3 ways companies will operate differently in 2023

Check out all the on-demand sessions from the Intelligent Security Summit here.

It’s now abundantly clear that work itself has changed. There is no going back.

But this is about more than just enabling remote work or digital transformation. Every company must be prepared for a profound shift in how they operate as a team, from fundamental business processes to the technologies they deploy.

We are now realizing that the way we’ve been running our companies is inefficient, exclusive, and in many cases, risky. It’s not enough to modernize our tools, prioritize cloud migration, or deploy dozens of new apps to keep people connected. In fact, to focus on those is to put the cart before the horse. The real challenge is evolving our company culture — how do we empower everybody to contribute, no matter where they live, in a secure, efficient, and scalable way?

Many companies will maintain the status quo and deem company operations a non-urgent matter. But the ones that will be successful long term will recognize that prioritizing how they operate is precisely how they will continue to innovate and surpass the competition. Here are three ways they’ll do it.


Intelligent Security Summit On-Demand

Learn the critical role of AI & ML in cybersecurity and industry specific case studies. Watch on-demand sessions today.

Watch Here

Companies will begin to operate an open-source mindset

As many companies continue to struggle to adapt to a more distributed workforce, they will turn to organizations that have proven for years that it is possible to create a collaborative, self-service environment of any size, no matter where its members live: Open source communities.

No longer just a software development process for hobbyist groups and smaller organizations, commercial companies are realizing that open source is also the mindset that everybody should be able to contribute. In fact, it is this mindset that allows open source teams to be more than the sum of their parts, creating innovative products and services in multiple categories.

Much of their speed comes from the way they operate, such as prioritizing asynchronous work, establishing governance models over enforcing singular leadership styles, and providing access to critical information by default, including documentation or even discussions among business leaders. Open source communities also avoid traditional, slow-moving product feedback channels by making their product’s code source-available and inviting their customers to co-create products together.

In the coming year, commercial companies will begin to adopt some of these open source practices, and they will be more transparent, inclusive, and collaborative as a result.

Every company must become a security company

In the past, the challenge facing every company was becoming a software company. Those that didn’t make the digital transformation leap found themselves disrupted and left behind. Now, with increasing security threats and a more distributed workforce, every company must also become a security company.

In the latest GitLab global DevSecOps survey, half of security professionals reported that developers fail to identify 75% of security issues. This poses huge risks for companies, and business leaders are recognizing that it’s no longer enough to develop great products and services. They must also be great at operating them and keeping them secure.

In 2023, companies will respond by making security a core part of their culture and a core capability of their product development process. This includes creating dedicated development security operations teams (DevSecOps), embedding security and compliance practices into their developer tools, and using AI to automatically scan for vulnerabilities before products and services reach the hands of customers.

This is not just a defensive move, but a proven proactive one that leads to fewer security incidents, less time spent taking corrective action and increased and secure productivity.

AI becomes essential for efficiency and productivity

Today’s knowledge workers face a concerning paradox: They’re being asked to do more, with fewer resources, but also too many tools. This leads to a decrease in overall productivity, as many tasks become either too difficult, or too repetitive. Rather than simply attack problems with more staff and tools, companies will turn to AI to help automate both difficult and repetitive tasks to increase productivity for all workers across every department.

Imagine software developers that can focus on building and delivering code, and not on scanning for security vulnerabilities. Sales team members who spend time on planning strategies to hit revenue goals, and not data entry and data cleaning. Marketers that focus on messaging and customer relationships, instead of maintaining lists of contacts.

Companies that use AI to automate inefficient tasks will free up their knowledge workers to focus on the creative ones, leading to increased productivity, more opportunities to innovate, and ultimately a competitive advantage.

Bottom line: Company culture and security before transformation and innovation

Technology is moving fast, and companies are under pressure to rein in spending while delivering the next big thing. The most successful companies, however, will look at the broader perspective. Rather than spending time chasing transformation and innovation, they will focus on how they operate as a company. That focus will foster a culture that allows all knowledge workers to develop transformative and innovative ideas together in the new year and beyond.

Ashley Kramer is CMO and CSO at GitLab.


Welcome to the VentureBeat community!

DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.

If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.

You might even consider contributing an article of your own!

Read More From DataDecisionMakers

Source link

Leave a Comment