Efficient Processes: Setting the Stage for Digital Transformation– February 07, 2020

Posted by Tyler Dalton

What are your strategic goals for your enterprise in 2020 and beyond? Do they involve embracing transformative technologies of the future, like robotic process automation (RPA) and artificial intelligence (AI)?
 
Data, technology and computing power are improving faster than ever before, causing the modern enterprise to radically re-think its back-office departments. As tools like RPA, AI, machine learning and intelligent analytics continue to develop, companies are shifting from manual intensive processes to driving analytical decision making and value-added tasks.
 
But even forward-thinking enterprises are finding it difficult to keep pace. For example, innovative companies like Boeing and Nike are hiring full-time science fiction writers to help them generate new ideas, envision future technologies and predict the needs of future customers.
 
While most companies are not going to the lengths of Nike and Boeing, many organizations are rushing to join the digital transformation movement. However, some tend to jump in “tech” first, choosing a technology without having the right infrastructure in place for it to be successful. Effective technology implementation and process automation begins before technology is even introduced. Efficient and streamlined processes are the building blocks for technologies to drive a new era of value-added performance and unparalleled efficiency.

Prepare for Technology by Streamlining Your Processes

The pace of change in business technologies is becoming so fast that C-level executives are worried about being left behind. In Gartner’s 2020 Analytics Outlook, 31% of CIOs plan to increase their investment in business core system digital transformations. But before considering technology implementation, end-to-end automation or even partial automation, executives need to optimize and streamline their existing processes.

While it’s extremely tempting to believe that technology can improve current day processes and the entire organization will immediately become more efficient, it’s generally not true.  Although technology can incrementally improve production in any back-office department, to unlock all the benefits, you must begin at the process level. That means starting with the basics, such as process documentation and standardization. A recent Accenture report cites companies that simplify and standardize their back-office processes reduce operating expenses by 9% to 10% and experience a 20% increase in process quality.
 
There are specific tools that can be helpful in the streamlining phase. Methodologies such as process mining and process re-engineering can be extremely valuable, as can benchmarking, process maturity and process mapping to gain a holistic view of the current state of your organization. As you fully define the enterprise’s current state processes, a comparative gap analysis — assessing the differences in performance between what you have and what you need — should be performed to determine how to streamline those processes. A gap analysis can help inform and align management on potential opportunities, which can be used to improve the business unit.

Create a Trusted Model for the Future

Once a transformative technology has been identified as a proper fit for the now streamlined process it is supporting, then it’s time to gain a deeper understanding of these technologies to move forward.
 
A critical disconnect in using digital technologies stems from a lack of understanding and ability to fully communicate the end-product the technology creates. Simply put, everyday users outside of the development team do not understand what the technology is supposed to deliver.
 
Misunderstood technology is a destructive force in the decision-making process for business leaders. It also creates an even larger trust disparity between technology and business leaders. A recent KPMG study found that 66% of surveyed leaders ignored the findings and insights that were created by AI because it opposed their experience or intuition. Overcoming this obstacle can only be done at the foundational level when the team is developing their technology.
 
AI in particular must be built on the pillars of transparency, explainability and adaptability. Lack of transparency within a model leads to a fear of using the technology. Tackling all three can be a daunting task ahead of the development phase, but these are some considerations to take into account to develop the best model possible:

  • What is the ultimate goal of this model?
  • Where will the data come from?
  • Which features will you use? How will you prevent the model from becoming outdated?
  • How will you test the model?

What’s the Next Step in Your Digital Transformation?

Employ a team that can help you assess which processes can be re-engineered in your enterprise to improve the chances of success — before investing in digital technologies. This will help ensure you can unlock all of the related benefits. Once your processes are as efficient as possible, consider some of the revolutionary technologies listed below as a way to make good on your strategic goals and embrace a digital transformation for your company in the coming year and beyond.

Types of Digital Technologies

Digital Technology

Definition

How it can be used

Application Programming Interface

A set of functions and procedures allowing the creation of applications that access the features or data of an operating system, application or other service

Easily transfer data to external software’s for visualization and data analysis

Artificial Intelligence

The development of computer systems able to perform tasks that normally require human intelligence

Facial recognition

Intelligent Analytics

An application which acquires real-time and historical data from user interactions, other sources, and leverages machine learning applications in order to provide suggestions and make predictions

Update pricing in real time based on market demand or other external influences

Machine Learning

An application that provides systems the ability to automatically learn and improve from experience without being programmed explicitly

Trial balance mapping

Optical Character Recognition

Software that utilizes machine learning for the identification of characters or words contained in handwritten, typed, or printed images 

Reading a scanned invoice and uploading it to your ERP system

 

Robotic Process Automation

An application of technology governed by business logic and structured inputs, aimed at automating business processes

Automate manual, rules based procedures across various systems


Contact Tyler Dalton at tdalton@cohenconsulting.com, John Cavalier at jcavalier@cohenconsulting.com or a member of your service team to discuss this topic further.


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Cohen & Company is not rendering legal, accounting or other professional advice. Information contained in this post is considered accurate as of the date of publishing. Any action taken based on information in this blog should be taken only after a detailed review of the specific facts, circumstances and current law.