DxSherpa - D

Hyperautomation in Healthcare and Life Sciences

Hyperautomation in Healthcare and Life Sciences

Healthcare and life sciences CIOs believe that automation is paradigm shifting technology. Yet, there is a lack of shared vision and governance to achieve Hyperautomation to scale businesses. CIOs must establish a center of excellence with Hyperautomation to process and conquer crucial barriers.

The challenge of attaining Hyperautomation in healthcare and life sciences

  • Most of the business process optimization initiatives have failed to deliver results that are required by the business leaders, because of siloed, poor scope and misaligned automation techniques
  • Without effective governance, the digitization efforts have become fragmented and complex
  • IT culture barrier shift have constrained the operating model shift rendering digital transformation initiatives incomplete or incompetent

Robotic Process Automation is not stand-alone solution

The healthcare industry is surrounded by high cost and inefficient legacy systems that have restricted digital transformation. Only 12% of organizations and 48% optimizing organizations have digital transactions for medical products and services. These processes overall require about 2 billion dollars to be automated in the North American region alone. At the same time, healthcare and life sciences CIOs cite automation as a game changing technology that can improve the process in their organizations by miles.

Top management has been pressuring the CIOs to deliver fast and agile process automation that enables them to achieve their cost saving mandates, as well as transformation goals through technologies and platforms like ServiceNow, RPA(robotic process automation) etc. Amongst all the leading technology, RPA has showcased short term savings thus business leaders are more inclined towards it. But, Hyperautomation can be achieved only through connecting platforms and RPA technologies.

Want to have Hyperautomation for your industry?

However, RPA is not a universal solution as it is not applicable to all the processes and scale. Without the right insight, the organization gets into more technical costs and ultimately causes complexity in the regular processes. A singular focus on task-level automation leads to ignoring processes like business process management, decision modeling, process mining and intelligent automation with machine learning and automation.

Gartner has defined ‘hyperautomation’ as the effective use of complementary technologies that augment business processes to deliver end-to-end automation

To achieve Hyperautomation, CIOs must adopt and scale RPA with platforms like ServiceNow with an enterprise wide approach.

Enterprise automation is not about having a specific goal, it is an agile program composed of a wide set of parameters with iterative processes focused around business management, governance and change management.

Develop an Automated Center of Excellence with shared vision and objectives

Develop an Automated Center of Excellence with shared vision and objectives

Digital process automation contains methodologies and technologies which can plan, model, co-ordinate, govern and monitor business processes being digital or physical. Enterprise-wide automation initiatives like robotic process automation (RPA) can quickly integrate existing systems by interacting with actions of users. RPA along with process automation, BPM, machine learning, low-code platforms and AI can establish a platform for hyperautomation.

Roadblocks for hyperautomation in healthcare and life sciences industry

  1. High expectations, potential benefits and customer engagement

    Key leaders and stakeholders along the business process connect with each other RPA which help them achieve quick and substantial results. But, investments are over multiple quarters and cause short-term reduction of full time equivalents.

  2. Less clarity on scope and poor standardization

    With various tools from RPA vendors in multiple divisions, function-specific causes have become unnecessary and complex. As the processes and people from different departments have various different functions are not achievable through this as there are no concrete results from them.

  3. Poor governance of process automation initiative

    Tactical RPA deployments within a single business function, leads to missed expectations. Enterprises tend to blame the technology for issues arising from deployments, rather than taking strategic approach to process automation

Recommendations for hyperautomation

Successful automation initiatives based on division level RPA or hyperautomation with optimization and transformation initiatives rely on effective partnership between IT and business operations. Following are the recommendations to avoid roadblocks:

  1. Ensure Alignment of process automation and strategic ambition

    Connection between business leaders and executive peers develops various benefits and challenges for automation challenges. Establish a realistic shared vision that clarifies program objectives and integration with strategic goals. Development of high level KPIs like manual process automation i.e improved throughput or reducing rework etc. solves most of the challenges

  2. Involvement of stakeholders from HR, Compliance, Security and Business

    The involvement of these stakeholders provides a better insight to hyperautomation especially in the health and life sciences industry which is bound by regulations.

  3. Comprehensive plan for Automation Center of Excellence

    An Automation Center of Excellence (ACoE) provides a focal point for business leaders to fine-tune skills for adapting enterprise-wide process automation approaches. As this comes into place, organizations can reinvent and reiterate key processes for developing new capabilities. This can also create a new opportunity for a center of excellence for analytics.

Get Hyperautomation digital audit for you

Governance framework for cultural barriers and change management

It is very important to establish a governance framework that helps ACoE leaders across business and IT to identify opportunities for automation. This framework acts as a crux of organization change management. To create a governance framework, the following are the steps to be taken:

  1. Responsibilities that can embed prioritization and decision making elements

    These responsibilities once divided, regardless of organization roles can sort abstract layers to give a clarity for business process optimization. By separating responsibilities from job roles, job titles and personalities neutralizes political challenges in governance. With clear responsibilities, decision making velocity increases and causes rapid organizational evolution.

  2. Embed automation strategy with existing mechanisms

    The architectural review of existing governance mechanisms embeds with automation strategy to support the wider business context.

  3. Automation governance board

    The process automation framework board can oversee ownership of top-level vision and strategy. This group includes business analysts, CIO and senior IT executives. The governance board reviews all proposed automation efforts, assessing the strategic business benefits and prioritization pipeline initiatives.

  4. Enterprise Automation Roadmap

    The Enterprise Automation Roadmap for hyperautomation in healthcare and life sciences is a documentation of all the opportunities. It captures and catalogs business processes to evaluate their sustainability to automation. The different part about this documentation is it also captures if the opportunities identified need redevelopment or reorganization. This document helps to secure the right balance in the organization.

Steps for enterprise-wide hyperautomation

ACoE is not simple to implement successfully – but holds a potential to realize digital transformation successfully enterprise-wide.

Start with one, but plan for all

ACoEs have the best success rate once it makes the initial project successful and solves the business problem. The business problem should be self-contained and at a relatively low level of maturity, for example, Data collection and Data validation. Scheduling and registration can also be managed through this initial plan.

Embed Learning

Once the RPA effort is focused, it is important to reflect on the steps and results achieved through it. Formalization of ‘before-action’ and ‘after-data’ is also important in this step.

Managing complexity and technical debt

It is important that the IT department manages the source code and manages versioning for the same. The connection with dynamic credentials and bots would create an extra layer for security. For RPA integration and platforms, each individual process needs to be tracked and monitored for success.

Achieving Hyperautomation

With all the above steps, seeking opportunities for business augmentation and end-to-end automation will help the organization achieve hyperautomation