In the war for talent, sometimes the solution is right in front of you. For businesses struggling to compete for tech talent, investing in your current talent through upskilling and training initiatives can provide invaluable returns, as many IT leaders are finding.

A study from Korn Ferry estimates that by 2030 more than 85 million jobs will go unfilled due to a lack of available talent, a talent shortage that could result in the loss of $8.5 trillion annual revenue globally. While automation may be able to fill some gaps, the study also posits that human capital will be just as important as automation in the future, leaving organizations without robust training programs subject to the whims of a talent market in short supply.

According to the National Bureau of Economic Research, companies have steadily dropped the ball on workforce training and upskilling since the 1970s. Oftentimes, workers are pushed to meet skills gaps without the necessary training, setting the employee and business up for potential failure. But shifts in workforce strategies in recent years have seen more companies developing strong internal training programs to reskill, upskill, and promote employees within the organization.

In addition to helping fill skills gaps, investing in the career growth of your employees can also foster a greater sense of trust, leading to a more resilient and productive workforce that is less likely to quit, according to data from Gallup. The return on investment in internal workforce training and upskilling programs can’t be overlooked, as the successes of the following four companies can attest.

Capital Group invests in careers for the long run

For financial services company Capital Group, the secret to competing in a tight IT talent market is to stay focused on a long-term employee investment strategy. Capital Group leadership believes employee satisfaction is just as important as customer satisfaction, and a key part of that is ensuring that employees have ample opportunity to grow their careers within the company. This includes internal bootcamps, courses for developing subject matter expertise, and an internal talent marketplace that gives employees more mobility within the organization.

Employees can also explore various career paths within Capital Group through its Technology Rotational Experience (TREx) program, a 25-month career development program that places participants across three different IT teams. Through TREx, employees can gain experience in other departments, work with new technologies, and identify whether there’s something new that they might be interested in working on moving forward.

“We focus on the long term,” says Global CIO Marta Zarraga. “Every single decision we make is based on the healthiness of the organization long term.”

And that includes ensuring employees can stay and grow with Capital Group, rather than leaving the organization to move their careers forward. TREx and other internal training programs, which include bootcamps, “learning journeys” for developing subject matter expertise, and mentorships, make employees feel valued and reinforce the organization’s culture of growth and learning, while also meeting organizational talent needs in IT departments.

“I can show up as myself and develop the skills and confidence for my career in software development within the financial industry. From early on my contributions at work have been respected, and I’ve found it very easy to reach out and ask questions to people on different teams,” says Aimee Oz [they/them], a software development engineer at Capital Group who participated in an internal bootcamp.

Progressive bootcamp bridges skills gap

Insurance company Progressive has developed an in-house IT Programmer Bootcamp to reskill non-technical staff for technical roles within the organization to meet skills and talent gaps in the organization. And by turning inward to find qualified candidates within its own workforce, Progressive can also leverage the wealth of knowledge candidates already have about the organization, while “knocking down some of those barriers of eligibility for some of these tech jobs,” says Stephanie Duca, leadership development consultant at Progressive, and leader of the IT Bootcamp program.

The pilot program was launched in 2021 with eight participants who came from non-IT roles such as customer support, underwriting, and claims. Employees attend the 15-week intensive training program full-time and are compensated for their time in the program, ensuring they will be able to focus entirely on the training. Employees do not need to have a background in tech to join the program and they are guaranteed a job placement along with adjusted compensation to reflect their new role. Progressive plans to continue expanding this program to include other areas of focus, such as data analytics roles.

“I just know that it’s sparked some real passion and an appreciation for Progressive — our employees see that we want to invest in them and keep them here and retain them,” says Duca.

Altria’s career development focus reaps rewards

Fostering career development is a key strategy for retaining vital talent. At tobacco company Altria Group, employees are given the chance to engage in upskilling and training, gain experience working in departments outside their own, and utilize the company’s structured career planning process. In fact, Altria’s dedication to investing in employees earned them first place for career development on IDG’s Best Places to Work 2021 survey.

Career development is a focus for all employees, even entry-level workers, and everyone is given several opportunities to grow their skills and learn new technologies. For example, an entry-level code developer at Altria will be thrown into highly technical work right away, so they gain experience fast. And then throughout their first five to six years with the company, they will be moved around IT departments to work on different projects, gaining more experience and potentially finding out what they’re most passionate about.

“In many cases, we’re trying to put them into a role that ultimately is going to make them sweat — it’s going to really challenge them,” says Dan Cornell, vice president and CIO of Altria Group.

Employees also go through an annual talent planning review process to assess where they are in their careers, what they aspire to within the organization, and how they want to shape their career moving forward. Managers can identify areas for growth, what skills can be developed, opportunities for training, and potential experiences in other departments they might benefit from. There’s also a heavy focus on helping employees pave a career path if they aren’t interested in leadership positions. Oftentimes, it can feel like the only way up is the leadership path, but helping employees discover there are other paths within the organization can go a long way for retention.  

Talent development pays off at Capital One

Upskilling and cross-training programs are key factors in improving employee productivity, retaining top talent, and filling skills gaps. Financial services company Capital One focuses on “developing the whole person” by leveraging internal professional development programs, including a full-stack development academy, the Capital One Developer Academy (CODA), and Capital One Tech College.

With over 11,000 engineers across more than 2,000 agile teams, Capital One has worked to run individual teams as if they’re each a small business. It’s a strategy that allows the large organization to stay agile, while also attracting and retaining engineering talent through the promise of getting to work on open-source projects, in an agile environment, and on a small team.

“It keeps a big company very nimble, creates that autonomy and then drives a lot of that team dynamic and team culture down into the other groups of folks that are releasing software every day of every week to our customers and our associates,” says Mike Eason, senior vice president and CIO of enterprise data and machine learning engineering at Capital One.

Its CODA initiative is a six-month software engineering program for full-time Capital One employees to learn full-stack development principles. It helps employees inside or outside of IT get the training they need to become a software engineer within the organization. The Capital One Tech College focuses more on upskilling employees through free training and certification courses, with opportunities to attend in-person and online courses on their own time. The investment in employees helps Capital One retain its best tech talent, while also cultivating stronger tech skills and expertise through the ranks.

IT Skills, IT Training 

By Milan Shetti, CEO Rocket Software

According to a recent Rocket Software survey, 80% of IT professionals categorize the mainframe as critical to their business. But in order to be successful in today’s technology-driven world, businesses that rely on the mainframe must modernize their operations and integrate the latest tools and technologies. Companies choosing to abandon their mainframe face a costly endeavor, risk downtime, and lose out on powerful benefits. Modernizing in place allows businesses to continue leveraging their technology investments through modernization without sacrificing the many benefits provided by mainframes.

One technology that modern mainframes need is secure open-source software. Four years ago, the Linux Foundation’s Open Mainframe Project introduced Zowe, a first-of-its-kind open-source framework based on z/OS, making it easier than ever to connect the gap between modern applications and the mainframe. Rocket Software is a founding member of the Zowe coalition, and our engineers have played an integral role in the evolution of the Zowe open-source framework. Open-source technologies provide organizations with the responsiveness and adaptability they need to implement advanced tools and practices that balance developers desire to work with the latest technology and organizational need for security and support.

Read on to learn more about why modern mainframes need secure open source.

Benefits of modernizing the mainframe

There is no denying the importance of mainframes within the enterprises that use them. Respondents to Rocket’s survey say the top three qualities that contribute to their organization’s reliance on the mainframe are reliability (34%), security (27%), and efficiency (22%). Modernizing in place is a great way for mainframe-reliant businesses to meet demands while positioning themselves for future success with an efficient and sustainable IT infrastructure.

Open-source software provides many benefits that can help businesses modernize mainframe development through capabilities that drive application and infrastructure modernization, accelerate application development, and enable the next generation of developers. Through DevOps/AppDev solutions, businesses can bring the accessibility of open source to the mainframe while ensuring the compliance and security of their system’s data. By automating processes, organizations can easily implement modern application development practices while ensuring compliance to organizational standards and business rules. Because of the development of open DevOps/AppDev solutions, businesses can bring applications to market faster, at lower cost, and with less risk.

Why the mainframe needs secure open source

Open-source solutions can provide the mainframe with a litany of benefits, but like any other technology, open source is not foolproof and comes with its own challenges. One of the main open-source challenges is regarding its security as applications are developed and delivered to and from the mainframe. Organizations are also concerned that if there are vulnerabilities found in open-source software, they will take a long time to fix. 

To overcome these challenges, organizations must take a security-first mindset and partner with industry-leading vendors to ensure that they have the capabilities to identify vulnerabilities and make fixes in time to mitigate security risks. For example, Rocket Support for Zowe gives users access to modern capabilities from the Open Mainframe Project’s Zowe open-source framework that makes it easier to interface and develop applications while providing 24/7 support, security, and compliance assurance.

The mainframe has been around for more than 50 years, and with the ability to integrate the latest technologies to match today’s business needs, it’s not going anywhere. Modernizing mainframe development with open-source software will enhance development practices while ensuring compliance to organizational standards and business rules.

To learn more about the power of open source on the mainframe, visit our website.

Digital Transformation

Few would swap sunny San Francisco and the innovation of Silicon Valley for a train ticketing company serving disgruntled UK commuters, but try telling that to Trainline CTO, Milena Nikolic.

A long-time Googler, who’s role as engineering director saw her lead the Google Play developer ecosystem, Nikolic was keen for something new that offered a greater sense of social purpose.

I had been at Google for so long that I stopped counting,” she says. “It was close to 13 years… and I was itching for a bit of a change.”

In a growing technology market, Nikolic waited for the right opportunity. Nothing clicked until she spoke to Trainline, the international digital rail and coach technology platform, headquartered in London.

“Everything fell in place; every box was ticked,” she says. “I really liked the mission, connecting people to places in greener, more sustainable ways.”

The first 100 days

As the new CTO tasked with setting the technical strategy, ensuring tech team delivery, and aligning product and business strategies, Nikolic had a lot on her plate for the first 100 days.

She spent time understanding the tech stack, the business challenges, and a comprehensive technology team split across infrastructure, product development, security, privacy and technical compliance.

Trainline had sound technical systems and a good level of autonomy, but Nikolic believed the team members themselves felt less empowered to move out of their comfort zone, which impacted business outcomes.

“We had engineers who were very good specialists in their field, but I think people felt less empowered to really own goals and outcomes end-to-end,” she says. “They’re all these brilliant individuals who have a lot to add beyond coding their part of the technical system. They were more stuck to their part of the technical stack, and just contributing to that.”

This reflection pushed Nikolic to make changes to how technology teams worked across the organisation, and support a new target operating model.

Driving business growth through new teams

Trainline has been a tech-enabled business since it launched in 1997, with online ticket sales available as far back as 1999. More recently, under the tutelage of former CTO Mark Holt, Trainline became a story of scale and mobility, moving to DevOps, agile principles and leveraging compute power through Amazon Web Services (AWS).

By 2018, the Trainline platform was hosting more than 80 million customer visits a month, with more than 80% coming through mobile devices. The company sold more than 204 tickets every minute.

Today, its Platform One, with 78 million visits every month across all channels, covers more than 270 rail and coach companies across 45 countries, including over 80% of rail routes in Europe.

Milena Nikolic

Such growth in scale has resulted in a steady ramp-up in resources. Despite the COVID-19 pandemic pushing the business to reach almost £250m in debt in 2021 (the firm has since recovered to achieve net ticket sales of £2.5bn and a net profit of £90m in its latest financial results), Trainline now employs around 400 engineers, data and tech specialists who work on Platform One and process over 600 system releases every week. The company has approximately 800 staff in total across the business.

Since joining a year ago, Nikolic has split teams into horizontal and vertical functions to support operational efficiency and product development.

Horizontal team members own the platforms to ensure their robustness, reliability, latency and scalability so engineers can be productive. Vertical teams, meanwhile, operate across the tech stack so teams aren’t localised to certain operating systems, orchestration or data layers. These cross-functional teams, including product support, UX and data, offer differing levels of expertise across both front and back-end infrastructure.

“Those teams have a clear mission… that they own the product or business outcome,” says Nikolic. “They have full autonomy to decide whatever they want to do… to drive that goal, that mission and move that [business] metric in the way we expect.”

Training engineers and building products

As part of reskilling teams, Nikolic has focused on building a T-shaped skillset and giving staff the opportunity to gain broader experience. For example, she says that an iOS developer could learn eCommerce, or a web developer could study back-end infrastructure.

There have been a number of vehicles to do that, from an internal ‘tech summit’ with speakers from within and outside Trainline presenting on all things tech, product and data, to a ‘culture of craft’ community that offers regular activities, such as coding dojos, workshops, hackathons and meetups. The company also provides access to the tech learning platform O’Reilly, where team members can attend live conferences, and access books and content.

The team has celebrated numerous achievements inside her first year. Nikolic says Trainline now has a robust and scalable platform capable of withstanding 10 times search traffic and transactions, while the company recently launched STicket barcode technology to reduce friction to buy and prevent fraud. It’s also launched delay notifications in France and the UK—a smart move considering a combined 600 train delays every minute, while Trainline’s new Where next? app integrates with Apple MapKit so iOS users can plan their journey without having to leave the app.

Platform One is the solid base for all tech and innovation at Trainline, with microservices and infrastructure-as-code (IaaC) both in vogue.

“Our tech stack is built on a solid foundation provided through AWS,” she says. “By utilising a variety of technologies, such as EC2, ECS, Fargate, Kinesis and RDS, Trainline is able to achieve a hyper-scale infrastructure necessary to enable us to provide our customers with a best-in-class platform.”

Getting more women in engineering

Having worked in the industry for 15 years, Nikolic remains frustrated with a leaky pipeline when it comes to women in engineering. She admits that the tech industry can still feel less inclusive to women, and this ‘societal problem’ can push women to leave the sector mid-career.

“It’s difficult, for sure,” she says, “and, having been part of this fight for 15 years, it can sometimes be disheartening, just how slow the pace of change is.”

Nikolic is, however, hopeful that the industry can improve the representation gap. She points to examples at Trainline, where the firm has introduced diverse recruitment panels and D&I targets, as well as partnerships with coding tech school ADA in Paris and Future Frontiers, a charity equipping students from disadvantaged backgrounds across 200 secondary schools in London and Edinburgh.

She believes the key to improving the numbers of women in engineering is adding more talent at the top of the pipeline, such as encouraging disadvantaged groups from school into early stage careers.

“The only sustainable way for us to prove this is break the barriers for underrepresented groups as they enter the tech world,” she says.

Trainline remains on an upward trajectory. There’s a reported international expansion on the horizon, government contracts to win and a new CDO, hired from Meta, now reporting into Nikolic. “I really want to make sure we execute well,” she says. ”If there’s anything keeping me up at night, it’s making sure the team is set up for success in the best possible way so we capitalise on these opportunities.”

CIO, Digital Transformation, IT Skills, Women in IT

How do attackers exploit applications? Simply put, they look for entry points not expected by the developer. By expecting as many potential entry points as possible, developers can build with security in mind and plan appropriate countermeasures.

This is called threat modeling. It’s an important activity in the design phase of applications, as it shapes the entire delivery pipeline. In this article, we’ll cover some basics of how to use threat modeling during development and beyond to protect cloud services.

Integrating threat modeling into the development processes

In any agile development methodology, when business teams start creating a user story, they should include security as a key requirement and appoint a security champion. Some planning factors to consider are the presence of private data, business-critical assets, confidential information, users, and critical functions. Integrating security tools in the continuous integration/continuous development (CI/CD) pipeline automates the security code review process that examines the application’s attack surface. This code review might include Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST), and Infrastructure as a Code (IaC) scanning tools.

All these inputs should be shared with the security champion, who would then identify the potential security threats and their mitigations and add them to the user story. With this information, the developers can build in the right security controls.

This information also can help testers focus on the most critical threats. Finally, the monitoring team can build capabilities that keep a close watch on these threats. This has the added benefit of measuring the effectiveness of the security controls built by the developers.

Applying threat modeling in AWS

After the development phase, threat modeling is still an important activity. Let’s take an example of the initial access tactic from the MITRE ATT&CK framework, which addresses methods attackers use to gain access to a target network or systems. Customers may have internet-facing web applications or servers hosted in AWS cloud, which may be vulnerable to attacks like DDoS (Distributed Denial of Service), XSS (Cross-Site Scripting), or SQL injection. In addition, remote services like SSH (Secure Shell), RDP (Remote Desktop Protocol), SNMP (Simple Network Management Protocol), and SMB (Server Message Block) can be leveraged to gain unauthorized remote access.

Considering the risks, security teams should review their security architecture to ensure sufficient logging of activities, which would help identify threats.

Security teams can use the security pillar of AWS Well-Architected Framework, which will help identify any gaps in security best practices. Conducting such a self-assessment exercise will measure the security posture of the application across various security pillars – namely, Identity Access Management – to ensure there is no provision for unauthorized access, data security, networking, and infrastructure.

Although next-gen firewalls may provide some level of visibility to those who are accessing the applications from source IP, application security can be enhanced by leveraging AWS WAF and AWS CloudFront. These services would limit exposure and prevent potential exploits from reaching the subsequent layers.

Network architecture should also be assessed to apply network segmentation principles. This will reduce the impact of a cyberattack in the event one of its external applications is compromised.

As a final layer of protection against initial access tactic methods, security teams should regularly audit AWS accounts to ensure no administrator privileges are granted to AWS resources and no administrator accounts are being used for day-to-day activities.

When used throughout the process, threat modeling reduces the number of threats and vulnerabilities that the business needs to address. This way, the security team can focus on the risks that are most likely, and thus be more effective – while allowing the business to focus on truly unlocking the potential of AWS.

Author Bio


Ph: +91 9176292448


Raji Krishnamoorthy leads the AWS Security and Compliance practice at Tata Consultancy Services. Raji helps enterprises create cloud security transformation roadmap, build solutions to uplift security posture, and design policies and compliance controls to minimize business risks. Raji, along with her team, enables organizations to strengthen security around identity access management, data, applications, infrastructure, and network. With more than 19 years of experience in the IT industry, Raji has held a variety of roles at TCS which include CoE lead for Public Cloud platforms and Enterprise Collaboration Platforms.

To learn more, visit us here.

Internet Security

Technology is hardly the only industry experiencing hiring challenges at the moment, but resignations in tech still rank among the highest across all industries, with a 4.5% increase in resignations in 2021 compared with 2020, according to Harvard Business Review.

For the most part, these employees aren’t leaving the industry altogether; they’re moving to companies that can offer them what they want. Flexible schedules and work-life balance? 

Absolutely. Higher salaries? Of course. But one of the primary reasons why people in tech, particularly developers, switch or consider switching roles is because they want more opportunities to learn. Developers don’t want to quit: they want to face new challenges, acquire new skills, and find new ways to solve problems.

Ensuring access to learning and growth opportunities is part of the mandate for tech leaders looking to attract and retain the best people. A culture of continuous learning that encourages developers to upskill and reskill will also give your employees every opportunity to deliver more value to your organization.

Read on to learn how and why expanding access to learning helps you build higher-performing teams and a more inherently resilient organization.

Developers want more learning opportunities — and leadership should listen

Giving developers opportunities to learn has a major, positive impact on hiring, retention, and team performance. According to a Stack Overflow pulse survey, more than 50% of developers would consider leaving a job because it didn’t offer enough chances for learning and growth, while a similar percentage would stick with a role because it did offer these opportunities. And 50% percent of developers report that access to learning opportunities contributes to their happiness at work.

Yet most developers feel they don’t get enough time at work to devote to learning. Via a Twitter poll, Stack Overflow found that, when asked how much time they get at work to learn, nearly half of developers (46%) said “hardly any or none.” Considering that more than 50% of developers would consider leaving a job if it didn’t offer enough learning time, it’s clear that one way to help solve hiring and retention challenges is to give employees more chances to pick up new skills and evolve existing ones.

How can tech leaders and managers solve for this? One key is to create an environment where employees feel psychologically safe investing time in learning and asking for more time when they need it. High-pressure environments tend to emphasize wasted time (“How much time did you waste doing that?”) instead of invested time (“I invested 10 hours this week in learning this”). In this context, plenty of employees are afraid to ask about devoting work time to learning.

Company leadership and team managers can make this easier by consistently communicating the value of learning and modeling a top-down commitment to continuous learning. Executives and senior leaders can share their knowledge with employees through fireside chats and AMAs to underscore the importance of this culture shift. Managers should take the same approach with their teams. You can’t expect your more junior employees to invest time in learning if you haven’t made it clear, at every level of your organization, that learning matters.

Expanding learning opportunities improves team performance and organizational resiliency

Elevating the importance of learning helps sustain performance and competency in your engineering teams. But it does more than improve retention or team-level performance: it also builds organizational resiliency.

Some of your employees are always going to leave: to seek new adventures, to combat burnout or boredom, to make more money. Leadership no longer has the luxury of hiring for a specific skill and then considering that area covered forever. Technology and technology companies are changing too fast for that. Retaining talent is certainly important, but ultimately leaders should be focused on creating organizations that are resilient rather than fragile. The loss of one or two key individuals shouldn’t impede the progress of multiple teams or disrupt the organization as a whole.

There’s nothing you can do to completely eliminate turnover, but you can take steps to make your organization more resilient when turnover inevitably occurs:

Ensure that your teams don’t break when people leave. Incorporating more opportunities to learn into your developers’ working lives helps offset the knowledge and productivity losses that can happen when employees move on, taking their expertise with them. How many times have you heard a variation of this exchange: “How does this system/tool work?” “I don’t know; go ask [expert].” But what happens when that expert leaves? Resilient teams and organizations don’t stumble over the loss of a few key people.Give employees access to the learning opportunities they want. As we’ve said, developers prize roles that allow them to learn on the job. Access to learning opportunities is a major factor they weigh when deciding whether to leave a current job or accept a new one. Expanding learning opportunities for developers makes individual employees happier and more valuable to the organization while increasing organizational resiliency.Avoid asking your high-performers to do all the teaching. Implicitly or explicitly asking your strongest team members to serve as sources of truth and wisdom for your entire team is a bad idea. It sets your experts up for unhappiness and burnout, factors likely to push them out the door. Create a system where both new and seasoned employees can self-serve information so they can unstick themselves when they get stuck.

Four steps to prioritize learning and attract/retain high-performance teams

When it comes to learning, there are four major steps you can take to attract and retain the best talent and increase organizational resiliency.

1. Surface subject matter experts.

Your team has questions? Chances are, someone at your company has answers. There are experts (and potential experts) throughout your organization whose knowledge can eliminate roadblocks and improve processes. Your challenge is to uncover these experts — and plant the seeds for future experts by giving your employees time to learn new skills and investigate new solutions.

Lower the barrier to entry by making it fast, simple, and intuitive for people to contribute to your knowledge platform. Keep in mind that creating asynchronous paths for your employees to find and connect with experts enables knowledge sharing without creating additional distractions or an undue burden for those experts.

How Stack Overflow for Teams surfaces subject matter experts:

Spotlights subject matter experts (SMEs) across teams and departments to connect people with questions to people with answersEnables upskilling and reskilling by allowing teams and individuals to learn from one anotherAsynchronous communication allows employees to ask and answer questions without disrupting their established workflowsQ&A format lowers barriers to contribution and incentivizes users to explore and contribute to knowledge resources

2. Capture and preserve knowledge

Establishing practices to capture and preserve information is essential for making learning scale. The goal is to convert individual learnings and experiences into institutional knowledge that informs best practices so that everyone, and the organization as a whole, can benefit. That knowledge should be easily discoverable and its original context preserved for future knowledge-seekers. To capture and preserve knowledge effectively, you also need to make it easy for users to engage with your knowledge platform.

How Stack Overflow for Teams captures and preserves knowledge:

Collects knowledge continuously to preserve information and context without disrupting developers’ workflowsMakes knowledge searchable, so employees can self-serve answers to their questions and find solutions others have already worked outCompared with technical documentation, Q&A format requires a shorter time investment for both people with questions and people with answers

3. Make information centralized and accessible

The good news is that nobody at your company has to know everything. They just need to know where to find it. After all, knowledge is only valuable if people can locate it when they need it. That’s why knowledge resources should be easy to find, retrieve, and share across teams.

This is particularly critical as your organization scales: new hires can teach themselves the ropes without requiring extensive, synchronous communication with more seasoned employees who already have plenty of responsibilities and find themselves answering the same questions over and over again.

How Stack Overflow for Teams makes information centralized and accessible:

Makes information easy to locate, access, and shareSpeeds up onboarding and shortens time-to-value for new hiresAllows users to make meaningful contributions to knowledge resources without investing huge amounts of time or interrupting their flow state

4. Keep knowledge healthy and resilient

Knowledge isn’t immune to its own kind of tech debt. The major problem with static documentation is that the instant you hit Save, your content has started its steady slide toward being out of date. Like code, regardless of its scale, information must be continually maintained in order to deliver its full value.

Keeping content healthy — that is, fresh, accurate, and up-to-date — is essential. When your knowledge base is outdated or incomplete, employees start to lose trust in your knowledge. 

Once trust starts eroding, people stop contributing to your knowledge platform, and it grows even more outdated. Since SMEs are often largely responsible for ensuring that content is complete, properly edited, and consistently updated, keeping content healthy can be yet another heavy burden on these individuals. That’s why a crowdsourced platform that encourages the community to curate, update, and improve content is so valuable.

How Stack Overflow for Teams keeps knowledge healthy and resilient:

Our Content Health feature intelligently surfaces knowledge that might be outdated, inaccurate, or untrustworthy, encouraging more engagement and ensuring higher-quality knowledge resourcesContent is curated, updated, and maintained by the community, reducing the burden on SMEsThe platform automatically spotlights the most valuable, relevant information as employees vote on the best answers, thereby increasing user confidence in your knowledge

Resiliency requires learning

You can’t build a resilient organization without putting learning at the center of how your teams operate. Not only is offering access to learning and growth opportunities a requirement for attracting and retaining top talent, but fostering a culture of continuous learning protects against knowledge loss, keeps individuals and teams working productively, and encourages employees to develop skills that will make them even more valuable to your organization.

To learn more about Stack Overflow for Teams, visit us here

IT Leadership

Organizations are increasingly focused on diversity, equity, and inclusion in their hiring practices and workplace culture not only because it’s the right thing to do, but by not doing so, it can be detrimental to the business.

With software at the core of every business, and organizations deriving more value and insights from their data collected by the software, having non-diverse data sets and software can result in products and services that only cater to a specific group of people and under-serves another, or worse, harms them. The reality is that developers and data scientists encode their beliefs, conviction, and bias – most often unconsciously – in their data and when they design software.

We’ve already seen in real life the negative impacts of when data science and software development go unchecked without considering DE&I. For example, in an early attempt by Amazon to design a computer program to guide its hiring decisions, the company used submitted resumes from the previous decade as training data. Because most of these resumes came from men, the program taught itself that male candidates were preferable to women. While Amazon realized this tendency early on and never used the program to evaluate candidates, the example highlights how relying on biased data can reinforce inequality.

Ultimately, these issues come up not because of malicious intent but rather being “blind” or ignorant of all viewpoints and potential outcomes that groups of people experience differently. The best way to mitigate and avoid the problem is to have a team with a diverse representation spanning various professional backgrounds, genders, race, ethnicities, and so on. A diverse team can look at each stage of building and managing data pipelines (collecting, cleansing, etc.) and the software delivery process considering all kinds of outcomes.

While we are seeing developments and improvements in increasing diversity in data science and software roles, more needs to be done. A 2020 study in AI suggests that while data science is a rather new field and will take time to respond to diversity initiatives, some of the efforts to increase diversity in other tech fields may be succeeding. Over the past several years, numerous diverse conferences and coding events have been developed, with participation rates rapidly growing.

One of the first places to start is committing to hiring diverse candidates, and fostering an inclusive workplace culture that retains and ensures the ongoing development of diverse teams. Likewise, managers must ensure they create an inclusive and open culture that gives a voice to underrepresented talent.

From there, ensuring the integrity of your organization’s data and software delivery can start to take shape.

How to ensure the integrity of your data and its outcomes

As we know, the ramifications of biased data can impact society as a whole, so having the right data set and applying it correctly is important. Programmatically, software teams have a lifecycle that they follow – collecting the data, cleaning and classifying it, then writing code that uses that data, and testing it to deliver outcomes that meet business and customer needs. Having a diverse set of people working throughout every step of the lifecycle will help organizations avoid some of these pitfalls mentioned earlier.

Spending time on defining what’s a “good” data set that will deliver equitable outcomes is key to ensuring the integrity of your data. Specifically, when looking at a data set, teams should consider if the outcome can be detrimental or if there is anything to learn from it. They should ask questions like, what does good look like, where could there be biases, what populations can be harmed by this? If the data doesn’t represent the population, you can expect to get bad outcomes or output from that data set. Through the data collection process, make sure you’re collecting all viewpoints, not throwing away critical information, and feeding into the data with the notion of what will result in “good” outcomes.

The iterative nature of software development also gives teams the opportunity to continuously course correct as they see issues within the data, where data may be ‘contaminated’ with personal biases, and constantly adjust.

Addressing issues of unconscious bias at every stage of the product life cycle starting from strategy to product definition, requirements, user experience, engineering, and product marketing will ensure organizations are delivering software that meets more needs. Likewise, diverse teams working on data sets and software that’s equitable and more inclusive can drive innovation that creates competitive advantage, enhances the customer experience, and improves service quality – all of which can lead to greater business outcomes.

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Collaboration Software, IT Leadership

Many companies that begin their AI projects in the cloud often reach a point when cost and time variables become issues. That’s typically due to the exponential growth in dataset size and complexity of AI models.

“In an early phase, you might submit a job to the cloud where a training run would execute and the AI model would converge quickly,” says Tony Paikeday, senior director of AI systems at NVIDIA. “But as models and datasets grow, there’s a stifling effect associated with the escalating compute cost and time. Developers find that a training job now takes many hours or even days, and in the case of some language models, it could take many weeks. What used to be fast, iterative model prototyping, grinds to a halt and creative exploration starts to get stifled.”

This inflection point related to the increasing amount of time needed for AI model training — as well as increasing costs around data gravity and compute cycles — spurs many companies to adopt a hybridized approach and move their AI projects from the cloud back to an on-premises infrastructure or one that’s colocated with their data lake.

But there’s an additional trap that many companies might encounter. Paikeday says it occurs if they choose to build such infrastructure themselves or repurpose existing IT infrastructure instead of going to a purpose-built architecture designed specifically for AI.

“The IT team might say, ‘We have lots of servers, let’s just configure them with GPUs and throw these jobs at them’,” he says. “But then they realize it’s not the same as a system that is designed specifically to train AI models at scale, across a cluster that’s optimized to deliver results in minutes instead of weeks.”

With AI development, companies need fast ROI, by ensuring data scientists are working on the right things. “You’re paying a lot of money for data-science talent,” Paikeday says. “The more time they spend not doing data science — like waiting on a training run, troubleshooting software, or talking to network, storage or server vendors to solve an issue — that’s lost money and a lot of sweat equity that has nothing to do with creating models that deliver business value.”

That’s a significant benefit of a purpose-built appliance for AI models that can be installed on premises or in a colocation facility. For example, NVIDIA’s DGX A100 is meant to be unpacked, plugged in and powered-up enabling data scientists to be productive within hours, instead of weeks. The DGX system offers companies five key benefits to scale AI development:

A hardware design that is optimized for AI, along with parallelism throughout the architecture to efficiently distribute computational work across all the GPUs and DGX systems connected together. It’s not just a system; it’s an infrastructure that scales to any size problem.A field-proven, fully integrated AI software stack including drivers, libraries and AI frameworks that are optimized to work seamlessly together.A turnkey, integrated data center solution that companies can buy from their favorite value-added reseller that brings together compute, storage, networking, software and consultants to get things up and running quickly.The DGX system is a platform, not just a box, from a company that specializes in AI, and has already created state-of-the-art models, including natural language processing, recommender systems, autonomous systems, and more — all of which are continually being improved by the NVIDIA team and made available to every DGX customer.“DGXperts” bring AI-fluency and know-how, giving guidance on the best way to build a model, solve a challenge, or just assist a customer that is working on an AI project.

When it’s time to move an AI project from exploration to a production application, the right choice can speed and scale the ROI of your AI investment.

Discover how NVIDIA DGX A100, powered by NVIDIA A100 Tensor Core GPUs and AMD EPYC CPUs, meets the unique demands of AI.

Artificial Intelligence, IT Leadership