we all know, change is a personal experience, and we all think and feel about it differently. Some will embrace the change and others will not. Organizations that put in place change management practices comprised of experienced change management professionals will ensure the transition is managed in the best way for employees and the organization.

In today’s rapidly changing business climate, companies that can free their employees from transactional quicksand by developing capabilities around the five key automation areas above, will be positioned as leaders in their respective markets.

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