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Why Do Organisations Struggle with Gaining Data Insights?

By Chris Huff, Chief Strategy Officer, Kofax

The current economic downturn and global disruption from the pandemic created a "Digital Awakening". Boards and C-level executives are accelerating digital transformation initiatives to drive efficiency, growth, business resiliency and remain relevant and competitive in the new digital normal. To make effective decisions these executives need data. To make effective decisions in a timely manner these executives need to automate the manner they capture, process, analyse and draw insights. If we agree that timely access to rich insights from data is the holy grail then the obvious question is "what do I need to reach this state of digital nirvana?" Over the next five minutes, we'll take a hypothesis-based approach to focused outcomes, then back into the type of technology that can help executives achieve the value badly need to navigate the current crisis while positioning for the rebound.

Most of us likely agree that insights from data is extremely beneficial, in the immediate and long term. Then why do so many organisations still struggle to capture, visualise, understand and optimise business-critical information from the moment it flows in?

It's not that industries don't understand the value of data, particularly as artificial intelligence (AI) and augmented analytics have gained traction globally.  Sixty percent of CIOs say that data and analytics will affect their businesses in the next three years1, and 73 percent of companies are planning to invest in DataOps initiatives to support AI and machine learning initiatives2.

But to leverage any of these advanced analytics technologies, organisations first need to capture the data. This includes structured data, including websites, business and desktop applications, and databases. But even more important is unstructured data, since these accounts require more overall data than structured. Unstructured data is the content found in documents and emails, for instance. Once we've ingested 100 percent of the available structured and unstructured data, the data must be orchestrated into appropriate workflows to feed downstream systems.

The typical organisation will use several disparate applications to process a single transaction. And in many organisations humans serve as the ‘connective tissue' among these disparate applications. This is expensive, takes time and is prone to error. Let's look at a typical customer onboarding process. This likely requires an initial digital channel feeding a CRM triggering credit checks, bounces off a decision-engine to initiate Know-Your-Customer (KYC) actions, sending notifications to the customer providing updates and requesting documentation while another application's partitioning the user account. To make this happen seamlessly, an automated end-to-end digital customer workflow can be designed to orchestrate the flow of data, eliminate errors, reduce cycle times and increase compliance. Automation can also accelerate the generation of data insights by rapidly aggregating different types of data-comprising business data, and data from different channels and sources, including operational and processing data, customer data, customer or stakeholder feedback, etc. The result is a more accurate and faster way to visualize business intelligence. Finally, every organisation wants to maximise the value of their data. A great approach is to "open it up" a bit through data democratisation using the right tools-empowering employees to spend more time engaging with and exploring the data to gain insights they can use in their roles.

Data Analytics Can Change the Game

Banks, insurance companies, transportation and logistics firms, healthcare companies, government agencies and more-every day, an avalanche of data pours into organisations across every industry. This data comprises a variety of formats and originates from multiple sources.

A number of organisations still struggle with information siloes, inefficient legacy infrastructure, and uncaptured and/or unstructured data. But increasing numbers are now successfully automating data capture and transformation into the right format. Lingering headaches that are common are high error rates from the merging of information entering the organisation, poor documentation and different rules requirements. All of this can contribute to production or service delays and, ultimately, frustrated users.

This is where analytics capabilities part of a larger, integrated intelligent automation solution can be game-changing. Automation and workflow create a new ‘digital frontier' removing friction resulting in higher efficiency levels, but when analytics are added we ultimately enhance decision-making. The business value of integrated intelligent automation and analytics is enhanced oversight of key business processes, streamlining workflows, pinpointing the likelihood of bottlenecks or service interruptions before they happen and speeding the delivery of critical business data and decisions.

Automation Helps You Make the Most of Your Data

The most elementary application of automation to your data can provide answers to questions including: Is the data we're capturing showing increased errors, and if so, why? Can we isolate user productivity by department and determine where extra training could be beneficial? Are our workflows processing data outside of our SLAs? If so, what's the surplus?

Analytics is about uncovering patterns, particularly unanticipated ones, and helping organisations use those real-time insights to act upon that information quickly and proactively-and predict future potential issues.

Unfortunately, according to IDC, only 10 percent of usable data is used for analysis3. It's true organisations have become quite adept at data collection, even very large amounts. But many struggle with transforming the massive amounts of information acquired through intelligent automation into something understandable and actionable so they can make better business decisions.

This brings us to essential tools every user tasked with maximising the value of organisational data should have. It starts with self-service, interactive, web-based dashboards and visualisations that don't require IT to build new reports, modify queries, or perform coding, syntax, or scripting.

Below is a list of the most important key dashboard configuration capabilities. Users should be able to:

  • Uncover real-time process trends through data visualisation and manipulation to improve performance
  • Drill down to identify low-confidence fields and set the right actions to improve process quality
  • Filter batch and document numbers by class and pinpoint bottlenecks
  • Evaluate productivity statistics teams-number of batches, documents and pages processed per time variable, team or process
  • Use predefined operations metrics to quickly view and accurately measure and improve performance
  • Get objective performance monitoring of human operators, business processes and software performance
  • Use a mobile or desktop view from any device
  • Protect data on-the-fly and apply security roles to protect data
  • Drill down to the lowest level of process data to account for, track and trace processes

Final Thoughts

Many organisations are leaving a great deal of insights on the table when it comes to their data. There's never been a better time to move beyond the boundaries of traditional systems and redefine what analytics means as digital transformation accelerates in the New Normal. Integrated intelligent automation connecting systems, data and people to achieve outcomes combined with powerful business intelligence is the key. The ability of organisations to garner real-time insights from this activity is the path toward realising the agility and resiliency successful organisations need to thrive today and in the long term.

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About the Author

Chris Huff 

Chris Huff drives Kofax's global strategic initiatives, Intelligent Automation thought leadership and cross-functional horizontal integration. Prior to Kofax, Chris led Deloitte Consulting's U.S. Public Sector Robotics and Cognitive Automation practice. 

 

1 Bill Briggs et al., Strengthen the core: 2018 global CIO survey, chapter 5, Deloitte Insights, August 8, 2018.

2 https://www.nexla.com/n3x_ctx/uploads/2018/06/Nexla-The-Definitive-Data-Operations-Report-2018.pdf

3 IDC Worldwide Global DataSphere Forecast 2019-2023, January 2019

Published Tuesday, July 14, 2020 7:48 AM by David Marshall
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