The Ghosts that Haunt Digital Transformation
Organizations are increasingly focused on “digital transformation.” They want to redefine business models, create new ways of engaging with customers and drive significant gains in operational efficiency. To achieve these aims, leaders seek to leverage capabilities that include intelligent automation, data analytics, cloud deployment and Agile methodologies.
Many initiatives, however, fail to produce real change, and outcomes are too often limited to digitizing existing ways of doing things. A key reason is that businesses are constrained by the legacy of people- and paper-based processes. Specifically, they’re haunted by operational “ghosts” that continue to influence organizational design, process improvement and technology deployment. The result: limited business benefits.
To overcome the burden of the past, businesses need a new perspective on problem-solving and goal-setting, as well as a better understanding of how outsourcing can help fully leverage the potential of today’s technology.
Replacing Manual Processes
Businesses have invested significant resources in Robotic Process Automation (RPA) applications to streamline back-office operations. And these tools have delivered impressive returns. That said, the benefits are measured and defined in the context of people- and paper-based operations. RPA benefits of productivity, auditability and cost savings, for example, are typically gauged and expressed relative to human administrators. And, RPA sales pitches often boast that bots execute routine administrative tasks in much the same way that people do.
And therein lies the problem. We’re using robots to replicate the way humans execute processes designed to accommodate the functionality of manual typewriters and carbon copies. Rather than use technology to approve invoices and process claims, we need to create entirely new operational designs, process workflows and job functions. And in the process, we need to redefine the relationship between human and digital labor.
One key to a successful transformation strategy is to realize that impactful innovation doesn’t have to be grandiose, nor does it have to be complicated. The concept of digital transformation, however, by definition implies a massively complex undertaking. But as we’ve learned, strategies that aim too high typically fail to deliver. In the early days of the Internet of Things (IoT), businesses invested billions to build networks of connected, intelligent devices. The expectation was goldmines of actionable insights that would change everything. Instead, we got swamps of data points that delivered minimal value.
The critical missing element in these initiatives was simple: a business problem to solve. Recognizing this, today we see an increasing focus on deploying intelligent devices to address specific needs. Examples include temperature sensors that monitor refrigerators in restaurants or medicinal storage units in pharmacies. Sensors that analyze chemical compositions can help oil companies identify fraudulent operators who water down fuel supplies or short-sell customers. Location devices can track lost luggage and deliver alert signals from lost hikers and abducted children.
In the context of exorcising operational ghosts, a focused, start-small approach can similarly move the needle. For a traditional insurer, driving digital transformation across its entire back-office operations is unrealistic. However, redesigning a particular function such as claims processing is doable. Such an initiative can achieve measurable results in terms of both customer experience (faster approvals) and operational efficiency (lower costs). In addition, the initiative can be a best practice-defining pilot for other business units.
Re-thinking business problems and focusing on quantifiable goals is essential to defining a digital transformation strategy. To sustain the journey, businesses need to effectively integrate machine learning-enabled data analytics and real-time communications. In terms of the former, basic RPA functionality is increasingly being complemented by cognitive capabilities. The result: “smarter” robots that go beyond rote repetition of programmed tasks and that are able to identify errors, aberrations and outliers.
The communications piece of the puzzle comprises a software-defined (and soon-to-be-5G-enabled) infrastructure, increasingly characterized by agility, on-demand service provisioning, automated monitoring, predictive maintenance and proactive security intervention. This infrastructure links the smart sensors at the edge of business activity to the analytical platform at the back end.
The result is a digital ecosystem that presents an opportunity to continually collect, analyze and act on data in real time to identify and solve problems that provide immediate benefit in terms of shorter time cycles and delayed negative outcomes.
Defining Core Competency
How can outsourcing help a business seize the opportunity of today’s technology? In one sense, little has changed. The value proposition of outsourcing has always been to allow a business to focus on its core competency. That’s still the case. The challenge now is that the definition of “core competency” is becoming increasingly narrow and restricted to business expertise. Twenty years ago, an insurer’s expertise in claims processing delivered a competitive edge by enabling superior customer service, reduced costs and quick remediation to customer demands.
Today, thanks to digital enablement, operations are becoming increasingly commoditized and internal operational defects are becoming more apparent to the end customer. Consequently, businesses need to be more strategic in identifying and leveraging their areas of differentiation. This requires shifting their internal focus towards proactive responsiveness to customer demands and volatile market conditions.
As a result, the decision on what to keep in house, what to outsource, what to transform, what to automate and what to integrate with cognitive gates becomes more difficult. The good news is that new technological approaches and analytical methodologies can allow businesses to let go of operating platforms, applications and processes. This creates new opportunities to modernize, create competitive advantage and shed the ghosts of the past.