It’s no secret that technology has forever changed the way we approach and do work. However, while budgets and headcount on technology teams continue to rise, technology leaders still have a hard time finding engineering talent with the right balance of skills.
Prior to COVID-19, businesses were already thinking about transformation initiatives that would help them transition from legacy systems to allow technical teams to work in more flexible, efficient, and secure environments. Post COVID-19, these attributes are more important than ever. However, just like with any transformation initiative, these transitions require hard skills, which are in high demand but short supply.
In fact, leaders report that Cyber Security is the number one skill shortage and top investment priority, made increasingly urgent due to moving to a fully remote workforce, which has increased the likelihood of malware and phishing attacks.
From becoming cloud-native to defending against cybersecurity attacks and breaches — organizations need a wider range of engineering skills on their teams than ever before. In order to solve skill gaps and talent shortages, businesses need to consider upskilling their existing engineers on must-have skills, such as cybersecurity and rethink engineering talent acquisition and onboarding strategies to ensure they get the right balance of skills and knowledge on their teams.
Two Refreshed Programs Help to Upskill Your Engineers
Over the last ten years, we’ve been helping organizations, such as Disney and Humana, acquire and build the engineering talent they need to compete in today’s digital economy. Through deep customer, industry, and market research, we’ve updated two programs to help more organizations meet their engineering talent goals.
Get a sneak peek of what those programs entail below:
Java Developer Immersive: Expand your Java development workforce with experiential training in the most in-demand skills. Participants will build core skills in Java, Spring Boot, test-driven development, troubleshooting dev ops, cloud, and agile development. Use this program to reskill junior engineers or onboard fresh computer science graduates to your teams.
Cybersecurity Accelerator: Bulk up your cybersecurity practices by training existing developers on best practices. Participants will learn how to add security features to their web applications to minimize the chances of an attack. Use this program to upskill existing engineers to increase cybersecurity skills and knowledge within your engineering team.
These refreshed programs allow you and your team to:
Access Transformative Tech Skills: Level up your engineering team by embedding must-have cybersecurity and java development skills.
Learn From Real Industry Experts: Give your people practical, hands-on training created and taught by leading subject matter experts.
Build and Develop Engineering Talent: Invest in existing and new talent by offering them learning opportunities that move your business forward.
As Always, More to Come
We’re working on more exciting things that we’ll be releasing over the next few months, such as useful workforce insights and updated skilling solutions. Keep your eyes on the GA blog or get in touch with us to hear the latest.
Want to learn more about how we can help your organization build essential engineering skills? Download the full catalog of GA’s tech skilling solutions here.
For years, the importance of data has been echoed in boardroom discussions and listed on company roadmaps. Now, with 99% of businesses reporting active investment in big data and AI, it’s clear that all businesses are beginning to recognize the power of data to transform our world of work.
While all leaders recognize the needs and benefits of becoming data-driven, only 24% have successfully created a data-driven organization. That is because transformation is not considered holistically and instead leaders focus on business, tools and technology and talent in silos. Usually leaving skill acquisition amongst leaders and the broader organization for last. It’s no wonder that 67% of leaders say they are not comfortable accessing or using data.
We’ve worked with businesses, such as Bloomberg, to help them gain the skills they need to successfully leverage data within their organizations & we haven’t left leaders out of the conversation. In fact, we know that leaders are crucial to the success of data transformation efforts & just like their teams, they need to be equipped with the skills to understand and communicate with data.
Why Should I Train My Leaders on Data?
When embarking on a data transformation, we always recommend that leaders be trained as the first step in company-wide skill acquisition. We recommend this approach for a few reasons:
Leaders Need to Understand Their Role in Data Transformation: Analytics can’t be something data team members do in a silo. They need to be fully incorporated into the business, rather than an afterthought. However, businesses will struggle to make that change if every leader does not understand his or her responsibility in data transformation.
Leadership Training Shows a Commitment to Change: According to New Vantage Partners, 92% of data transformation failures are attributed to the inability of leaders to form a data-driven culture. In order for your employees to truly become data-driven, they have to be able to see a real commitment from leaders to organizational goals and operational change. Training your leaders first sends that message that data is here to stay.
Leaders Need to Be Prepared to Work With Data-Driven Teams: Increasingly, leaders are expected to make data-driven decisions that impact the success of the organization. Without literacy, leaders will continue to feel uncomfortable communicating with and using data to make decisions. This discomfort will trickle down to employees and real change will never be felt.
Just like your broader organization, leaders cannot be expected to understand the role they play or the importance of data transformation without proper training.
What Does Data Literacy For Leaders Look Like?
Leaders need to be able to readily identify opportunities to use data effectively. In order to get there leaders need to:
Build a Data-Driven Mindset:
While every leader brings a wealth of experience to your org, many leaders are not data natives, and it can be a big leap to make this shift in thinking. Training leaders all at once gives you the opportunity to get your leaders on the same page and build a shared understanding and vocabulary.
So what does building a data-driven mindset look like in practice? To truly have a data-driven mindset leaders must be aware of the data landscape, as well as the opportunity of data, be mindful of biases inherent in data with an eye towards overcoming that bias, as well as being curious about how data can influence our decisions.
Leaders should walk away from training with a baseline understanding of key data concepts, a shared vocabulary, knowing how data flows through an organization and be able to pinpoint where data can have an impact in the org.
Understand the Data Life Cycle
Leaders are responsible for having oversight of every phase of the data life cycle and must be able to help teams weed out bias at any point. Without this foundation, leaders will have a hard time knowing where to invest in a data transformation and how to lead projects and teams.
All leaders should be equipped to think about and ask questions about each phase of the life cycle. For example:
Data Identification: What data do we have, and what form is it in?
Data Generation: Where will the data come from and how reliable is the source?
Data Acquisition: How will the data get from the source to us?
It is not the role of the leader to know where all the data comes from or what gaps exist, but being able to understand what questions to ask, is important to acquire the necessary insights to inform a sound business strategy.
Get to Know the Role of Data Within the Org
In an organization that’s undergoing a data transformation, there’s no shortage of projects that could command a leader’s attention and investment. Leaders must be equipped to understand where to invest to put their plans into action.
Based on existing structure, leaders need to understand the key data roles, such as data analysts or machine learning engineers, why they are important and how they differ. Once a leader has the knowledge of the data teams, they will be able to identify the opportunity of data within their team and role.
Make Better Data-Driven Decisions
Leaders who rely on intuition alone run the huge risk of being left behind by competitors that use data-driven insights. With more and more companies adjusting to this new world order, it’s imperative that leaders become more data literate in order to make important business-sustaining decisions moving forward.
Leaders should walk away from training with a baseline understanding of key data concepts, a shared vocabulary, knowing how data flows through an organization and be able to pinpoint where data can have an impact in the org.
Getting Started With Leadership Training
Including data training specifically for your leaders in your data transformation efforts is crucial. While leaders are busy tackling other important business initiatives, they, just like the rest of your organization must be set up with the right skills to successfully meet the future of work. Investment in data skills for leaders will help you to forge a truly data-driven culture and business.
Businesses have shifted from traditional ways of operating to truly becoming customer-centric digital organizations — and the global pandemic has accelerated this inevitable shift. Product managers, who sit at the nexus of customer needs, business strategy, and technology, play a critical part in building their companies’ digital fluency so organizations can evolve and transform their products to meet market and customer demands.
That said, product management is often ill-defined as a function, especially in traditional companies, and business leaders and managers have a responsibility to precisely understand product management skills and careers to help these nascent leaders succeed and unlock their full potential.
By developing and integrating product managers as strategic thinkers who help evolve organizations into being customer-centric, leaders and managers can tap into many benefits:
Improved leadership pipeline and succession planning: Product managers are responsible for many things, but skills development strategies to level-up their subject matter expertise into leadership roles are not often clear. By connecting product management skills to a long-term and articulated career path, you can improve your leadership pipeline and increase career satisfaction for your product managers.
Clear hiring objectives: Evaluating candidates against a documented set of skills can decrease bias and help recruiters make vital distinctions between hiring project managers, product managers, and product owners.
Increased product management talent pipeline: Creating consistency around what early-career professionals understand a product manager to be and what they must learn creates access to product management careers for people who don’t already have product managers in their networks.
We formed the Product Management Standards Board with a wide-ranging set of product management leaders across the consumer goods, technology, finance, and education sectors. We’ll channel our collective experience into increasing clarity of and access to product management skills and careers so that the next generation of product management talent can maximize their impact in organizations and the world.
We’ve crafted a career framework as a valuable tool for:
Product leaders who want to build capable, well-balanced teams.
Aspiring product managers who want to understand what skills they need to enter the field and help lead organizations.
Mid-career professionals who wish to understand their career options.
HR leaders who want to build transparent, consistent career pathways.
What Defines an Excellent Product Manager?
We drafted a career map that captures our collective thinking about what makes a product manager and the career paths and associated skills required for an employee to one day become a product leader.
Let’s break down each section of the framework and see how they’re used to guide career progression.
Associate Product Manager
To begin a career in product management, individuals often move into associate product management roles from within or outside an organization with some existing understanding of the business, product, and/or customer base. While we firmly believe anyone can become a product manager starting at the associate level, we commonly see analysts, software engineers, designers, project managers, or product marketers moving into this role. In this stage of career development, product managers learn to use data to make decisions, influence without authority, and understand the balancing act of prioritization.
Product managers learn a mix of skills based on their particular product, area of responsibility, and expertise. Product managers in charge of a new product or feature may heavily focus on research and development. In contrast, product managers responsible for improving the quality and efficacy of an existing product or feature may focus more on data analysis to understand what drives an improved experience.
Squad leadership is critical to ensuring all people understand the goal they are working towards and what success will look like.Product managers at a large organization have the opportunity to either specialize in a single domain or can work with their managers to rotate ownership over product areas to develop a breadth of experience and skills.
Product managers at a startup will likely get to experience all of these skills in rapid rotation as their teams iterate quickly to identify product-market-fit and the right set of features for their product.
Senior Product Manager
The senior product manager level is where product managers start differentiating between becoming “craftmasters” in the individual contributor path or people managers on the leadership path. While craftmasters still need to provide inspiring team leadership to those working on the product, they often become particularly versed in a product domain, like product growth and analytics.
In contrast, a people manager in this role largely focuses on team management skills. Either way, this role is a critical step in someone’s career as it allows them an opportunity to practice developing and sharing a vision for a product with their team and working with more moving parts to guide people towards that vision. Understanding and prioritizing these moving parts become a key skill to develop at this level.
Additionally, the responsibilities to make decisions related to product growth also increase here. This level is a product manager’s opportunity to demonstrate an understanding of how business, market, and product intersect to inform the direction of the product and distinctly articulate how they expect that product to impact the company’s financials.
Director of Product
At this career point, directors of product are making a critical transition from manager to leader. They have to bring the threads of the product strategy and the product roadmap together and take ownership and responsibility for their decisions and impact. The Director of Product also starts to gain ownership of the cost side of their decisions – at some companies, this can extend as far as P&L ownership for project and product costs. They move into managing a portfolio of products and connecting the dots between how they work collectively for users and guide teams to work through complex problems to develop goals on a longer, future-driven timeline.
VP or Head of Product
Once an individual reaches this leadership level, they have mastered the key functional skills of product. They are now the pivotal connection point between the rest of the company’s leadership plans and the product team. They have to get beyond “product speak” and help connect the dots between technology, customers, and business goals with other leaders and employees across the business. There is a fair amount of time spent aligning resources and plans with other leaders to drive the strategy forward. As product leaders, they are also driving innovative thinking and are responsible for either the entirety of the product or a significant portfolio in terms of the company’s financials.
A Few Notes
We’ve had many rich discussions while building out the career map and teased out some nuances listed below that may come to mind as you work your way through this framework.
What about a product owner?
While product owners play a critical function, we do not see this as being a distinct job title for someone. If you’re curious about the distinction and who might play a product ownership function in your teams, read Product Dave on Medium.
What about the difference between startups and large organizations and everything in-between?
Product leaders at a large organization should consider rotating their product managers between a few different areas before moving them into more senior roles to build a range of skills sustainably. Product managers at a startup will likely get to experience all of these skills in rapid succession as their teams iterate quickly to identify product-market-fit and the right set of features for their product.
Does the framework change for “craftmaster” vs. “leadership” paths?
We have focused this framework more on the leadership path, but there is a continued path as an individual contributor, especially within larger organizations. Senior product managers, principals, and distinguished product management roles often see product managers tackle increasingly complex problems and mentor their colleagues on critical product skills while remaining in the “craftmaster” path.
Where do tangential functions fit in?
Some roles work closely with product managers to enable the full execution of products, but they are excluded on this map as they are adjacent to a product manager career path. A few of these functions include pricing analysts, product marketers, and product operations.
What happens after VP of Product?
The next step after VP of Product is very dependent on the organization. Some VPs of Product already report to the CEO or a business unit owner, in which case, those roles would be the next step. In other organizations, a Chief Product Officer role exists and becomes the next step. Data from Emsi shows that there has been a 140% increase in CPO postings from Nov 2019 to Nov 2020; a clear reflection of organizations’ increasing awareness of the value of the role of product leadership in aligning customer needs, technology, and business strategy, and the increasing number of opportunities for advancement to the executive suite in this field.
Next Steps: Putting Words Into Action
We formed the Product Management Standards Board to increase clarity of and access to skills and careers so the next generation of product management talent can maximize their global impact in organizations. Our career framework is a first step toward achieving this goal, but it’s only effective if followed by action.
To put this theory into action, we have started using this framework within our organizations to:
Explain career progression and roles across our teams to guide development conversations and linking individual activities to strategic objectives on our product teams.
Guide high-potential employees on how to maximize their leadership skills.
Evaluate job candidates based on their skills match with the function for which they are applying, rather than exclusively what schools they’ve gone to or previous roles they’ve held.
If you could benefit from these same actions, we encourage you to join us in using the framework for similar purposes in your organizations. Our industry needs to use a common language around product management, and that language extends beyond our board.
This is a living document, and we’ll be seeking feedback from partners in our executive teams, industry associations, and peers around the world. We’re also asking you. If you have feedback on how this could be useful for you, please let us know at email@example.com.
By coalescing on what it takes to succeed in product management careers, we can begin to solve some of the pertinent talent challenges facing the profession and better prepare the next generation of leaders. We look forward to working to standardize product management career paths together.
Data is everywhere and in every part of your business; however, data is often left for technical teams to figure out. In recent years, data has been prioritized in digital transformation efforts, with an increasing amount of businesses striving to be data-first. Hoping to leverage new tools, technologies and hiring data analysts and scientists are often overlooking one essential fact: data is for everyone, and every employee can benefit from acquiring data skills.
Businesses who leave skills out of the equation in their data transformation efforts are further widening their skill gaps. In fact, according to Accenture, 74% of employees report feeling overwhelmed when working with data. According to Deloitte, contributors aren’t the only ones; 67% of leaders say they are not comfortable accessing or using data. It’s time to change all of this.
Perhaps this anxiety and discomfort stem from businesses misunderstanding the role every employee has in leveraging data:
Leaders set the vision and use data to ensure that they are making the right business decisions.
Data practitioners solve complex problems with a blend of technical ability in analytics and data science.
The broader organization uses data to understand impact, communicate results, and make decisions.
All roles can benefit from upskilling to shift mindsets, gain fluency, and build efficiencies across the business, with building literacy across the broader organization being the most urgent priority.
What does data literacy look like?
Data literacy is the ability to create, read, and analyze data, and then communicate that information and use it effectively. To do this, people must understand how data is collected, where it comes from, what it shows, how it can be used, and why it’s important.
Being data-literate means understanding:
Literacy Goal: Understanding the data lifecycle, data roles and responsibilities, and how data flows through an organization.
Data Ethics & Privacy
Literacy Goal: Explain why ethics and privacy are essential and understand the role each employee has to play.
Literacy Goal: Learn why common types of visualizations are chosen to promote certain comparisons and interpret the information.
Literacy Goal: Describe data and spot trends in visualizations.
Artificial Intelligence (AI)
Literacy Goal: Identify opportunities to integrate AI and data science tools within your workflow.
Giving data skills to all employees will help businesses meet their loftiest data transformation goals. Training all employees comes with many benefits, such as higher decision quality and improved cross-functional communication. According to Deloitte, in companies where all employees train on analytics, 88% exceeded their business goals.
Five Ways to Build a Data-Literate Organization
1. Understand How Data is Being Used in Your Business
Shifting mindsets at the top of the org chart is essential to becoming a data-literate org. Being a role model for your employees helps build trust with your new skills — they will help you form a data-driven agenda. With the right skills, you’ll be able to prioritize projects with the most business impact. Data literacy also helps you effectively communicate with data practitioners within your organization and help focus your contributors on the data points that truly matter.
2. Define Preferred Data Usage in Your Business
Data is plentiful, so narrowing that data down to only the most essential points is imperative to success. Understand what data you wish to collect and track, how that data will be used, and what tools and skills are needed to leverage that data successfully.
3. Get Leadership Buy-in Across the Business
Getting buy-in from leaders across the business is essential to establishing a data-first culture. Any strategic initiative starts at the top, and leaders that understand the power of a strong data culture will be willing to make the tools, training, and people investments necessary to build one.
4. Create a Training Plan
Once you know what data you wish to use, consider which skills would be the most beneficial. Remember, everyone can benefit from training. We recommend building literacy skills where there are definite gaps among leaders and across the broader organization.
5. Put New Skills Into Practice
Your plan is in place! Now, give your teams learning opportunities and explain why these skills will matter to the business’s success.After training, provide team members opportunities to practice their new skills by giving them goals directly related to using, communicating with, and becoming more data-proficient.
Continue to offer learning opportunities for those employees who wish to advance past literacy and into hard skills. Consider upskilling your data practitioners to become more efficient.
In an era of increased digitization, many businesses still don’t know how to use data to gain critical insights and information on goals and objectives. From the intern to the C-suite, it’s more important than ever for all business members to create, read, analyze, and communicate data pertaining to these objectives. Data literacy at all levels can and should be encouraged to future proof the organization and support overall business goals. Investing in upskilling to ensure that everyone is comfortable bringing data to the table has ROIs well beyond cost.
Thinking about building your teams’ data literacy? Learn more about how our data curriculum can help your business make this powerful pivot.
We are in the midst of a grand economic experiment catalyzed by COVID-19 to accelerate digital transformation efforts in almost every business. The days of arguing whether digital transformation is the right path are over. Simply put, companies that don’t modernize will fail. That said, not every company is on the same journey. By the end of 2019, nearly 20% of enterprise organizations had not started digital transformation efforts. Another 40% said they were currently undergoing it, and budgets are rising to match. IDC forecasts global spending for digital transformation rose by about 17.9% in 2019 to $1.18 trillion. Partially due to COVID-19, that number is expected to increase by another 10.4% in 2020.
If you asked businesses before the pandemic about the importance of digital transformation, most would agree that it was important, but not all would prioritize it in the same ways. However, digitization becomes crucial very quickly when tens of millions of people must work from home, and non-essential businesses are closed to foot traffic.
Look at the shift in global consumer sentiment in the first week of May:
While some of these shifts were temporary, many are not. We see fundamental changes in the way the economy works. A recent IDG survey found that 59% of IT decision-makers have accelerated their efforts with spending likely to grow by more than 10% in 2020. Demand for skills in technology, data analysis, product, marketing, and UX are higher than ever as companies shift to a new model that emphasizes remote operations.
Time is no longer a luxury for organizations that had not yet started or been in the early stages of planning digital transformation efforts. The new normal requires businesses to be agile and digital.
What is a Digital Transformation?
Digital transformation is the process of remodeling existing business processes to meet the current market — specifically, the needs of the customer. Until recently, that included banks implementing mobile apps and investing heavily in FinTech, or healthcare organizations digitizing records and connecting devices and people seamlessly across a large network, etc. Digital transformation was previously about supplementing existing offerings with new technologies that met consumers where they were most likely to engage.
Post-COVID-19, digital transformation is still about these things. One of the many challenges large organizations have with digital transformation is that they attempt to implement small efforts within silos in a much larger company infrastructure — digital transformation is bigger than that. It’s about recognizing the core ways to interact with customers and making smart investments to address specific challenges.
Why is digital transformation different from simple digitization? The latter is about shifting away from paper-based and analog processes. It’s about making data accessible to everyone in an organization and connecting employees at all levels. Digital transformation is about leveraging those changes to improve the relationship between your company and your customers with things like personalized messaging, configurable products and services, and more accessible, catered customer service offerings.
Of course, these efforts can be difficult to execute. To date, less than 30% of them have succeeded, and only 16% have improved performance and resulted in long-term changes. While smaller businesses (those with fewer than 100 employees) are significantly more likely to succeed, enterprise organizations are challenged to realize demonstrable returns. However, it’s not the concept that’s flawed; it’s the process. Too many organizations start from the top, thinking of the technologies and tools and not the people who will implement them.
Digital transformation relies on people at multiple levels. Not only are highly skilled individuals in marketing, IT, and product required to implement new initiatives, the entire workforce must buy into these changes. Without high levels of adoption, large investments in new software and processes can quickly look like mistakes.
Why Are Digital Transformations Important?
More than 80% of decision-makers in technology and engineering see a mismatch between the skills workers have, and the skills companies need. The biggest gaps are in strategic thinking and analysis: data analytics, data science, innovation strategy, and web development, among others. That talent gap with organizations is growing as more companies are eager to bring on top-tier talent to steer their efforts into the next decade. Digitization addresses this by leveraging artificial intelligence and machine learning to support internal workers and enable the development of the right skills for the necessary work.
Furthermore, companies should be looking at the staff they already have to see how they can help support digital transformation goals. The Build vs. Buy Approach to Talent allows companies to build internal competencies that support digital transformation. We know that 75% of digital transformations fail because companies focus on systems instead of including talent as a critical enabler. Of the large chunk that fails, 70% are due to a lack of user adoption and behavioral change. Digital transformation isn’t only about buying the flashiest new tools. It’s about crafting a strategy that your employees are willing and able to implement. You need buy-in from every level of an organization. When employees embrace the concept of digital transformation, technology becomes secondary. As employees work in ways they never have before, this is more important than ever.
This might all sound like a lot of work. Coming into 2021, many companies had long put off this process because of that perception. But, the growth potential is staggering. MGI estimated that an additional $13 trillion could be added to global GDP in just 10 years by implementing AI, automation, and digitization. Despite that, only 25% of the economic potential of digitization has yet been captured. And that’s the average. In some industries, the digital frontier gap is significantly larger — especially in revenue generation, automation, and digitization of the workforce.
Despite the delays before this year, many chief executives now see the value of digital transformation. Two-thirds of CEOs expect to change their business models due to digital technologies, and 77% of digitally mature companies are more likely to grow digital roles in the next three years. These trends have only continued in light of COVID-19. A July survey showed that the number of days spent at home by employees had grown four-fold. Ultimately, all remote employees require technological support. Think about all the technology that we rely upon that needs adequate support, too: Cloud-based applications. WAN modernization efforts to support a dispersed workforce and maintain network security. Improvements to active directory and identity management.
The impact of digital transformation efforts leads to fundamental changes in departmental models as well. Marketing, for example, is leveraging AI to improve the customer experience across the board. With 80% of companies now using AI chatbots and 84% of customer-focused companies spending heavily to improve mobile experiences, the way organizations engage with prospects and customers has fundamentally changed in the last half-decade.
The Impact of Digital Transformation (Done Right)
Over the past six months, workforce digitization has accelerated faster than at any point in the last twenty years. For organizations ahead of the game, it was a chance to put their innovative efforts to the test. For those who had delayed digital transformation initiatives, it was a major challenge. With limited resources, a highly competitive talent pool, and an uncertain future reshaped by the events of 2020, it’s more important than ever to develop a strategy that guides your business forward. This is a massive opportunity for leaders who understand the moment we are in, to arm their organizations with the tools, resources, and processes needed to succeed.
Data is integral to every business. It helps organizations set strategies, report on wins and losses, make smarter business decisions, and is the connective tissue between leaders and teams. However, as businesses lean into a data-first future, through digital transformation, they must also take into account the skills needed to successfully leverage data.
According to New Vantage Partners, only 24% of organizations have successfully become data-driven. Organizations undergoing data transformations don’t typically fail because of tools or technology but because of talent-related challenges, such as cultural resistance and lack of leadership, contributing to a general discomfort communicating with and using data. A study by Accenture confirms that 74% of employees feel overwhelmed or unhappy when working with data.
It’s time to change all of that. Investment in data upskilling for existing talent is a step in the right direction for businesses hoping to benefit from the full use of data and AI. From mindset training for leaders to upskilling functional practitioners on modern practices to fluency for the broader organization, businesses must begin to see the opportunity and importance of data transformation in the context of employee skills.
Introducing Four New Training Programs to Embed Data Skills Into Your Organization
We’ve had the pleasure of helping businesses, such as Guardian and Booz Allen Hamilton, build data-driven workforces from within through upskilling and reskilling. Our work with the AI & Data Science Standards Board and our customer and industry research helps us to understand what training each employee — from leader to contributor— needs to successfully leverage data within their roles.
As the digital landscape continues to evolve, we saw an opportunity to further enable teams to transform into data-driven organizations. Over the last few months, we’ve been hard at work refreshing existing training programs for leaders and functional practitioners and building new ones for the broader organization, all connecting to the most emergent data-skilling needs.
Here’s a quick overview of those programs:
Data Literacy On Demand [New]: Data literacy for all employees has become a must-have for businesses striving to build a data-first culture. This flexible training solution fits right into your employee’s workflow and gives them the foundational knowledge they need to start interpreting and communicating with data.
Building Data Literacy [New]: For deeper, more targeted data literacy training, we created a brand new workshop, Building Data Literacy. Use Building Data Literacy to train smaller cohorts of employees or as a deeper, more hands-on follow-up to Data Literacy On Demand.
AI for Leaders [Refreshed]: We refreshed our AI for Leaders workshop to better focus on giving organizations a place to start when considering AI. This approach for getting started with AI was validated by our AI & Data Science Standards Board members.
Advanced Analytics Accelerator [Refreshed]: Advanced Analytics Accelerator is one of our most popular data programs. We used client feedback to develop a new assessment approach and refresh the curriculum to better meet learner needs. New assessments help show learner uplift and mastery of concepts covered in the program.
These new programs will allow you to:
Take the First Step With Data & AI: Move transformation initiatives forward by giving every audience in your business foundational data and AI skills.
Stay on the Cutting-Edge With Content Validated by Experts: Give your people real world, actionable insights with training programs that are created with and delivered by subject matter experts.
Reach Employees With Relevant Training: Maximize learner retention with curricula designed and delivered in the right format for your learning objectives.
More to Come
Over the next few months, we will be releasing more useful workforce insights, updated training programs, and more. Keep your eyes on the GA blog or get in touch with us to hear the latest.
Want to learn more about how we can help your organization lean into a data-first future? Download the full catalog of GA’s data skilling solutions here.
Systemic racism has been a critical problem for generations, and the Black Lives Matter (BLM) movement has brought centuries of injustice to the spotlight. Over the last six months, following the deaths of Ahmaud Arbery, Breonna Taylor, George Floyd, and so many others, individuals worldwide have taken a stand to fight oppression and discrimination against Black, Indigenous, and People of Color (BIPOC).
It’s an inflamed and sensitive time that calls for radical change. Diverse companies not only outperform their less diverse peers, but they also forge stronger connections with their customers. 77% of U.S. consumers said it was “deeply important that companies respond to racial injustice to earn or keep their trust.” As consumer bases diversify and consumers change their spending habits, companies need to ensure that their content, messaging, product, design, and data align with these shifts. While organizations know they need stronger commitments to diversity, equity, and inclusion (DEI), many don’t know where to start — individual companies often take action but lack coordinated guidance.
Our Standards Boards were established to increase the clarity of and access to careers in marketing, AI & data science, product management, and UX design. To date, the Boards have primarily focused on providing clarity on the skills needed within specific fields by publishing career frameworks and certifications. Now, it’s time to connect to the access portion of their work. Together, the Standards Boards have crafted DEI principles that guide organizations on how to provide equitable access to skills and career paths for their employees.
Improving Diversity, Equity, & Inclusion: A Practical Guide
To create a meaningful guide to DEI, our Standards Board Members reflected on what diversity, equity, and inclusion meant as individuals, employees, and leaders of organizations. With this in mind, we focused on improving the current DEI practices each member saw being used and creating a practical playbook that could be applied across companies and disciplines. Ultimately, we hope this playbook serves as a starting point for conversations around DEI that lead to career paths for diverse talent and helps leaders create work environments in which all can succeed.
Our Standards Board DEI task force drafted a playbook of seven overarching principles that have been refined through feedback from colleagues, DEI experts, GA instructors and staff, plus more. These principles were designed to guide any organization’s DEI strategy, regardless of function, industry, geography, or company size.
These principles were created by leaders in various industries who have a real conviction for driving change. Below, you’ll find a few principles our board members stand behind; they hope you’ll use these to drive conversations and assess how your organization is implementing DEI.
“We all recognize a critical need to address systemic issues with diversity, equity, and inclusion through actions — not just words. These principles were created to support action plans for every company to ensure a culture of belonging for all employees, at all levels throughout the organization.”
We hope these principles spark conversations at your organizations that lead to tactical activities such as revisiting policies, analyzing pay equity, and tracking diversity data. While some of these principles are being implemented across board member organizations, some aren’t. Our intention is to enable organizations to implement DEI policies across every level of an organization through actions, not just words.
The Actions We Are Taking
It’s essential that these aforementioned principles are put into action. Across the Standards Boards, we’ll be incorporating DEI into career frameworks, assessments, and products. We’ll also be actively recruiting more board members in 2021 to ensure our boards are representative of the talent in their industries.
Within GA, we’re also committed to aligning these principles with our work. We’re actively promoting equity and justice by using our platform to discuss why we should all be angry, and we’re making real commitments to ensure we’re not idle in the face of systemic racism. We’re cultivating conversations about our diversity story and creating a culture of dissent through creating an Inclusion Committee as well as a Fireside Chat series that brings employees and executives together for candid conversations on D&I (both started in 2019).
We’re cultivating our future employee base by updating our policies to require a diverse slate of interview candidates for all leadership-level positions, revisiting internal promotion criteria, and launching a mentorship program (Code Grow) so our Black, Indigenous, and People of Color (BIPOC) staff has formal avenues to develop their careers. To attract diverse talent, we are utilizing outlier career-search platforms like AngelList, Underdog.io, Vettery, c0ffe3, Black Creatives, and more.
We’re transparent about the areas of difference we’re cultivating by reformalizing our Employee Resource Groups (ERGs) with dedicated executive sponsors. And we’re tying outcomes to actions by measuring all our people metrics and making plans to improve the experiences of underrepresented groups in our organization. We’re also ensuring DEI is central in our product development.
The principles set forward by the Standards Boards are essential to capturing many voices across multiple sectors because they encapsulate what has been learned on our individual and collective journeys. We look to evolving and integrating these principles into GA’s courses, continue the hard work and commitment to DEI at GA, and further develop organizational behaviors, along with the willingness of our Standards Board partners to do the same.
The list below notes the leaders that have signed on. If you’re a leader who is ready to join us and adopt these principles, you can sign on here.
Shri Bhupathi, Founder and Technical Fellow, MILL5 Gideon Bullock Andrea Chesleigh Chad Evans, SVP, Product and Platform, NBA Stephen Gates Benjamin Harrell, Chief Marketing Officer, Priceline Marla Kaplowitz, President and CEO, 4A’s Willy Lai Louis Lecat Kevin Lyons, SVP of Technology, Nielsen Francisco Martin, Head of Business Development, Thrive Global Marilyn McDonald, SVP of B2B Experiences, Mastercard Kristof Neirynck, CMO of Global Brands, Walgreens Boots Alliance Gretchen O’Hara, VP of AI & Sustainability, Strategy & Partnership, Microsoft Michelle Onvural, CEO, Bonobos Seth Rogin, CEO, Magnolia Media Partners Nick Perugini Adam Powers Professor Andrew Stephen, Associate Dean of Research & L’Oréal Professor of Marketing Linda Tong, General Manager, AppDynamics (a Cisco Company) Sang Valte, UX Director, Jellyfish
It’s a new world that calls for moral bravery and clear actions. We welcome all feedback on these principles and look forward to hearing how your organization implements these and other DEI initiatives.
When you hear the term “artificial intelligence,” what comes to mind?
The idea that AI is upending the modern workforce is a big obstacle companies have to overcome when thinking about how to best integrate and adopt artificial intelligence into their business. While it’s true that automation may displace 75 million jobs, statistics also indicate that it will generate 133 million new ones worldwide by 2022. COVID-19 is only accelerating this change, transforming business models in every industry and challenging the skill sets of their teams.
While leaders know that artificial intelligence can unlock incredible insight, many companies — especially traditional ones — are struggling to adopt it. The ability to identify and implement AI technology can be overwhelming and complicated in equal measure. This stems from four critical challenges with emerging technology:
Complex change management: There is often a disconnect between how companies anticipate using AI solutions and the ability of leaders and managers to handle the degree of adaptation that’s required. In general, the lack of understanding about what artificial intelligence actually is and what it does gets in the way of fully planning for this integration in order to really improve the business.
Lack of examples: There aren’t enough publicly available common use cases from which leaders can learn.
Need for ethics guidelines: There isn’t enough awareness of how to make good decisions around the ethical and responsible use of artificial intelligence.
Skills gaps for practitioners: There aren’t enough people with hard skills in AI, DevOps, cloud, machine learning, and data engineering to really enable this change, even as leaders begin identifying the right opportunities for it. About 95% of the AI-impacted workforce population (as identified by the adoption map below)* does not have skills in these sectors.
To address these challenges, we partnered with Microsoft to form the AI & Data Science Standards Board, representing a broad set of AI and data executives across the tech, auto, media, healthcare, professional services, and hospitality sectors. The board aims to increase the clarity around and access to AI skills and careers so that organizations and leaders can responsibly realize the opportunity of artificial intelligence.
Board members agree that, while machine learning and automated tools have the potential to drive better business decision-making, the No. 1 barrier to adoption is an organization’s inability to identify and implement artificial intelligence into its business model. This begs the question: How do you transform a business model?
It starts by taking a look at your workforce strategy.
Defining Roles in the AI Workforce
A true picture of AI encompasses how a workforce collaborates across teams, how workers do their work, and how they communicate with leadership. With this in mind, we created an AI & Data Science Adoption Map to help organizations evaluate what’s required for their artificial intelligence and data science adoption journey. The map captures the board’s perspective on which groups and functions should be responsible for the different elements of enabling a change to create a successful AI organization.
Let’s break down the map’s key features. At a high level, we have three groups: Leaders, Creators, and Users. These were chosen specifically to display their interconnectivity and showcase each group’s responsibilities. Leaders set the vision and are accountable for the responsible adoption of AI, which influences the Creators’ work. Creators implement the vision (set by the Leaders) while keeping in mind the needs and processes of the Users. Users then leverage the outputs of this AI and data science adoption to improve speed, efficiency, and quality of work. This map is not a reflection of an org chart, rather, it provides a bird’s-eye view of who should be involved in AI adoption and how it impacts their function. Download the map for more detail about the key functions and titles that fall within each group.
Many of our board members and enterprise partners acknowledge that few leaders truly know where to start when it comes to implementing and effectively leveraging artificial intelligence. But Gretchen O’Hara, VP of U.S. AI & Sustainability Strategy & Partnerships at Microsoft, stated that the “map will help companies reskill faster and at scale.”
If you could benefit from using the AI & Data Science Adoption Map, we encourage you to join the board in reviewing this framework to evaluate your organization and the strengths and gaps in your AI system.
Implementing AI and data science strategy within an organization is complex, and the AI & Data Science Adoption Map is a first step toward achieving improved clarity and definition for the field. The board’s next focus will be to more clearly articulate the skills required across different functions. Of course, we will also be evolving our training and certifications for relevant roles to ensure that team members at every level can better execute their goals.
This is only the beginning, and we can’t wait to hear from you about how you plan to use the map. We look forward to continuing the conversation in the months to come.
Download the free AI & Data Science Adoption map here. Have reactions or feedback? We’d love to hear from you! Email us at firstname.lastname@example.org.
Meet the AI & Data Science Standards Board
Since 2011, General Assembly has trained individuals and teams online and on campus through experiential education in technology, data, marketing, design, and product. Learn more about how we can transform your talent and our solutions to upskill and reskill teams around the globe.
Even before the twists and turns caused by COVID-19, digital transformation was top-of-mind for today’s business leaders. Companies everywhere are reimagining their workforces and doubling down on digital capabilities and systems with an accelerated timeline.
But success isn’t guaranteed.
In fact, 75% of digital transformations fail to generate returns that exceed the original investment1. Why? Because companies often fall into the trap of focusing on systems rather than people. Leading companies recognize that, in order for their digital transformations to work, employees need the structure, mindset, skills, and vocabulary to support and drive new strategies — from senior leadership to those on the front lines.
Through collaborations with global organizations like L’Oréal, Booz Allen Hamilton, Guardian, and many more, we have identified our top six people-first strategies for driving success in digital transformation. We first published this list in 2018 and have refreshed them to meet this moment. Despite rapid market evolution, they still ring true.
1. Create a Leadership Agenda for Change
Given the far-reaching implications of a successful digital transformation — especially in 2020 — it’s critical to have full leadership support and encouragement from the top. To translate theory into action:
State a bold goal simply and repeatedly. Adopt a simple-but-bold vision for the future, and frame every key milestone — including company updates, staffing shifts, new launches, and training initiatives — in the context of how it is impacting that goal.
Hold an executive sponsor accountable and give them access and authority. This C-suite member must take responsibility to carry initiatives forward and make the organizational changes necessary to bring your goal to life.
Campaign internally and externally. Reinforce transformation goals by developing talking points and slogans that are easy to grasp and remember. By building a reputation as a tech-forward employer, your company can attract the right tech talent and create an internal culture that motivates employees to drive initiatives forward.
2. Embrace Agility & Uncertainty
Agility is key to success when undertaking digital transformations. Gone are the days of three-to-five-year strategy cycles and two-to-three-year product and marketing innovation plans. Today’s technologies and consumer needs change faster than historical business roadmaps can deliver.
Winners in this environment learn to adapt and adjust, finding digital equivalents to the traditional processes that guided business thinking and development in the past. This is as much a mindset shift as it is a physical shift in work, as — at least for the short-term — face-to-face consumer interactions have been largely replaced by virtual consumer encounters.
Take Procter & Gamble, which recognized this need and established P&G Ventures to create new, innovative direct-to-consumer brands. “The disruption of DTC was biting on our heels. How consumers are discovering new brands is different than how we grew up. [P&G Ventures] gives us a more nimble, agile way to get closer to the consumer,”2 Leigh Radford, the initiative’s vice president and general manager, said. P&G Ventures brought us on to offer capability training in digital marketing disciplines, including Facebook and social media marketing, eCommerce strategy, and marketing analytics. As a result, most of its product design and brand creative is done in-house, and leaders across all levels and functions know how to remain close to the customer.
3. Organize Around the Consumer
The consumer and customer must be at the center of any successful digital transformation. This is the only way to stay grounded in the reality of the market and resist the urge to chase every new trend or platform.
First and foremost, it’s essential to understand your consumers — their tastes, habits, ways of communicating, and pathways to purchase. Leading companies implement tools such as journey mapping, personas, and user research to learn about consumer needs. Then, assess the best way to organize and address your findings through different departments such as product development, marketing, and sales.
Finally, allow for new injections of people, ideas, and technology within your organization to incorporate new abilities, approaches, and ideas. We’ll explore this further in Strategy 6.
4. Measure & Reward Based on Metrics
Digital transformations often fail to take HR into account, particularly when it comes to managing employee performance against executing on these goals. This is often a severe blocker to real change — if people’s personal goals, compensation, and motivators aren’t aligned with the organization’s, there’s unlikely to be much positive impact.
Update performance management tools to reflect the business metrics and desired behaviors that matter to individual roles, and track the metrics that employee efforts can directly impact. We recommend using “micro-metrics” such as:
Number of digital media A/B tests executed per month to monitor the company’s embrace of experimentation.
Time-to-deployment for new products to measure hours saved by using new coding applications such as React libraries.
Number and scale of manual data processes automated to measure efficiency gains from using Python instead of Excel.
You can further support employees by describing key behaviors and competencies that will help them achieve success.
5. Bring Data to Every Conversation
We believe strongly in “data-driven people strategy.” In practice, this means that hiring, development, and team structure are all underpinned by robust assessments, and the resulting data helps to understand and pinpoint each individual’s strengths and weaknesses.
GA assessments are built in partnership with top industry executives on our Standards Boards who help define excellence in their fields. By designing and deploying practical skills assessments, we provide employers with a clear and consistent understanding of their teams’ abilities in key high-demand domains, including marketing, data, and tech.
Collecting this data can shape a variety of goals, including benchmarking existing talent against the industry, evaluating job applicants, designing learning paths for employees, and making decisions about organizational structure.
6. Invest in a Culture of Lifelong Learning
Given the speed at which change is taking place, our recommendation is simple: Companies need to invest in learning, both at the institutional and individual levels. Leaders not only need to embrace new technologies but also build digital mindsets at all levels of the organization to power new ways of working.
Keep in mind: Talent with in-demand skills is not only scarce and expensive but also difficult to retain, so companies cannot rely on “buying” talent alone3. Prioritizing up- and reskilling is a necessary measure in order to transform teams and organizations for the future. “Building” talent through training programs is often a more efficient route to acquire these skills versus searching for them externally. What’s more, research suggests that education is among the most-valued benefits for modern employees, boosting retention, engagement, and loyalty.
Thomas Malone, professor at MIT’s Sloan School of Management and director of its Center for Collective Intelligence, told Deloitte that: “Many decisions in a company are made by communities — a kind of informal consensus involving community norms. If you want to accomplish almost anything in the world and if you’re realistic about it, you need to be thinking about how to work with [collective community intelligence] to achieve whatever you want.”4
As you build a culture of learning, the foundation of digital transformations, it’s essential that everyone — from the CEO to individual contributors — is involved.
Learn more about how General Assembly can help guide your company’s talent transformation.
“Interactive,” “Engaging,” “Hands-on,” “Relevant,” “Practical,” “Digestible,” “Clear and easy to understand,” or “Fun!”
We’ve asked this question hundreds of times, and the answers are rarely surprising. Yet, when we ask another question, “How many of the classes you’ve taken actually fit these descriptions?” sadly, the percentage is often quite low — but not for our students.
At GA, we’ve mastered the magic of delivering great learning experiences for each student and client.
Interested in what this means? Read on.
Principles of Andragogy
Andragogy is an esoteric term meaning the method or practice of teaching adult learners. If this is the first time you’re seeing the word “andragogy,” you’re not alone.
The reason we mention this term is that we’re often asked about our “pedagogy”, in reference to our learning theory. Considering that the word most commonly used to discuss learning theory (pedagogy) has a prefix that means “relating to children” (ped) says something about the way society thinks about education. Namely, that learning is primarily for children. This has never been less true than it is today, where even successful professionals with years of post-graduate education and executive experience need to continuously upskill to keep pace with our rapidly changing world — now more than ever.
The distinction between andragogy, the adult learning methodology, and pedagogy, the children’s learning methodology, is important because while many good learning experience qualities such as engagement and interaction apply to both adults and children, there are some key contextual differences.
In both cases, excellent educators reference Bloom’s Cognitive Taxonomy to ground their courses in observable learning outcomes, and aim for active, hands-on learning with multiple opportunities to check for understanding and provide feedback along the way.
However, we all understand that adulthood differs from childhood. As adults, we have an abundance of two things children typically have less of: choice and responsibility.
What does this have to do with learning design? When you start thinking about taking a course or changing your career as an adult, you are plagued with different considerations than you had in grade school:
Is this worth my time and money?
Will I be successful in learning this?
What kind of people are going to be in my class?
Will this be useful for my unique set of circumstances?
Should I just Google it?
Designing for the Adult Learner
Six key actions tend to assuage adult learning anxieties, and help learners construct individualized meaning from a shared learning experience:
We know that adults learn best when they are active in the learning experience, when they are working toward solving a realistic, relevant, and interesting problem, and when they can show up as a whole person with individual experiences, goals, and preferences. Adults are not empty vessels… they are fully developed and experienced individuals.
So how does this knowledge impact our approach to learning? We design classes where the instructor does not just push information to the students; the instructor creates space where students can share their perspectives, be social, build connections, hear from other people, stretch their minds, and enjoy the process.
If you’re having trouble picturing a unique GA learning experience, here is an example of what it looks like in practice:
As a warm-up activity, we ask groups of participants to “be the search engine.” We give them printouts of five different Google search results from a previous search we conducted, such as “lunch.” We then ask them to arrange those printouts in the order they should be returned to the searcher in response to a few rapid-fire search queries, such as:
“Best Restaurant to Take Clients”
“Vegan Lunch Downtown”
This succession of questions leads students to look at the details of the pages — their titles, contents, references to location, date published, etc. — to make and discuss these decisions. These details are factors of how search algorithms work and factors they will need to optimize for in their SEO strategies.
The exercise illustrated above takes about ten minutes, roughly the same amount of time it would take the instructor to explain how search engines work. However, the exercise primes the students with decision-making, real-life engagement, and meaningful, useful information that can later be built upon. Most importantly, the students have not just heard the information; they have processed it — and had fun along the way.
Instructional Design in the Digital Age
At GA, we deliver learning across two spectrums: the experience spectrum, which ranges from absolute beginners to field professionals seeking to remain current, and the duration spectrum, which ranges from 20-minute eLearning modules to 12-week, 480-hour immersive courses.
Designing a relevant and active learning experience across these spectrums is not easy, but it’s core to our proven success in digital skills education over the last nine years. Our instructional design practices are rooted in:
Modern Digital Design Practices
Learning Theory and Sciences
Understanding each of these fields helps us to better utilize the other.
Modern digital design practices include user research, design thinking, agile development, data analysis, and rapid iteration. These practices are typically core drivers of the last 30 years of technology innovation, yet too many educational institutions have been slow to embrace them. By leveraging these more modern practices into our instructional design process, we can make better use of learning theories and sciences that largely emerged in the 20th century, including the behaviorist learning theory and constructivist learning theory.
For example, Nir Eyal’s book, “Hooked: How to Build Habit-Forming Products,” elaborates on a behaviorist learning theory used by UX designers and product teams to keep users coming back to their platforms. Think of that addictive social media feed, or how you can’t resist tapping an app with a big red notification bubble…
This behaviorist strategy is also well-suited for learning beginners just starting in a field, or those independently working through material on a digital learning platform. Through data analysis, we’ve seen this user need come through in myGA (eLearning) lessons via requests for “more knowledge checks,” and we’ve added them accordingly. Those frequent checks help learners gain confidence and validate their understanding, which is particularly important in the absence of a live instructor.
As a learner “climbs” Bloom’s taxonomy into greater depths of knowledge in a field, frequent, short exercises start to become irritating, and gamification attempts can feel juvenile. We’ve seen this in students’ feedback on long-form courses where they’d prefer fewer activities. This feedback led us to consolidate those activities into select, more robust exercises.
Meaningful, more robust exercises are examples of the constructivist learning theory, which suggests no singular “truth,” and each individual will derive a personal meaning through action and reflection. At GA, this shows up in all of our long-form courses, where in the end, students solve real-world business problems of their choice in a capstone project.
Guiding learners to make their own meaning through project work is great when you are leading a classroom of professionals in solving a business problem using new digital skills. Still, it can leave people lost in certain scenarios, i.e., if applied in a room full of first-time programmers trying to understand what a Python loop is. That’s why both constructivism and behaviorism strategies are effective for different purposes.
Through user research and data analysis of the thousands of learners collected over the years, we know how to deploy the right strategy at the right time, and iterate in rapid cycles based on continuous feedback from our instructors and learners.
Bringing Everything Together
We’re passionate about delivering best-in-class education, and hope a deep dive into our approach to learning has provided some helpful insights as you explore an upskilling journey that will ensure both personal and professional growth for your teams.
Alison Kashin is the Director of Instructional Design at General Assembly.
Since 2011, General Assembly has trained individuals and teams online and on-campus through experiential education in the fields of technology, data, marketing, design, and product. Learn more about how we can transform your talent, and our solutions to upskill and reskill teams across the globe.