• Corporate
  • Jul 21, 2020

QOMPLX Ideas: When is it OK to plug away at a Tech Program?

QOMPLX Ideas: When is it OK to plug away at a Tech Program?

In this latest installment of our QOMPLX Ideas series, we explore when a business should start deploying a technology program, when to keep plugging away at it and, finally, when to call “time out!” on it. In this post, QOMPLX CEO Jason Crabtree weighs in on how and when to continue with a new tech venture, even when the going gets tough.

We live in an era of digital transformation. Businesses face pressure from consumers, shareholders and hypercritical analysts to be up to speed. This inevitably means upgrading technology systems and software as part of digital transformation initiatives and to pursue buzz words like ML and AI.

"There is all sorts of pressure on organizations to pretend they can flip a switch and reinvent themselves overnight," says Jason Crabtree, QOMPLX's co-founder.

Digital Transformation: Harder Than It Seems

But digital transformation initiatives are hard to pull off. According to a 2018 McKinsey & Company survey, more than eight in 10 organizations that responded said they have attempted to transform digitally in the previous 5 years.

Yet only 16% said it successfully improved their performance and equipped them to sustain changes in the long term. Even companies in digitally savvy industries like high tech, media and telecoms reported feeble success at 26%.

So if a company is struggling in the midst of a digital overhaul, how should its leaders know whether to keep plugging away or call it a day and return to fundamentals? Which tech projects are worth sticking with? It's a problem that Crabtree and his co-founder and CTO, Andrew Sellers, see all too often. QOMPLX advises companies to do background research to ensure the technology program they are implementing is viable.

"We consistently see folks enamored with buzzwords like artificial intelligence (AI) and machine learning (ML) without doing the homework,” Crabtree says, “Access control, security, data inventory and management, process mapping and documentation – all those things are not fun and sexy, they are also the most critical parts of actually having an ML or AI program that works."

(For more on this, see our QOMPLX Ideas post "Ahead of Digital Transformation, Address Security Fundamentals".)

The Benefits of Failing Forward

This is where it helps to do a proof of concept (POC). Test out a new tech program on a small scale first before rolling it out across the board to demonstrate its feasibility, and find out if it's truly a game-changer or not.

Failure is common in business, so try to "fail forward" and test out small new ideas before scaling up. Big companies like JP Morgan Chase are increasingly encouraging employees to micro-experiment at work.  Individual use or demonstration can lead to team, department or eventual organizational adoption of new tools.  However, many such efforts lack the benefit of intentional design; some centralized review, coordination and planning is required to harmonize efforts.

In QOMPLX’s experience, it is helpful to adopt a mindset focused on balancing demonstration of a business use case and longer term alignment with core technology modernization and architecture goals when deciding whether to plug away at a project or pursue a different path.

"Companies need to do specific types of exploratory learning and selective proof of concepts in parallel to robust enterprise-grade data output and inventory improvements that support putting the ‘data factory’ in place,” Crabtree explains." Otherwise when they get to the end of their POC journey they end up with lots of little toy start-ups and home grown projects in ‘POC purgatory’:" absent the technology, services or maturity to scale their use cases or the controls to validate them, Crabtree said.  

Size Matters

Company size also has a significant impact. Success rates of digital transformation projects vary by company size. According to McKinsey, companies with fewer than 100 employees are 2.7 times more likely to report a successful digital transformation than those organizations with more than 50,000 employees.

That would suggest that leaner, more nimble businesses are better off plugging away with their technology overhaul. Larger companies might want to keep micro-experimenting but focus on a limited set of truly strategic vendors who can fit within their larger enterprise architecture, security and business goals before deciding whether to keep at it.

Other QOMPLX Ideas posts:

The Provenance of Data-Driven Decision Making

Ahead of Digital Transformation, Address Security Fundamentals

When should you start a Tech Program?

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