Diversity and inclusion (D&I) have become necessary missions for most businesses. Research has long shown that diverse teams are more productive, more engaged, and the companies that create them are more profitable. And the murder of George Floyd — and the social unrest that followed — made it clear that taking a stand around social justice is necessary to recruitment, retention, and even the viability of your brand.

Despite the requisite commitment and knowledge, however, creating a truly diverse and inclusive workforce takes much more than locating and tapping a diverse hiring pipeline.

According to a recent study in the Harvard Business Review (HBR), organizations of all sizes have made unprecedented investments around diversity, equity, and inclusion (DEI) in the past few years. That same report, though, found that those efforts are not finding the level of success companies had hoped for. Much of the disappointment is not with recruitment, however. It’s with employee retention.

“In a lot of organizations, especially in tech organizations, you get a revolving door,” says Stuart McCalla, managing partner at Evolution. “People come in and then they leave.”

That’s expensive and frustrating for everyone involved.

CIO.com spoke to DEI leaders and experts to uncover the best practices for building diverse teams and a culture that nurtures those teams and individuals to stop the churn and get closer to the organization’s overall D&I goals.

1. Set measurable goals and then measure them

“One of the most important aspects of creating inclusive organizations is about measurement,” says McCalla. “Numbers don’t lie.” You can’t really know how well you are doing at building the inclusive environment you want if you don’t set goals and measure your progress against them. Yet, according to the HBR study, 60% of companies report that they have a DEI strategy but gender representation goals (26%) and race representation goals (16%) are infrequently part of it.

These are not recruitment goals. They are representation goals. Maybe you hired a diverse team for entry-level positions. But where are they now? Did they get promoted and build diversity in your management team? Or did they leave because there was no opportunity for advancement, the company culture didn’t make them feel welcome, or there was bias that’s invisible to your management team but crystal clear to them?

You can use data to identify these issues and prioritize where you need to implement programs, offer training, and focus your efforts.

“If you examine the average tenure of an underrepresented group and discover that it’s less than a year or two, aggregate the exit interview data for that group,” explains McCalla. “If 35% of those folks say they left for a better opportunity, 45% say they were unable to progress in their career, and 20% say their manager didn’t understand their experience, what should you focus on?”

Knowing your goals and how you are performing against those goals gives you a workable plan for improving what needs attention.

The HBR study found that companies do collect this sort of data, but it is underutilized. Most companies collect gender data (90%) and ethnicity data (88%). But when it comes to attrition, only 52% of those companies analyze the data by gender and less than half (40%) look at it through the lens of race and ethnicity. And when it comes to tracking who gets promoted? The numbers drop again.

2. Fix your inclusion problems before you recruit

“The intention has to be there,” says Luan Lam, chief people officer at Harness.io. Like many D&I experts, Lam is a strong advocate of starting a company with a DEI plan already in place, setting the tone for every hire past the founders.

“If you set your intention from the beginning, it builds a framework you can fine-tune as you go along,” he says. In this way, DEI isn’t an afterthought, added during a crisis. It is baked into everything from office design to hiring to pay to processes. “That way, there isn’t a lot of cleaning up to do. You set your intention. You put a plan in place. And you execute against that plan,” he says.

That’s great advice for startups. But if your company is not a startup, it is still important to fix your culture before you recruit. You can’t hope that, somehow, the new hires — simply through their presence — will repair your company culture from within.

“Internally organized inclusion efforts often fall informally on people from diverse backgrounds,” explains Cassandra Shapiro, global head of DEI at Reaktor. “That is extra labor for people who are already facing unequal opportunities or barriers that are invisible to people from the majority. So, to have to create inclusion for people that come in after them is additional work. If organizations don’t find a way to formalize inclusion efforts before they start bringing in more people, people from marginalized backgrounds will not be interested in shouldering that burden and will leave.”

Recruiting a team without assuring that they will be included by your culture is a waste of your resources and efforts.

“When people find an excellent position, interview, join, and realize the culture is not making space for them, it is a monumental waste of effort — on both sides,” says Shapiro.

3. Encourage people to tell their story

A great place to start on this journey is to create forums — Slack groups, employee resource groups, events, and educational opportunities — that establish environments where people can tell their stories.

“If we encourage safe forums for speaking up, we can create a sensitive and mature approach to discussing injustice,” says Nichelle Grant, head of diversity, equity, and inclusion at Siemens USA. “We can create a dialogue that strengthens our organizational culture and builds a more resilient organization as a whole.”

This can be simple to implement and powerful: Invite experts to speak about topics around equity or that throw a spotlight on diverse experiences. Create forums where people can tell their own story and where people are encouraged to listen and respond.

“When you share stories, people automatically sit up and listen,” explains Shapiro. “They find a way to connect their own stories and their own experiences with the stories and experiences you’re sharing. At Reaktor we have open DEI meetings that end up as storytelling sessions. We also do education sessions when there are topics people want to talk about.”

For example, explains Shapiro, “We found an expert on neurodiversity and asked him to speak. The purpose was to educate us on the basics of neurodiversity. But there was also a question-and-answer session where people were buzzing, typing in lots of questions.” That level of interest and curiosity led to Reaktor employees starting a dedicated Slack channel for neurodiversity matters, a safe space for neurodivergent people and advocates to come together. “That is a rich and active place now,” she says.

Creating these channels of inclusion are important for the people who are already there, but they also go a long way towards creating a place that is welcoming to new team members. If a neurodiverse person — or a black woman or trans man — arrives and discovers a Slack channel or an employee resource group already exists with a rich community of like people talking openly to each other, they are more likely to feel welcome.

4. Make leaders accountable to your DEI goals

Managers have an outsized influence on the experience of people on their team so it’s important that they hear these stories around diversity and inclusion, too. Unfortunately, leaders are often the last to hear from discontent team members, especially if they are seen as the problem. Leaders are gatekeepers for promotion, so when they make decisions that are influenced by unconscious bias, it has a ripple effect on the culture.

The HBR story found that for DEI goals to succeed, executives and leaders must be held accountable to them. Yet most DEI plans don’t do this. Only 28% of companies hold C-suite executives accountable for progress against the DEI strategy, 23% for pay equity, 12% for gender diversity, and 5% for racial and ethnic diversity. A mere 7% of companies hold execs accountable for gender diversity in promotions, and 5% are accountabe for racial and ethnic diversity in promotions.

Having a clear process and stated criteria for advancement, too, according to a report from Culture Amp, can move responsibility and decision-making power away from managers so employees believe that bias will not stand between them and opportunities.

“One thing that has been successful for us is to work with leaders and get them ready to hear things that don’t match their current beliefs,” says McCalla. “It can be hard for skilled, competent, successful leaders who have been around to accept the understanding of systemic oppression – how different identities work. It is hard, especially for those leaders. It is an extra layer of complexity and yet this is the leadership skill for the 21st century.”

John Marcante, CIO-in-residence at Deloitte, experienced how hard it is to see the world through a lens that is not your own at an employer-hosted diversity and inclusion event when he was the CIO at Vanguard. “I sat next to a Black executive, and we started sharing stories,” he says. “At the time, my son was learning to drive. We got into a conversation about the stories Black parents tell their sons — especially about keeping their hands on the wheel and not reaching for the glove compartment — as an officer approaches the car. I’ve never taught my son anything like that. It hit me so hard. That was my first understanding that life is very different.”

And understanding how different the lens is for underrepresented groups is a great start. No one can be passionate and engaged in solving a problem they can’t see.

“I think about this as building a practice where I am weaving in behaviors and actions with intention into everything I do, so that it’s part of my job,” explains Libby Maurer, vice president of user experience at HubSpot. “If we’re not doing that, this is just an extra thing on your checklist that doesn’t yield an inclusive environment.”

5. Create ways for people to say what’s wrong

People who experience bias are often hesitant to tell leaders what’s wrong. Overcoming the feeling that nothing will be done about it, that there will be backlash against them, and that speaking up is dangerous to their career is an integral part of living life as an underrepresented group. “Finding avenues for people to speak directly to you while removing any potential backlash that they might feel is so important,” says Shapiro.

Even something as simple as an anonymous Google form where people can say what’s going on can help. Even better? Solicit feedback through anonymous surveys and feedback tools so that you aren’t waiting for someone to experience extreme dissatisfaction before they find the courage to speak.

“We have many listening posts and feedback channels to listen for inclusion issues, lack of inclusion, and a lack of safe environment,” says Maurer.  Without those sorts of listening posts, and even perhaps with them, you will rely heavily on exit interviews to course correct your efforts.

Solicit feedback in those exit interviews and encourage exiting employees to be candid and you will get better data to measure against your goals, change your culture or leaders, expand DEI programs, and clarify systems around pay, equity, and advancement.

“We have an entire system when folks decide to leave,” says Maurer. “So, we can get deep into the drivers for why they made that decision.”

6. Examine the rules and assumption that define your culture

Because life is so different for different slices of the population, it’s important to examine policies and cultural norms that enforce one culture while excluding others. If you have a dress code, ban things like tattoos or piercings, or require people to come to the office at specific times, you may be excluding members of underrepresented communities that you want to hire or be preventing them from bringing their entire self to work, which makes for an exhausting workplace for them.

“How can you encourage people to be authentic if you’re not allowing them to show off their tattoos or piercings and things like that?” asks Adriana Gascoigne, founder and CEO at Girls in Tech. “Do you enable people to be themselves when it comes to their thoughts and feelings? Do you encourage them to generate ideas and come to brainstorms and say what they feel? That is all part of being authentic.”

Most people from underrepresented groups can tell stories about having to change, or hide, who they are to survive or be considered for opportunities and advancement.

“Starting my career at a high-profile social networking company, back in 2008 and 2009, I would go into something I called man mode,” says Gascoigne. “I was climbing the ladder, surrounded by men. The only way I could be respected was if I wore pantsuits, talked in a lower voice, didn’t say anything funny, and was very curt. I had to have lots of slides with numbers and stats. This is very different than who I am as a person.”

Women who fight through that bias to find success are often asked to start all over if they have a child and return to a workplace where maternal bias, the assumption that they are less committed because they are mothers, is rampant.

Overall, women leave the workforce — especially those in leadership roles — in much higher numbers than men. If your data shows a high attrition rate for women, those women know why they are leaving.

“I’ll guarantee you they know why,” says McCalla, as do all underrepresented people who leave. “Maybe you should listen to that why?”

7. Give the DEI leader a seat at the table

In the past five years, there has been a 71% increase worldwide in all DEI roles, according to LinkedIn data. But the HBR study found that work still needs to be done when it comes to listening to the DEI team. It found that 58% of companies have a budget dedicated to DEI but only 21% have a senior role dedicated to this effort. Only 9% have a DEI leader who sits at the same level as other executives. And only 12% of those DEI leaders have a team working for them. The Culture Amp report found that only 34% of DEI leaders reported that they had adequate resources.

Often the DEI role is part of the HR team or an independent person with little say or resources. Empower your diversity people, listen to them, and give them people to help execute against their plan. That will give your DEI effort, according to a recent Time report, “an enterprise-wide mindset and a seat at the decision-making table.”

“Companies can’t just talk about their mission around diversity, equity, and inclusion,” says Marcante. “We have to be adamant about getting the message out that we are committed to diversity — at all levels of the company. We are committed to transparency and equal pay. Actions matter, too. Are the senior leaders sponsoring employee resource groups and diverse talent? Does the diverse talent in the organization get access to senior leaders?” How diverse is your senior leadership team? “That’s the only way we change this.” 

Diversity and Inclusion, IT Leadership, Staff Management, Women in IT

What is project management?

Project management is a business discipline that involves applying specific processes, knowledge, skills, techniques, and tools to successfully deliver outcomes that meet project goals. Project management professionals drive, guide, and execute company-identified value-added goals by applying processes and methodologies to plan, initiate, execute, monitor, and close all activities related to a given business project in alignment with the organization’s overall strategic objectives.

Project management steps

Project management is broken down into five phases or life cycle. Each phase intersects with any of 10 knowledge areas, which include: integration, scope, time, cost, quality, human resources, communication, risk procurement, and stakeholder management. The phases, processes and associated knowledge areas provide an organized approach for project managers and their teams to work through projects, according to the following outline:

Initiating phase:

Integration management: Develop project charter.
Stakeholder management: Identify stakeholders.

Planning phase:

Integration management: Develop project management plan.
Scope management: Define scope, create work breakdown structure (WBS), gather requirements.
Time management: Plan and develop schedules and activities, estimate resources and timelines.
Costs management: Estimate costs, determine budgets.
Quality management: Identify quality requirements.
Human resource management: Plan and identify human resource needs.
Communications management: Plan stakeholder communications.
Risk management: Perform qualitative and quantitative risk analysis, plan risk mitigation strategies.
Procurement management: Identify and plan required procurements.
Stakeholder management: Plan for stakeholder expectations.

Execution phase:

Integration management: Direct and manage all project work.
Quality management: Performing all aspects of managing quality.
Human resource management: Select, develop, and manage the project team.
Communications management: Manage all aspects of communications.
Procurement management: Secure necessary procurements.
Stakeholder management: Manage all stakeholder expectations.

Monitoring and controlling phase:

Integration management: Monitoring and control project work and manage any necessary changes.
Scope management: Validate and control the scope of the project.
Time management: Control project scope.
Costs management: Controlling project costs.
Quality management: Monitor quality of deliverables.
Communications management: Monitor all team and stakeholder communications.
Procurement management: Keep on top of any necessary procurements.
Stakeholder management: Take ownership of stakeholder engagements.

Closing phase:

Integration management: Close all phases of the project.
Procurement management: Close out all project procurements.

Stakeholder expectations

Stakeholders can be any person or group with a vested stake in the success of a project, program, or portfolio, including team members, functional groups, sponsors, vendors, and customers. Expectations of all stakeholders must be carefully identified, communicated, and managed. Missing this can lead to misunderstandings, conflict, and even project failure.

Here are some tips for managing stakeholder expectations.

Assemble a team specific to project goals, ensuring team members have the right mix of skills and knowledge to deliver.
Leave sufficient time in advance of a project for key individuals to delve into and discuss issues and goals before the project begins.
Ensure the project timeline and scheduled tasks are realistic.

Project scope

During the planning phase, all project details must be solidified, including goals, deliverables, assumptions, roles, tasks, timeline, budget, resources, quality aspects, terms, and so on. The customer and key stakeholders work together to solidify and agree on the scope before the project can begin. The scope guides the project work and any changes to the scope of the project must be presented and approved as a scope change request.

Project budgets

Budgets play a large role in whether a project progresses, or if it can be completed. Few companies have an unlimited budget, so the first thing project stakeholders look at in determining whether a project succeeded or failed is the bottom line. This fact fuels the pressure project leaders, and their teams face with each passing day. As such, effective budget management is a primary area of focus for project managers who value their careers. The following are five strategies for maintaining control of your project budget before it succumbs to whopping cost overruns:

Understand stakeholder’s true needs and wants
Budget for surprises
Develop relevant KPIs
Revisit, review, re-forecast
Keep everyone informed and accountable

Project management methodologies

Most projects are conducted based on a specific methodology for ensuring project outcomes based on a range of factors. As such, choosing the right project management methodology (PMM) is a vital step for success. There are many, often overlapping approaches to managing projects, the most popular of which are waterfall, agile, hybrid, critical path method, and critical chain project management, among others. Agile, which includes subvariants such as Lean and Scrum, is increasing in popularity and is being utilized in virtually every industry. Originally adopted by software developers, agile uses short development cycles called sprints to focus on continuous improvement in developing a product or service.

PMO vs. EPMO

Successful organizations codify project management efforts under an umbrella organization, either a project management office (PMO) or an enterprise project management office (EPMO).

A PMO is an internal or external group that sets direction and maintains and ensures standards, best practices, and the status of project management across an organization. PMOs traditionally do not assume a lead role in strategic goal alignment.

An EPMO has the same responsibilities as a traditional PMO, but with an additional key high-level goal: to align all project, program, and portfolio activities with an organization’s strategic objectives. Organizations are increasingly adopting the EPMO structure, whereby, project, program, and portfolio managers are involved in strategic planning sessions right from the start to increase project success rates.

PMOs and EPMOs both help organizations apply a standard approach to shepherding projects from initiation to closure. In setting standard approaches, PMOs and EPMOs offer the following benefits:

ground rules and expectations for the project teams
a common language for project managers, functional leaders, and other stakeholders that smooths communication and ensures expectations are fully understood
higher levels of visibility and increased accountability across an entire organization
increased agility when adapting to other initiatives or changes within an organization
the ready ability to identify the status of tasks, milestones, and deliverables
relevant key performance indicators for measuring project performance

Project management roles

Depending on numerous factors such as industry, the nature and scope of the project, the project team, company, or methodology, projects may need the help of schedulers, business analysts, business intelligence analysts, functional leads, and sponsors. Here is a comparison of the three key roles within the PMO or EPMO, all are in high demand due to their leadership skill sets.

Project manager: Plays the lead role in planning, executing, monitoring, controlling, and closing of individual projects. Organizations can have one or more project managers.

Program manager: Oversees and leads a group of similar or connected projects within an organization. One or more project managers will typically report to the program manager.

Portfolio manager: This role is at the highest level of a PMO or EPMO and is responsible for overseeing the strategic alignment and direction of all projects and programs. Program managers will typically report directly to the portfolio manager.

Project management certification

Successful projects require highly skilled project managers, many with formal training or project management certifications. Some may have project management professional certifications or other certifications from the PMI or another organization. Project management certifications include:

PMP: Project Management Professional
CAPM: Certified Associate in Project Management
PgMP: Program Management Professional
PfMP:Portfolio Management Professional
CSM: Certified Scrum Master
CompTIA Project+ Certification
PRINCE2 Foundation/PRINCE2 Practitioner
CPMP: Certified Project Management Practitioner
Associate in Project Management
MPM: Master Project Manager
PPM: Professional in Project Management

Project management tools

Project management software and templates increase team productivity and effectiveness and prepare the organization for changes brought about by high-impact projects. CIO.com has compiled the ultimate project management toolkit as well as some open-source project management tools to help you plan, execute, monitor, and successfully polish off your next high-impact project.

Project management software falls into multiple categories. Some tools are categorized as project management software; others are more encompassing, such as project portfolio management (PPM) software. Some are better suited for small businesses and others for larger organizations. Project managers will also often use task management, schedule management, collaboration, workflow management, and other types of tools. These are just a few examples of the project management software and tools available to help simplify project management.

Popular project management tools include:

Asana
Changepoint
Clarizen
Planview
Mavenlink
Trello
Wrike

Project management skills

Effective project managers need more than technical know-how. The role also requires several non-technical skills, and it is these softer skills that often determine whether a project manager — and the project — will be successful. Project managers must have these seven non-technical skills: leadership, motivation, communication, organization, prioritization, problem-solving, and adaptability. It’s also beneficial to have a strategic mindset, have change management and organizational development expertise, agility, and conflict resolution capabilities, among other skills.

Project management jobs and salaries

By 2027, the demand for project managers will grow to 87.7 million, according to PMI, but these hires won’t all be project manager titles. While the more generic titles are project manager, program manager, or portfolio manager, each role may differ depending on industry and specialization. There are also coordinators, schedulers, and assistant project managers, among other roles.

Project managers have historically garnered high-paying salaries upwards of six figures, depending on the role, seniority, and location. Indeed provides a searchable list for job salaries, including some annual project management salaries companies are offering for these roles: 

Project manager: Base salary $85,311, bonus $13,500
Program manager: $85,796
Portfolio manager: $100,742
Software/IT project manager: $106,568
Project administrator: $62,093
Project planner: $69,528
Project controller: $90,342
Document controller: $74,899
Project leader: $130,689
Program/project director: $101,126
Head of program/project: $128,827

Careers, Certifications, IT Governance Frameworks, IT Leadership, IT Skills, IT Strategy, Project Management Tools

Ergonomics is often one of the most overlooked health concerns within the office. While there are OH&S regulations for lifting, moving heavy objects, and safety when working with chemicals and electricity, and there are guidelines for how long a person should be “sedentary” (i.e sitting), there are no formal governance requirements for the chairs that people use, or their computer equipment.

Sitting for long periods of time day in, day out, has been associated with repetitive strain injury, back pain, carpal tunnel syndrome, arthritis, chronic pain and metabolic syndromes (heart disease, obesity and high blood pressure). Musculoskeletal conditions costs $4.8 billion, and back pain costs $2.8 billion in Australia per year. This can be a serious cost to both businesses and the economy, and can also cause deep levels of dissatisfaction in working conditions and lifestyle.

Poor ergonomics is, by stealth, one of the greatest productivity costs in Australia, and IT has a big role to play in helping to address it.

Consider the eyes too

Staring at the wrong screen all day long can cause issues for two reasons:

It can force the head into a position that causes strain, tiredness, and potentially causes damage to the neck muscles. It can also lead to poor posture habits in the long term.A poor quality monitor can also cause eye strain.

The expectation for professionals to sit in front of screens for long periods of time – whether working from the office or remotely – does not appear to be wanning, despite the health issues being well-known. So, with the needs of professionals in mind, Samsung has worked hard to develop a business monitor range to help promote healthier working habits.

Firstly, Samsung’s entire range of business monitors feature VESA mount compatibility, and a variety of tilt, swivel, and pivot control points designed to give the user fine levels of control for just about any environment. This is important because modern wisdom suggests that people should vary how they work through the day. In recent years, standing desks have become popular, because they are proven to improve blood pressure and reduce lower back pain. At the same time, standing at a desk all day can cause new problems, such as foot pain.

So, most office workers are encouraged to alternate between sitting and standing positions throughout the day now. However, shifting between sitting and standing reorients the body and requires fine control of the monitor to help maintain a comfortable head and neck position each time. This is what the VESA mount compatibility facilitates.

Meanwhile, the business monitors have also all been given TÜV certification for intelligent eye care. TÜV Rheinland is one of the world’s leading testing service providers, and it tests displays against the ISO 9241-307 standard to ensure that they reduce annoying reflections, are designed to safeguard image quality from different perspectives, facilitate adjustable blue light content and helps to ensure displays are flicker-free.

With as many as 90 per cent of digital device users experiencing the symptoms of digital eye strain, investing in monitors that are proven to minimise the strain on the eyes is a quick pathway in ensuring that the majority of the workforce are comfortable while at work.

The best practices while using a monitor

Of course, technology can only be part of the solution, and with ergonomics, best practices really need to be built into workplace policy and education to help protect the employees. With regards to monitors and computers, employers should complement the investment in ergonomic equipment by encouraging their employees to:

Keep the monitor at a good distance. Larger monitors are actually good for this as they encourage the employee to position themselves further away to have a good view of the whole screen.Take quick and regular breaks to move away from the screen for a short time. This could be a quick coffee run or even a moment to step away from the desk and stretch out. It’s a good idea to leave the mobile behind when doing that, so that they avoid the temptation to look at a screen at all.Adopt a neutral posture. If sitting make sure to use the backrest, rather than hunch over forwards. If standing, be mindful to split the weight between both feet to distribute the weight evenly.

By looking after the ergonomics at a workplace, the organisation will enjoy better productivity and a more positive workforce. At a time where skill shortages are severe, it’s more important than ever to make sure that employees are healthy, well looked after, and happy in their jobs.

To learn more about the Samsung business monitor line, and its ergonomic benefits, click here: https://www.samsung.com/au/business/monitors/

Ergonomics, Monitors

You’ve heard it before: change is the only thing we can count on. It’s especially true in today’s volatile job market and constantly changing work landscape. With so much in flux, organizations that fail to preserve their institutional knowledge are inviting major losses in productivity and innovation.

The reality is that doing nothing to surface, preserve, and share institutional knowledge is much more expensive than building a culture of collaborative knowledge sharing that starts with the C-suite and extends to everyone at the company.

The question facing leadership today is: How can companies develop collaborative, knowledge-sharing cultures that will help them thrive in our volatile workplace landscape?

In this guide, we’ll help you answer that question by covering:

The difference between knowledge management and knowledge sharingHow organizations can address knowledge-sharing challenges by implementing best practices and embracing a culture shiftWhy it’s worth investing in a purpose-built knowledge-sharing platformWhat you can do right away to start transforming your organization’s knowledge culture and practices

Knowledge sharing matters

How does knowledge sharing differ from knowledge management? Knowledge sharing puts the employee first, not the technology.

Traditional knowledge management platforms and approaches require that organizations think about the technology first—what the content hierarchy is, what governance needs to be in place, etc. In traditional knowledge management platforms, it’s more important that the knowledge is managed than that the employee can share, discover, and reuse that knowledge.

Put people first

Knowledge-sharing platforms put the employee first by focusing on flexibility, intuitive organization, and actively bringing knowledge to the user. These platforms enable transparency and discoverability of knowledge, enabling effortless async collaboration between individuals and across teams. All of this makes the platform, and the organization, highly inclusive—an environment where everyone can contribute and benefit from day one.

Solid knowledge-sharing practices and a top-down commitment to preserving and disseminating knowledge can help organizations address challenges like:

Onboarding and retaining talent

New hires hail from different companies and programming environments, and no matter how impressive the new talent, they’ll need some time to come up to speed. Your product team may be itching to get started so they can meet their launch timelines, but your new folks are still training under more experienced team members—and taking up those experts’ time as they continue to encounter roadblocks they need help overcoming.

So much for those target launch dates.

Giving new employees access to a knowledge-sharing platform that helps them learn the ropes means they won’t have to wait for answers from more experienced colleagues before they can start delivering value. The platform will give new hires and seasoned employees alike access to common experiences, the languages and frameworks your company uses, product-specific details, and information around company processes and policies. If someone can’t find the information they need, they can ask their own questions and tag the right teams to find an answer. Because team members can easily add insights or updates to content, information stays relevant and up-to-date.

Provide a better employee experience

The right approach to knowledge sharing doesn’t just make onboarding faster and easier; it also helps you attract and retain the right people.

Expanding opportunities for learning and growth

It’s important to developers that their jobs give them plenty of chances to acquire new skills and develop existing ones. According to a Stack Overflow pulse survey, more than 50% of developers would consider leaving a job that didn’t offer sufficient learning opportunities, while about the same number would stick with a role that did offer learning opportunities. At least half of developers say learning opportunities contribute to their happiness at work.

Tech leaders, of course, want their developers to keep learning—that’s how they’ll acquire new skills, abilities, and insights that help them add more value to the organization. Once a developer is part of your team, you want them to learn continuously: to build on the skills that originally qualified them for hire while cultivating new skills.

A culture of continuous learning that encourages developers to upskill and reskill will help you retain the best employees while giving those employees every opportunity to deliver additional value to your organization.

Improving productivity and preventing knowledge loss

A central knowledge-sharing platform empowers employees to find the information they need without having to interrupt coworkers or waste time combing through chats and emails looking for a solution to a problem someone else may already have solved. Team members can post questions as they arise, and their coworkers can add updates or additional context to existing answers.

This crowdsourced model captures and preserves knowledge, but it also keeps that knowledge fresh and up-to-date by allowing users to vote on the accuracy and usefulness of others’ answers. 

Your developers can keep moving and stay agile while prioritizing knowledge sharing and preservation, and you can rest assured that employees who move on to other opportunities aren’t taking irreplaceable institutional knowledge with them.

Even short-term and temporary absences like vacation and parental leave can create headaches for developers still at their desks. “We recently had an engineer leave for an extended break during the holiday season, and Teams was instrumental in making sure we had proper coverage,” says Morgan Jones, Director of Engineering at Flex, a Stack Overflow for Teams customer. “Instead of peppering him with questions before he left, I was able to write them down and get his answers documented by him, which was really helpful for both of us.”

Accelerating innovation

When it comes to knowledge sharing, it’s crucial for teams to be able to collaborate cross-functionally in an environment where they can ask questions, hazard guesses, and share their perspectives and experiences. An employee-centric knowledge platform helps teams iterate creatively and fearlessly, and draws out a broad diversity of opinions and viewpoints from every facet of your organization.

Democratizing access to information allows every team to kick off new initiatives. Experts serve as advisors, not gatekeepers, while technical documentation and established best practices are accessible to everyone.

Create an innovative company culture that scales

Organizations that invest in systems to enable open discussion and knowledge sharing across teams are able to create an innovative company culture that scales with the business. It’s comparatively easy to create this kind of environment at a small startup—but how do you maintain that sense of rapid, transparent innovation as you scale?

Stack Overflow for Teams customer Runtastic went from a tiny team to a 250-person-strong organization spanning Salzburg, Pasching, and Vienna. With many of the core team members still around, Runtastic’s challenge was adjusting from a chaotic, ad hoc system in which everyone caught up with everyone else on a daily or as-needed basis to one where information flowed through static documentation.

David Österreicher, Runtastic’s Head of Engineering, broke down the problem: “You sit down to write a piece of documentation in a wiki, in our case Atlassian Confluence, but the person writing documentation never knows how many details to include. You then need all these smaller clarifications around it, so you ping someone on Slack, and get more context.”

That context, instead of being discoverable by the next person who needs the same information, is gone if it’s not recorded. As a result, Runtastic’s engineers were repeating themselves constantly, answering the same question over and over again. Runtastic knew they needed a knowledge-sharing platform to capture and preserve information in its full context so that future engineers could self-serve, finding the answers to their own questions.

Inaction is expensive

At this juncture, you might be wondering about the cost (or the risk) of doing nothing to implement sustainable knowledge sharing.

What do you have to lose?

One of the most critical functions of knowledge sharing is preserving institutional knowledge as people move into new departments or leave your organization. Without a system in place to capture, preserve, and maintain this information, you risk costly knowledge loss with every turnover.

Individual experts leave (or forget), and productivity and innovation suffer as those employees left behind struggle to reinvent the wheel. This becomes a vicious cycle, as your remaining developers can suffer frustration and burnout that may nudge them out the door, too.

Matt Madson, Senior Software Engineer at Intuit, explains the cost—in both productivity and morale—when developers are too beset by repeat questions and other distractions to focus. “Our support staff was expressing frustration that they couldn’t focus on their core tasks,” explains Madson, describing the pain points that led Intuit to adopt Stack Overflow for Teams. “They were getting constant interruptions in Slack, people were always pinging them with issues they considered urgent, and they didn’t have time left to actually work on addressing the underlying problem areas that these questions and issues arose from.”

“Engineers should help solve the hardest questions, the unknowns, where being familiar with how the product was built is essential,” explains Suyog Rao, Director of Engineering at Elastic, another Stack Overflow for Teams customer. “But we don’t want to keep answering solved problems over and over again. That’s where Stack Overflow really helps.”

Engineers should help solve the hardest questions, the unknowns, where being familiar with how the product was built is essential…but we don’t want to keep answering solved problems over and over again.

Suyog Rao, Director of Engineering, Elastic

Best practices for knowledge sharing

Based on our experiences, especially our work with customers like MicrosoftIntuit, and Dropbox, we’ve landed on some knowledge-sharing best practices to shape your strategy and help you choose the best knowledge platform for your organization.

Be proactive in documenting knowledge

Make it fast and seamless for employees to document knowledge without distraction or excessive context switching. Employees should be able to communicate their questions to colleagues and subject matter experts without resorting to email or chat—mediums that don’t preserve knowledge for the future or disseminate it throughout the organization so that everyone can benefit. That endless email or Slack thread is where knowledge goes to die, and you want your knowledge to be fresh, accurate, and widely accessible.

Make knowledge sharing a dynamic platform

To cultivate a company culture that prioritizes knowledge sharing and preservation, focus on making knowledge sharing a dynamic platform, rather than a destination or document library. This means that leaders and managers should:

Avoid set-it-and-forget-it documentation practicesEnsure knowledge sharing works with your developers’ preferred tools and within their existing environmentsMake knowledge searchable so that finding the information they need is fast, simple, and intuitive for developersBuild a system to surface insights that will benefit leadership, such as discovering what tech your developers are using or illuminating the most persistent roadblocks they encounter

For their Stack Overflow for Teams instance, Box used the Slack integration and created tags specific to their team and expertise. “It’s great because in our team Slack channel, we’ll see when someone posts a question. If someone is able to answer the question off the top of their head, great, they’ll go ahead and answer it,” says Aiko Krishna, Product Manager on the File System team at Box. “But if not, during our stand-ups, we’ll all look at the questions together and someone will volunteer to answer the questions. So we have a process in place now.”

Transform your culture from knowing to learning

Establishing knowledge-sharing practices is crucial, but it’s not enough.

Create a culture of learning

Knowledge sharing requires creating a collaborative culture that prioritizes knowledge sharing and preservation, evolving your company culture from one that emphasizes knowing to one focused on learning.

Often, organizations start this transformation with a business catalyst (like a hiring push) or an evangelist who leads the charge, as with Stack Overflow for Teams customer IMC.

Of course, it helps if developers already know how to use your knowledge platform and already rely on it for guidance at work. That familiarity makes them more likely to engage early and often. “When we launched our internal Stack Overflow instance at Microsoft, it took off like wildfire,” explains Laura MacLeod, a Senior Program Manager in the Developer Program at Microsoft. “When new users join, they come in, and from day one they know how to use this tool.”

On a similar note, Expensify wants programmers to feel empowered to work on any project. 

Stack Overflow for Teams has made that easier. “Everyone has a certain amount of code base that they are familiar with, but sometimes you might know about an issue much more deeply than the so-called subject matter expert,” said software engineer Ira Praharaj. “It gives an open opportunity to everyone who has the knowledge to share it, and there is no bias.”

It gives an open opportunity to everyone who has the knowledge to share it, and there is no bias.

Ira Praharaj, Software Engineer, Expensify

Invest in a purpose-built knowledge solution

You know you need a better knowledge-sharing solution. But should you task your engineers with building one from scratch or implement a purpose-built solution?

For several reasons, it makes more sense to invest in a purpose-built knowledge-sharing solution, rather than cobbling together a homegrown solution. Here’s why:

Knowledge sharing is more than documentation.

The right knowledge-sharing solution does more than simply document information. Employees need a way to access and use information that they can be confident is accurate and up-to-date. That’s why elements like crowdsourced rankings that spotlight top-voted answers and a searchable, transparent format that encourages collaboration and surfaces the best expertise are important.

DIY solutions don’t address the whole picture.

DIY solutions usually involve multiple disconnected systems that each address one or two aspects of knowledge sharing and collaboration without grappling with the problem as a whole. This approach introduces its own problems: lagging or inconsistent adoption rates, unclear or inconsistently followed processes, and ineffective knowledge capture all cause people to lose trust in the quality and relevance of your answers.

When they first realized they needed a new, more scalable approach to knowledge sharing, the Elastic team turned to the internal tools they were already familiar with. “We already use GitHub for our code,” explains Marty Messer, VP of Customer Care. “We also use it anytime that we need to escalate an issue to our dev teams from our customers. We figured we would try using that, because that’s where our engineers spend their days.” The support team began to put questions and answers into a GitHub repo created specifically to store this kind of knowledge. 

Unfortunately, that solution made it difficult to search for answers later on, and there was no way to identify the best answer if multiple people had contributed ideas for possible solutions.

This experience showed Elastic that they needed a searchable knowledge-sharing platform that prioritized knowledge quality and automatically directed users to the most valuable, relevant answers.

What can you do now?

Like any foundational shift in culture, fostering an environment of continual learning and knowledge sharing takes time. But you can set things in motion now.

Here are some tactics to get your knowledge-sharing solution off the ground:

Start with leadership.

For your whole company to embrace knowledge sharing, leadership needs to model the importance of capturing, preserving, and sharing knowledge. Leadership can share their knowledge with employees through fireside chats and AMAs (ask me anything) to signal the importance of this culture shift. Encourage managers to do the same with their teams.

Create spaces and occasions for learning.

Create spaces for internal thought leaders to share their experience and expertise, whether through content on your knowledge platform or events like lunch-and-learns.

Identify and dismantle roadblocks.

As your knowledge-sharing practices coalesce, you’ll be able to identify the points of friction that tend to block progress and stall momentum. In overhauling your knowledge practices, start by eliminating barriers that keep teams from working together effectively.

Have fun with it.

Embrace elements of gamification like upvotes and awards or badges that recognize excellent solutions and valuable questions. Gamification encourages engagement and stokes good-natured competition, which further drives engagement.

Work with what you’ve got.

If your knowledge-sharing platform doesn’t integrate effortlessly with the tools and resources your developers are already using, employees will be much less likely to engage with those platforms. And for knowledge sharing to work properly, engagement needs to be high.

Select a purpose-built platform that facilitates and promotes knowledge sharing.

Choosing a platform your developers already know, use, and rely on increases adoption speed, encourages high engagement rates, and reduces friction for users.

Doctolib developers wanted to create a place for internal thought leaders to share their expertise and for teams to discuss new technology trends. In their Stack Overflow for Teams instance, developers began sharing bite-sized knowledge under tags like “hot tips.” They engaged in friendly competition to see whose contributions would receive the most votes and comments.

As an engineer, you work towards targets, but you also work for recognition from your co-workers. This tool helps me get both.

Fábio Guerreiro, Full-stack Engineer, Doctolib

Fábio Guerreiro, a full-stack engineer at Doctolib, said this approach to knowledge sharing made him a contributor from day one. “On the public Stack Overflow [site], I was just a reader, but on Doctolib’s instance, I began writing questions and answers right as I started.” Gamification works for Guerreiro and his colleagues. He admits, “Personally, what I would miss with a different solution is the points, achievements, and medals. As an engineer, you work towards targets, but you also work for recognition from your co-workers. This tool helps me get both.”

Plan for change

Ironically, change is one of the few factors that developers, managers, and company leadership can count on. Capturing and preserving invaluable institutional knowledge helps companies manage rapid, unpredictable change without sacrificing productivity, innovation, or developer happiness. Building a collaborative, cross-functional culture that values learning and prioritizes knowledge sharing is a necessity.

See how other businesses use knowledge-sharing

See how organizations around the globe use Stack Overflow for Teams to help break down silos, foster collaboration, and build a knowledge-sharing culture. Read the case studies.

IT Leadership

Developing and deploying artificial intelligence (AI) solutions efficiently and successfully in businesses requires a new set of skills, for both individuals and organizations.  In a recent study, over half of companies that have successfully deployed AI applications have embraced an enterprise-wide strategy that is inclusive, open, and pragmatic, using homegrown AI models 90% of the time. They have spent time understanding and documenting consistent and effective ways of rolling out projects and processes to drive efficiency. 

AI is Booming. Wanted: More People & Best Practices.

AI in business is advancing at a brisk pace. The market is forecast to grow at a Compound Annual Growth Rate (CAGR) of 36.2% between 2022 and 2027, when it will reach $407 billion, according to a recent study by MarketsandMarkets. But the report cautioned that: “The limited number of AI technology experts is the key restraint to the market.” The same lack of enough skilled personnel, along with established processes for deploying AI, was also cited in a recent global study of 2000 businesses by IDC.

Thirty-one percent of companies surveyed were actively using AI while the others were still in prototyping, experimentation, or evaluation stages. Significantly, companies using AI – considered early adopters – have integrated their AI platforms with the rest of their data center and cloud environments instead of running AI in silos used by separate groups. They have defined holistic, organization-wide AI strategies or visions along with clearly defined policies, guidelines, and processes. 

Another characteristic of these early AI adopters is that they use internal staff instead of external vendors to deploy AI applications. They also prioritize training line of business managers to use outcomes from algorithms and to tap these stakeholders to help guide new projects. This connection between IT and business leaders results in a high degree of support from C-level executives on down. 

AI Environments are Complex

To provide the massive compute power and data storage resources required for AI applications, businesses typically use systems with graphical processing units (GPUs) that accelerate applications running on the CPU by offloading some of the compute-intensive and time-consuming portions of the code. High-speed storage, parallel processing, in-memory computing, and containerized applications running in clusters are other techniques that are part of AI solution environments. 

Working with such complex technology requires the right training and experience. According to Datamation, there are 55,000 jobs currently listed under “artificial intelligence” on LinkedIn. Many if not most of these jobs (e.g., AI engineer, data scientist, AI/ML architect, AIOps/MLOps engineer) require years of education and advanced degrees. Yet the IDC study makes clear how much more effective AI projects are with these personnel designing models and collaborating with stakeholders in-house.

Scaling an AI Environment for Critical Healthcare Diagnoses

A leading pathology diagnostics firm in the U.S., that works with top biopharmaceutical and medical organizations around the world, has developed its own best practices for designing and deploying AI applications. Project teams at the firm include IT professionals, machine learning engineers, and data scientists who specialize in the biomedical industry.  Line of business managers also help guide the development of algorithms, 90% of which are developed based on the use of inhouse models. 

Many team members work primarily alone, then collaborate to deliver complex projects. With fluid, continually evolving project requirements, the company uses the Agile software development process that anticipates the need for flexibility in a finished product. To ensure that the technology they use (including GPU-based compute with high-speed and object-based storage and file-based access to Kubernetes clusters) is kept up-to-date and future proofed, the firm relies on close partnerships with vendors to review product roadmaps and anticipate and incorporate new features.

Agile development requires a pragmatic approach. IT managers at the firm insist that developers evaluate their work critically in the design phase and be willing to start from scratch if an approach isn’t working. In IDC’s survey, the companies actively using AI take an average of three months to build machine learning and deep learning models where AI laggards commit a fraction of that time. Deployment in AI early adopter companies like the pathology diagnostics firm, however, is accelerated because developers have already done their homework and obtained buy-in on models and validation from data scientists on technology purchases. 

Summary of Best Practices for Effective Use of AI 

As more C-level and line of business executives recognize and prioritize the use of AI as an effective tool to enhance competitiveness and drive efficiencies, the barriers to adoption have also become clear. Companies achieving success with AI have invested in people with skills and expertise. They have established vendor partnerships to future-proof solutions by staying up-to-date on evolving product roadmaps. They have fostered collaborative and highly flexible development environments that can alter course based on changing business dynamics. Using mostly homegrown models, they are committed to taking the time required to get the design of algorithms right before moving to well-defined established deployment processes.  Finally, AI development teams mentor business stakeholders, working with them to uncover and apply actionable insights from data analytics. 

Download the new IDC report to learn more about what is separating AI leaders and laggards. 

***

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Artificial Intelligence

Managing risk is one of the top responsibilities of any leadership team. But leaders can manage only the risks they know about. Effective leadership, it turns out, depends on risk reporting. Reporting risks to your company’s executive team and board of directors will help your organization make the right decisions about reducing risks. 

This article focuses on the reporting of risk itself. That means finding the right information to share with your company’s leadership team and sharing it so it can be acted on effectively. 

Reporting risks that matter to a company’s leadership

Risk means a lot of things to a lot of different people. If you talk to IT people about risks, you’ll hear about the risk of server outages or data breaches or software vulnerabilities that could lead to data breaches. 

You might also hear about unauthorized devices, bring-your-own-device (BYOD) policies, and how difficult it is to monitor what employees are doing with the company’s data on their home networks now that they’re working remotely.

All those things, from server outages to remote employees, represent risks of one form or another. But if you’re in charge of reporting risk to your company’s executive team and the board, do you really want to give them a list of unpatched systems or an estimate of how many employees are using BYOD devices? 

What risks does your company’s leadership team ultimately care about?

To answer that, let’s ask about risk itself. Fortunately, there’s a generally agreed-upon definition of risk, at least among IT professionals. ISO 31000, the International Standards Organization’s guidelines for risk management, defines risk as “the effect of uncertainty on objectives.” 

“Uncertainty” seems straightforward enough. If something is certain, there’s no risk involved. If we know absolutely that our servers will never crash, there’s no risk of them crashing.

But what about “objectives?” Every employee, team, department, and business has objectives. When reporting risk to the executive team and the board, you need to ask yourself which objectives they care about. It’s not that they’re indifferent to the goals of individual teams and projects. Rather, it is the job of a company’s leadership to focus on the big picture. 

Here are three objectives you can be sure your company’s leaders care about:

Data confidentiality, integrity, and availabilityBusiness continuityRegulatory compliance 

There may be other objectives, such as a certain percentage of revenue growth or a good reputation in the marketplace. But you can be sure that your company’s leadership cares about managing and protecting its important data, avoiding IT outages that bring business to a halt, and ensuring that the company never makes headlines about regulatory fines.

Each of these objectives will likely require detailed reporting to support the objective’s overall risk assessment. For example, the data the board cares about encompasses everything from customer data to employee data to financial records to intellectual capital such as product designs and patents. All those need to be managed and secured. 

Different types of data may be facing different types of risks of varying severity. The board will need to know how much this objective is at risk overall, as well as what specific types of data might require new investments in security or personnel training. 

Before you prepare a report about risk in your organization, make sure you understand your leadership team’s objectives. Some of those might be posted on your company’s website. Others might be listed in an internal, long-term strategic plan. One way or another, you need to know what those objectives are because you’re going to use them to frame your discussion of risk.

Your risk report should provide the leadership team with the information they need to make smart decisions about which actions to take to mitigate risks related to the company’s strategic objectives.

Identifying risks helps you think like an attacker

There’s an added benefit to framing your risk reports this way. When you’ve identified risks to your data and to the company’s business continuity, you’ve also identified the weak points that criminal syndicates and hostile nation-states might attack.

After all, when a cybercriminal tries to break into your company’s IT systems, what are they doing? Most likely they’re trying to get to your data to steal it or leak it, or trying to get to the systems that process your data and disrupt them, possibly through ransomware or some other form of attack.

Because you’re now measuring and reporting risk based on strategic objectives, you have a detailed, weighted report on the weakness and vulnerabilities related to your data and the systems that store, process, and present your data. You know what’s most likely to be targeted and how to go about protecting them, based on your detailed knowledge of vulnerabilities and probabilities.

All this supporting information makes the risk assessment you’re presenting to the board much more credible and useful. The board sees how data and business continuity are at risk, what controls are in place to mitigate those risks, and how those controls could be improved or broadened to reduce risks further in keeping with the company’s overall strategy.

Risk reporting is an ongoing practice

Risk reporting should be an ongoing practice. Risks are continually changing, whether they’re arising from new business initiatives or new types of cyber threats. Automating data collection and risk assessment helps provide your company’s leadership team with the vital information they need to make the right decisions to mitigate risk and advance the company’s objectives.

Not sure about your risk levels? Get your risk report here.

Risk Management

The role of the CMO is more invested in technology than ever, and CMOs have no choice but to engage with the CIO and align business and tech objectives. Key to the success between CMO and CIO is how both roles can collaborate around data.

Related reading: How the CMO can leverage the data of retail networks to deliver better outcomes for their organisations.

On the surface, there is a perceived tension between CMOs, CIOs, the rest of the executive team, and data. CMOs need to look for ways to leverage customer data to deliver superior and highly tailored experiences to customers. CIOs need to ensure that the business’ use of data is compliant, secure, and done according to best practices. They need to assure the board that the risk from data is minimised.

“Understanding that global data policies and regulation are ever-evolving, CIOs must plan around regulation in effect today, and also what could be adopted in the future,” Melanie Hoptman, Chief Operating Officer, APAC, at LiveRamp said. “By taking a forward-thinking approach to privacy and security, CIOs will set a sustainable and durable foundation for data ethics practices at their organization.”

In Europe, for example – often considered the leader in global trends when it comes to compliance law – the GDPR alone costs more than $US1 million to be in full compliance, on average, and in terms of penalties, companies were fined more than €1 billion in 2021 alone.

However, as data enablement platform, LiveRamp, has noted, CIOs are well across these requirements, and are now increasingly in a position where they can start to focus on enablement for people like the CMO. “The good news for many CIOs is that they’ve already laid the groundwork through investments in data governance and migration to the cloud,” LiveRamp noted in a recent report.

“While the passage and enforcement of GDPR, CCPA in California, and other data regulations may have once been seen as seismic events affecting brands and publishers alike, they’ve actually been a forcing function for companies to organize their data, remove data silos, and clearly document what they have access to and how it can be used.”

Gaining Executive Buy-In

Successfully capitalising on the data opportunity requires a whole-of-business approach. However, LiveRamp notes that there are three particular executives that CIOs and CMOs should collaborate most closely with so they can drive buy-in across the organisation.

CEO & CFO – “Bring your stakeholders along your journey, proving your strategy’s value by being transparent on the metrics you’re tracking and how you’re faring. In doing this, you’ll soon find partners within the organization who are willing to lean in and help.”Chief Data Ethics Officer or General Counsel – “Working directly with these executives will also give you a sense of the types of leading-edge technologies that they are willing to explore.”Chief Analytics Officer – “The right technical data management tools can reduce that time significantly for marketing, data, and analytics teams, accelerating insights that can spark innovation.”

The goal – at least in the initial instance – will be to reduce the siloing effect across organisations. As noted on Tech Target, data silos create a number of headaches for organisations and often make maintaining compliance more difficult:

Incomplete data sets, which hinder efforts to build data warehouses and data lakes for business intelligence and analytics applications.

Inconsistent data, which can result in inaccuracies in interacting with customers, and affect the internal operational use of data.

Less collaboration, when different teams have access to different data sets, the opportunities to work together and share data between departments is reduced.

Data security, the decentralised nature of where data is stored when it is siloed can expose the organisation to increased security and privacy risks.

In this context, there is a natural alignment across the organisation to address the challenges of siloing. The CMO wants to free the data up for better collaboration and customer interactions, while recognising the need for the CIO and others to ensure the organisation adheres to best practices for the increasingly strict compliance environment.

However, the challenge is that one line of business will not always want data accessible to another line of business – and indeed that in itself can become a compliance risk. Marketing should not have access to elements of the finance team’s data, for example. The CIO should work with their counterparts like the CMO and others to ensure teams have access only to the data necessary to drive their specific business outcomes     .

“Businesses must think of the CIO and CMO as equal champions whose partnership makes innovation possible,” Hoptman said. “When the CIO unites siloed customer service data with CRM data, marketers can create new opportunities for upsells, data monetization and better personalization, or leverage even purchase data to send targeted offers to customers in-store or at the register. Either use case shifts the perception of marketing from cost-center to revenue-driver, while increasing ROI for tech investments. This is a win-win for CIOs and CMOs.” 

Rather than allow that to undermine efforts to embrace cross-business collaboration and de-siloing, LiveRamp instead recommends privacy-enhancing technologies (PETs). “PETs represent an ever-growing group of cryptographic and encryption protocols—math, basically—that offer businesses the ability to accelerate safe data collaboration, build customer intelligence, and maximize the value of data without relinquishing control or compromising consumer privacy,” Hoptman said.

The LiveRamp platform provides that to organisations, giving them the ability to collect first-party data as a single source, leverage third-party data in conjunction with first- and second-party data securely, and collaborate both internally and externally by building secure data partnerships with sources (silos) that would have been otherwise inaccessible.

In delivering this capability to their organizations, CIOs can position themselves at the centre of enablement, giving CMOs access to the critical data that they need for marketing efforts, and articulating the value of doing so to more risk-averse executives, all while maintaining data best practices.

“With additional data regulation undoubtedly in our future, customer intelligence will only become more challenging, increasing the need for enterprises to unite their internal data and build the infrastructure to support safe, secure collaboration with trusted external partners,” Hopman said. “The CIOs who plan for this future now will be the ones poised to reap greater returns on their current investments.”

Read the full report here.

Data Management

The nonsense was tucked away in a PowerPoint slide, as so much nonsense is. “We’ll help you institute best practices, followed by a program of continuous improvement,” the offending bullet said.

Now, I’m willing to shrug at a bit of harmless puffery from time to time. And maybe this puffery was harmless. But I don’t think so.

As my pappy used to say, ‘If someone sells this and someone else buys it, they have something in common: They’re both schmucks.’ Even ignoring the two-schmucks-in-a-pond aspect of the situation, the whole premise of “best practices” isn’t just flawed, it’s fraud — that should be avoided at all costs. It’s a phrase that pretends to provide value when it’s really inserting nothing but noise into the signal.

The idea of “best practices” is deeply wrong for these reasons: (1) It’s argument by assertion, not evidence and logic; (2) “best” is contextual, not absolute; and (3) it encourages stasis by precluding innovation.

Argument by assertion

When you read or are told a particular way of doing things is best practice, do you ask what the criteria are for awarding it best-practice status? Or, for that matter, who the governing body is that’s authorized to give out the award?

In the rare cases where there is a governing body — ITIL is an example — best practices aren’t what they offer. What governing bodies more often provide are “frameworks,” which are lists of practices, not actual how-to assistance.

If you have asked, you’ve probably discovered that there is no such group. What there is in its place is self-proclaimed authority. Here’s how that works out:

Imagine the situation at hand isn’t about running IT or a business — it’s about curing intense abdominal agony, for which surgically removing the vermiform appendix is, you’re told while lying in your bed of pain, best practice. An industry consultant tells you so, buttressing their argument by laying out three case studies in which appendix removal successfully eliminated the abdominal distress. It’s best practice!

Except it isn’t, because, sadly, they lost a few patients along the way. There are, as it turns out, lots of different types of intense abdominal pain, most of which aren’t appendix-related. Somehow or other these weren’t written up as case studies.

Best is contextual

As has been pointed out in this space before, processes and practices have six dimensions of possible optimization, and because they trade off you can only optimize no more than three of them.

For any given practice, different organizations need to optimize different combinations of these dimensions. A process or practice whose optimization goals are, for example, cycle time and quality will be designed quite differently from one designed to optimize for unit cost and excellence.

Which makes designing any one process or practice that’s best in all situations no more possible than designing any one anything else that’s best in all situations.

Stasis over innovation

Call me Captain Literal, but “best”? Really?

Look, if we’re supposed to take someone at their word, their word should mean what it’s supposed to mean. So a best practice should be, by definition, a practice that can’t be improved on.

As a leader and as a manager, the last thing you ought to be doing is encouraging the attitude that the way you do things, or the way you’re going to do things once you’ve installed a new practice, is that there’s no place for innovative thinking.

But that’s what the phrase tells them.

So don’t use it.

Where do you go from here?

When you decide you need to improve your organization’s practices, starting from scratch doesn’t make sense either. Surely there must be a way to learn from the experience of other organizations.

There surely is, and it’s probably obvious to you if you’ve read this far.

If you’re on the proposing side of such things, banish the phrase “best practice” from your vocabulary. When you’re tempted to use it, describe the practice you’re proposing as a “proven practice” or “well-tested practice” instead, assuming you and your teams have enough experience to justify the claim.

If you’re on the buying side of the equation and someone uses it as part of their attempt to persuade you to embrace their way of doing things, stick your fingers in your ears and sing, La la la la la! I can’t hear you! La la la la la!

It is, after all, just noise.

If you’re looking for a better way of doing things, and like the practice in question as described and are explaining why you’ve chosen to implement it, go beyond banishing the phrase.

Replace it with this dictum: There’s no such thing as best practices, only practices that fit best.

And make sure you’ve evaluated the practice in question so you’re confident it does fit your organization best.

Is that best practice for practice improvement?

Probably not.

But it’s a pretty good one.

IT Leadership, IT Strategy

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

A substantial shift has happened in the enterprise storage industry over the last 12 months that has changed the dialogue about storage. In past years, the first conversations with enterprise storage buyers were about cost efficiency and performance. However, today, the two most important things that come up first in storage conversations are cybersecurity and delivery time. This is a radical change that is redefining strategic planning and purchasing of enterprise storage solutions.

Storage has become part of a bigger conversation that an increasing number of decision-makers in enterprises are recognizing. It’s as if customers are waking up to a new reality – a new normal – that storage needs to be a core component of an enterprise’s corporate cybersecurity strategy, and lead times for delivery of products are longer or, at a minimum, vary by vendor.

One vendor may provide products in weeks, while another vendor will need to take many months to deliver complementary products for an end-to-end solution. Because of this, enterprise buyers and IT solution providers, who provide solutions to enterprise buyers, need to think differently.

In the past, customers and prospective customers who were interested in buying storage solutions were quick to talk about capacity, speed, IOPS, workloads, and application profiles. Storage cybersecurity would not even be discussed until the eighth conversation or later. Yet, in 2022, the first three conversations are laser-focused on cybersecurity and how storage is a critical element of an overall corporate cybersecurity strategy.

The realization that primary and secondary storage are integral to a strong enterprise cyber security posture, including immutable snapshots, fast recovery, fenced-in forensic environments, and more, casts a wide net for the one thing that keeps C-level executives and IT leaders up at night – cyber resilience (or, rather, the lack of it).

If an enterprise does not have the proper level of cyber resilience built into its storage and data infrastructure, there is a huge gap. This is why, on average, it takes an organization nearly 300 days to figure out if they have even been infiltrated by a cybercriminal.

In the work that Infinidat has done to help large enterprises increase their cyber resilience, we have learned what it takes to bring storage and cybersecurity together for an end-to-end approach.

Of course, consolidation and its dramatic impact on capital and operational expense structures are still part of these conversations in the storage market, too. As enterprises upgrade to improve their cybersecurity, they are also using the opportunity to consolidate from a high number of arrays to Infinidat’s petabyte-scale arrays.

Instead of having 50 arrays that have been built up over time, they can consolidate and use a few Infinidat arrays, while getting greater capacity, better availability, unmatched real-world application performance, and higher storage cybersecurity. Consolidation is also a major factor in advancing green IT efforts – less use of power, cooling, floor space, and resources.

Partners need to talk about storage cyber resilience and consolidation with customers, hand-in- hand. But they also need to tackle the other big conversation-starter glaring at all of us in the face – namely, the supply chain challenge that is affecting delivery times.

Customers and partners must embrace the mindset that strategic planning needs to be done earlier, and decisions will need to be made quicker. My message to customers and partners – for their own benefit – is this: talk to their suppliers earlier than they previously have.

Infinidat customers have been benefitting with us. Infinidat has been doing a superb job managing the supply chain and being able to deliver storage solutions faster than suppliers of other types of IT products, such as servers or switches.

But since the supply chain crunch has its ups and downs for all companies (as no vendor is totally immune to vicissitudes), it is smart to talk to us and your other suppliers earlier, so you will not get hit head-on with a supply chain issue.

While Infinidat is able to deliver in a matter of weeks, a server vendor may be saying it will be nine months before the new servers will arrive. The storage platforms cannot be utilized until the servers are installed. So, this is where a partner can step up and find practical solutions to get servers from another source in, for example, a third of the time.

Customers should be working closely with their partners and suppliers to be creative about how to speed up delivery timelines. It may sound like very hard work, but it will actually help prevent bigger problems down the road. There are customers ordering products now, but those products won’t arrive until Q4. They are thinking ahead. They are accelerating decisions as they map out and fulfill their strategic plans.

The functioning of their business depends on these technical and business decisions. You don’t want to have to face an irate CEO who wants to know why you can’t get IT products that are necessary to support the next phase of the company’s digital transformation initiative or elevation of DevOps or help them thwart malware and ransomware threats.

You don’t want to have to explain to the Board of Directors why the data infrastructure could not scale. You don’t want to have to face fines from a government for failure to ensure cyber resilience, leading to the exposure of sensitive data.

Don’t get caught digitally flat-footed.

To learn more, visit Infinidat.

Data Management, Master Data Management