Digital Transformation Failure Lessons from the 2020 US Election

Written By: Eric Kimberling
Date: November 13, 2020

If you followed the 2020 presidential election in the US, you have probably observed some of the theatrics and drama surrounding the results. Like most organizations, the process has exposed weaknesses and opportunities for improvement – many of which would likely cause digital transformation failure if extended to other situations.

A significant portion of the US electorate is questioning the processes and technologies used within the voting process. Many of these new producers and technological advances were implemented due to the Covid-19 pandemic, which made this election unlike any other in American history. Regardless of your positioning on the political spectrum and setting aside any opinions regarding the outcome, this election provides an interesting case study on how not to manage your digital transformation.

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There are a plethora of allegations, theories, facts, and misinformation emerging in real-time as I’m writing this. Some of the examples may be disproved over time, but one thing is clear: the people, process, and technology components of America’s latest election could have been aligned or at least communicated much more effectively than they were.

Here are some of the lessons from the 2020 US election that can be applied to your digital transformation going forward.

Decentralization can create digital transformation challenges

Unlike many political systems, the US has a very decentralized way of voting for local, state, and federal candidates. Each state has their own voting rules and laws, and the winner of a presidential election within any state receives that state’s electoral votes. Within each state, there are countless polling precincts, cities, and counties managing their own election and voting processes.

While this localized approach is fundamental to American politics, it exposes some of the challenges of a highly decentralized structure. Diverging business processes, technologies, and employees can be harder to manage. While it provides more flexibility and responsiveness to local customers (voters), it can also be highly inefficient and confusing. Organizations of all types face these same tradeoffs and decisions each day.

The same holds true for digital transformations in general. Large, multinational organizations with disparate business processes and systems can be inefficient and hard to standardize. It also creates redundant effort and costs across different locations. It is important to consider these and other concessions when determining how centralized or decentralized you would like your transformation to be.

This video outlines some of the things to consider when managing change in a decentralized environment:

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Don’t underestimate the value of testing

Technology flaws appear to be a primary concern about how some votes were tabulated in certain parts of America. For example, parts of the country alluded to reporting errors after tabulated the results - largely due to an unexpected upgrade that happened the evening before the election. This made it difficult (if not impossible) to fully test the system prior to loading it with a high volume of transactions.

Examples like this underscore the importance of testing during digital transformations. Last-minute, untested upgrades are a sure-fire way to create chaos, broken processes, and inefficiencies. It is important to properly and thoroughly plan and test your system prior to go-live. This is crucial to ensure that your system is properly working and that your employees fully understand how to use it.

In a cloud and SaaS ERP world, this problem is further magnified by the constant changes to the software. Since customers don’t necessarily have control over the timing or substance of software changes, it is especially important to ensure that technology changes are aligned with business processes and organizational roles and responsibilities.

Change management can lead to digital transformation failure

Just as testing is required to smoke out any technical glitches, lack of organizational change management and training can lead to failure. In the case of the US election, thousands of temporary poll workers and volunteers were required to learn processes and systems that they weren’t accustomed to using on a daily basis. And, they were expected to develop those competencies within a very short period of time.

There were allegedly “human errors” that led to the restatement of some election results. Other anecdotal incidents point to poll workers that didn’t know or understand the impact of pressing certain buttons on voting machines. Others apparently didn’t know how (or weren’t instructed) to validate mail-in ballots. These are all good case studies that highlight the importance of organizational change management and training, as well as the consequences of not investing enough resources in these important activities.

Dirty data can ruin a digital transformation

Voter registration data is very complex. Databases need to track those that are registered, where they live, whether they are living people and other data points that are constantly changing. This can make data management and cleansing a big challenge.

During the 2020 election, states in the US are being accused by some for having dirty data. For example, voter master data contained records of dead people, people that no longer live in the state, and even some that are allegedly not US citizens. This led to some concern about the integrity of the election results.

Let’s extrapolate these election examples to a current private-sector digital transformation. One of our clients is a large commercial contractor that creates nearly 100,000 service orders per month. These service orders track very rich data and information regarding the customer order, such as photos, sketches, and other complex data. Keeping this data clean has been a constant struggle for this client, which is part of why they reached out to us.

Bottom line? Clean data and good master data management is a critical component of any digital transformation.

Cybersecurity and other advanced technologies can enable a more successful transformation

Many Americans share concerns about the integrity and security of the voting process, particularly as it relates to mail-in votes. This is an example of manual and antiquated processes - much like what other organizations experience - and it is also highly insecure.

Elections highlight examples of how organizations might leverage advanced technologies to tighten cybersecurity. For example, blockchain and biometrics offer two technologies that could both streamline the process and secure people’s identity and votes along the way. Like elections, organizations need to also find ways to keep intruders out of their systems, whether it be outside hackers or employees that put data at risk (whether intentional or not).

Key digital transformation lessons and takeaways

Regardless of what irregularities are or are not uncovered during investigations into the 2020 US election, it is clear that the entire mechanism could be improved. Just like most organizations, there are broken processes, flawed systems, and human dynamics that need to be upgraded and optimized.

What challenges are you facing with your digital transformation? Please feel free to contact me to discuss your project and brainstorm ways to improve the path you’re on. I’m happy to be a sounding board for you as you continue your transformation journey!

Kimberling Eric Blue Backgroundv2
Eric Kimberling

Eric is known globally as a thought leader in the ERP consulting space. He has helped hundreds of high-profile enterprises worldwide with their technology initiatives, including Nucor Steel, Fisher and Paykel Healthcare, Kodak, Coors, Boeing, and Duke Energy. He has helped manage ERP implementations and reengineer global supply chains across the world.

Eric Kimberling
Eric is known globally as a thought leader in the ERP consulting space. He has helped hundreds of high-profile enterprises worldwide with their technology initiatives, including Nucor Steel, Fisher and Paykel Healthcare, Kodak, Coors, Boeing, and Duke Energy. He has helped manage ERP implementations and reengineer global supply chains across the world.
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