Consider the present state of work. Nearly every business and industry has been thrown into the future and forced to innovate and collaborate in an entirely virtual environment — years of inherent routines and “rules” have been cast aside, and everyone has needed to reset and restart. Remarkably, companies haven’t only survived in this climate — some have even thrived. So, while the pandemic truly has been a test of survival on every level, this challenging time has fortified and innovated us in ways that will continue to propel us forward.
This moment is one of unanticipated celebration as it has fueled the ongoing acceleration of digital transformation for companies around the globe. Before the pandemic, leaders everywhere began preparing for reskilling, talent recruitment, and future-proofing their business strategies at a “nice to have, should do” pace. Fast-forward to 2021, and we have new issues to contend with. From the return to offices to The Great Resignation to constantly zagging in response to breaking news, global travel updates, and the race to end the biggest pandemic of our lifetime — forget the “new normal.” Leaders are far better off asking, “What’s next?”
That’s why we’re excited to announce the launch of our standards board digital magazine, The Index. Within this issue, we’re not interested in the topic of returning to business as usual, so we set out to explore “the next normal.”
Keep reading to learn more.
What’s Inside The Index:
The Index includes stories that help leaders take on the next normal and navigate the future of work. Within the pages, you’ll discover dynamic stories such as:
Beyond Buzzwords: The Journey to Make Your Company Data-DrivenÂ
Google Stole the Cookies from the Jar: Why & What’s Next
What Remote Teams Can Learn From Design
The Future & Importance of Inclusive Company CulturesÂ
& So Much MoreÂ
You Should Download the Index If:
You’re a leader looking for advice on how to navigate the future of work.
You’re interested in future-focused topics that will help you bring your organization to the next level.
You know how valuable building an inclusive company culture is and want to learn how other businesses are thinking about this.
Get a copy of The Index by clicking and downloading this handy link.
At the beginning of 2020, most of P&G’s products were sold in brick-and-mortar retailers. When COVID-19 struck, they had to go back to the basics: refocusing on website quality, partnerships with e-retailers, and making information available online to sell brands without in-store promotions. In other words, they had to rechannel their path-to-purchase strategies to serve consumers when consumer behavior changed drastically and quickly.
Over the last 18+ months, large and small CPG companies have grappled with these same challenges: the explosion of eCommerce, the rising demand for sustainability, a shift in consumption from makeup toward skincare, and a massive increase in time spent on social media. As the pandemic accelerated the impact of technology and shifted consumer behaviors seemingly overnight, businesses have had to become even more innovative and agile to keep up.
In a space where the only constant is change, we talked to leaders in CPG and marketing experts to understand their most effective techniques for adapting to the ever-changing digital landscape and equipping their marketing talent for success. The top answer? Getting even more customer-centric with deeper and more frequent connections to their consumers.
Let’s break down what this means in three steps:
1. Consumers expect peak digital experiences that call on marketing to transform.
The growth of digital shopping last year was shocking, and it may be slowing down — but not by much. 2020 showed a 25.7% surge in eCommerce sales, and eMarketer predicts 2021 will bring another 16.8% gain, taking the global eCommerce sales pie up to nearly $5 trillion. Alongside this behavioral shift, consumers have experienced widespread emotional trauma that shifted all life priorities. This changing landscape sped up the need for digital transformation in marketing — not only in reaching consumers through digital channels but using technology to understand what they need in this new context.
“It’s easy for brands to sound tone-deaf,” recalls GA instructor Terry Rice, digital marketing expert, business development consultant, and writer for Entrepreneur magazine. Marketers need to “[take] the time to learn about consumer behavior shifts — and take the time to deploy empathy in marketing: we hear you, we understand you, and we’re here to support you.”
The social trends of the last 18 months have challenged marketers to up their game, particularly when it comes to winning over Gen Z. “They stand up for their values, they stand up for diversity and inclusion, and they have a big push in demand on sustainability,” says Philipp Markmann, CMO of L’Oreal and member of our Marketing standards board. In this climate, you have to bring real value beyond the product you make and tell consumers the causes you stand up for.
While this emotional challenge doesn’t fit with the classic business models of maximizing shareholder value (at least in the short run), CPG marketers across the board understand that they can’t fall into the trap of trying to optimize toward a past that no longer exists. Luckily, this is a challenge that cuts right to the heart of marketing principles, and marketers are best-prepared to create the solutions.
“More and more business questions will become behavioral questions and psychological questions because relying on past data to predict future behavior is increasingly unsafe,” emphasizes Rory Sutherland, vice chair at Ogilvy UK. “We vastly need marketers to elevate themselves in status and influence… understanding wants, needs, motivations, and fears have suddenly become 10x more important in 2021 than it was in 2018.”
2. Stay plugged into evolving consumers through innovative digital collaboration.
Shifting alongside consumer behaviors means mobilizing the digital transformation work that brands across the CPG space have been doing. Companies like Shiseido, P&G, and L’Oreal have invested in digital infrastructures to prepare for this future.
While L’Oreal has spent over 10 years building on digital marketing capabilities, COVID-19’s “massive digital stress test” required marketing and commercial teams to be bold and try new things. This required creative thinking and experimentation across teams — what L’Oreal calls a “company collaboration accelerator.”
“In March 2020, every machine learning algorithm you had for optimizing traffic was worthless, Ben Harrell, CMO at Priceline and member of our Marketing standards board, pointed out. “Data from yesterday and today is what matters.” Yet amidst this rapid consumer change, the marketing industry has seen a steep decrease in the cookies and other data streams they once relied on for personalization, meaning marketers need to rebuild the customer journey practically from scratch.
That’s where data literacy comes into play. Marketers need personalized customer data from other in-house teams, which increases the need for tight internal systems and communication of first-party data. This requires not only a shared digital language across marketing, data, and product but a digital literacy about information systems like MarTech. “Then you can start having meaningful conversations with your engineers to say, hey, I want to do XYZ with this consumer segment…can we potentially integrate a third-party service that is API-led?” Ogilvy’s Sutherland illustrates.
This type of collaborative innovation requires marketing to have the vocabulary to work with other teams to help solve complex technical problems, as well as the growth mindset that is so fundamental to digital culture.
In the long run, CPG leaders expect this tight-loop connection with customers to get even faster. Beyond simply protecting user privacy, the democratization of data is giving consumers more ownership of their data, which will ultimately challenge marketers to innovate commercial models directly with the customer based on the value of that data.
Salim Holder, founder and CEO at 4th Ave Market, is working toward making that vision a reality in this decade: “In 2030, we’re integrating our business model with the community we’re trying to deliver value to… and we provide financial incentives for the community.” This might mean discounts in exchange for sharing information and building strategy around the way communities engage with products organically. “As a result, the data that we get will allow us to make all the decisions… and [source] the information and the knowledge from the community that is also there to provide value in itself.”
3. Skills for a dynamic world — and the culture that keeps them fresh.
When it comes to enabling marketing teams to innovate, marketing leaders are unanimous: there is a need for constant learning.
“Instead of looking at ROI, we should be looking at the cost of inaction. If consumers have a pain point, it’s on us to solve customer problems,” Matthew Tumbleson, P&G entrepreneur-in-residence, stresses. “It needs to be an ongoing thing where we are upskilling forever.” When consumers have a good experience elsewhere, it’s on your brand to do it better, or you’ll be creating the conditions for you to lose. This means making sure they have the “hands-on-keyboard skills” — those that they’ve historically outsourced to agencies — in-house. “Even at P&G,” he says, “it requires continual improvement.”
At Shiseido, digital literacy is stressed across teams as the basis of good decision-making. That’s why Roxanne Ong, head of digital transformation at Shiseido, invests time and energy in ensuring that there is a common digital literacy across all employees.
“Marketing has become such a monster, if you will, as a disciplinary approach,” Ong says, so it’s hard to ensure everyone has the baseline skills that often aren’t taught in school or MBA programs. “What GA has done is crystalize the fundamentals a true-blue marketer needs to have on a foundational level before they can move on out to an expert level.” Shiseido used GA’s CM1 assessment to get a baseline check on their teams’ skills to identify gaps. From there, she leads teams to aspire to be a “T-skills employee,” one who possesses skills across the board to go deep in one of their functional fields.
Not only are marketing skills assessments like CM1 good for identifying development areas for teams, Entrepreneur magazine’s Rice points out, “For someone who’s an expert, it’s going to reveal blind spots and opportunities… If you’re an expert, it’s a good way to make sure that you’re aware of what your team’s doing and to make sure you’re up to date with best practices across platforms.”
Ultimately, though, Ong says, “Equally important to skills is culture.” Beyond the specifics of hard skilling, Ong emphasizes the need to invest in digital culture, i.e., take risks, have curiosity, and collaborate — evergreen soft skills. There will always be so much unknown, so you need to create a culture of constant learning to be responsive to consumer changes and build new solutions to problems. “It’s a day-by-day, week-by-week situation. The idea of being data-driven in the digital age cannot be underscored enough: keep your ears on the ground for the data pulses, large and small.”
Beyond curiosity, this takes courage: “Have the courage to try to actually go to a place that’s unknown to you. Understanding the nuance and how to do it well is a whole different story altogether.”
We work with CPG companies to successfully transform their traditional marketing teams into high-functioning digital marketers, helping them drive their top-end goals: eCommerce sales growth, omnichannel experience, and reduced dependence on agencies.
When companies come to us, they’ve often been trying to transform their marketing functions on their own — and, despite their best efforts, do not see the results they want. Their teams may demonstrate a grasp of digital concepts or familiarity with new data-driven technologies, but those wins aren’t yet translating to meaningful changes in digital goals.
What holds these CPG companies back? Well, there are telltale trends. In our experience, overcoming these five common hurdles helps clients make their marketers successful.
Hurdle #1: Investing primarily in engineers and data-driven specialists to drive transformation.
Naturally, your corporate transformation strategy requires engineers and data scientists to get your digital enterprise up and running. But a common mistake we see from CPG companies is focusing their investment in high-tech roles without upskilling the teams that connect to and support them. CPG companies need fluency across their organizations in order to create a coordinated go-to-market push, both across and within teams, that successfully implements modern techniques.
Hurdle #2: Relying on historical insights about your customer (and how a household brand embraced change).
Let’s say you’re a household name, and you have decades of experience in successfully reaching your target audience. So it makes sense to keep what’s not broken, right? Maybe not. Today’s consumers are demonstrating seriously rapid changes in consumer behavior, with the pandemic accelerating the shift to eCommerce in five years. That’s not to mention evolving gender norms, family life-cycles, increasing prevalence of DINKs, greater demand for sustainability and social responsibility, in addition to rapidly-accelerated digital platform usage. Today’s customer-centric strategy requires an ongoing connection with consumer trends and an openness to go against the “time-tested truths” of a traditional CPG.
One of our Fortune 100 CPG clients is known for its best-in-class brand management, which challenged GA to help it use digital techniques to improve its marketing function. This client invested in proficiency-focused bootcamps designed to build hands-on skills per digital channels for both practitioners and SMEs, giving marketing teams hands-on training in digital marketing specialties like eCommerce. Investing in modern, customer-centric marketing skills helped them to better deliver on strategic initiatives to compete with new “digital native” brands.
Hurdle #3: Under-leveraging data… and not generating insights.
A key piece of that customer-centric mindset requires generating ongoing data-driven insights about what your specific customers want and do. However, the best approach to data-driven marketing requires coordination across functions. For example, “Is my purchasing data demonstrating niche markets I can engage with tailored marketing messaging? Or, “What are the customer engagement channels that drive consumers to buy products in-store?”If the systems for tracking these datasets do not talk to each other, you miss out on opportunities to identify channels for improvement. A global children’s entertainment and toy company honed in on data-driven marketing as an area to improve their sophistication. Through GA’s “Data-Driven Marketer” workshop, they honed skills on optimizing digital spend by focusing on the highest ROI channels, reducing reliance on data teams by de-siloing access to data, and choosing the right KPIs for their goals, helping them interpret data and reveal insights for data-driven decisions more independently.
Hurdle #4: Overreliance on agencies.
A common issue among CPG clients is that they don’t have the in-house skills for key digital functions, like using MarTech, generating data-driven insights, or interpreting marketing analytics, so they outsource a bulk of their digital marketing to agencies. This leaves brands facing a “black box” in terms of what their agency partners are doing, without the skill set to collaborate deeply or specify strategic areas for partnership. This often results in brands not owning the data or strategies needed to close the loop and drive innovation. By building up capabilities and possibly taking some functions in-house, you can better own your customer journey.
For a global CPG master brand looking to reduce agency dependence, GA helped them build internal capabilities to improve collaboration. Through GA’s Getting the Most Out of Your Creative Partnerships workshop, the marketing team worked to increase their skill at using data to generate actionable customer insights, developing personas, charting their customer journey, and pitching creative briefs. By taking the drivers’ seat with these capabilities, CPG companies can have more leverage in making partnerships successful.
Hurdle #5: Underdevelopment of key functions.
Even as you build towards this closed-loop control, any weak link can pull down the opportunities for advancement in your marketing organization. What good are great customer-centric insights if you only get them from your agency at a single point in time, and you don’t have the tech infrastructure to maintain and update them? Or the MarTech knowledge to activate them and drive results?
This is where it is critical to not only have broad digital literacy and strong core marketing skills (like leading with customer insight and applying data-first marketing) but to invest in cutting-edge instruction of marketing specialties. Digital functions like eCommerce, SEO, and Content Marketing evolve at a rapid clip, and staying up-to-date on them is key to applying the future-proof skills that will take your team from skilled traditional marketers to fluent and innovative digital marketers.
That’s a wrap!
Getting over these five hurdles can be the difference between maintaining the status quo (despite your talent investment efforts) and seeing a noticeable improvement in your KPIs and bottom line. At GA, we specialize in helping CPG marketers make a deep, sustainable transformation in their marketing functions across insights, creative, channel activation, data usage, and marketing technology.
For more than a decade, business leaders have sounded alarms about the shortage of tech talent, often using language more appropriate for the battlefield than for the boardroom. The Bureau of Labor Statistics predicts that demand for tech jobs, like software developers and data-related roles, will continue to grow rapidly over the coming decade. And recent research suggests that tech hiring has continued to trend upward as the country makes its way out of the pandemic.
For business leaders, the need to understand the evolving role of tech skills in the labor market has, in some ways, taken on renewed urgency in the wake of COVID-19. Facing a rocky road to economic recovery, policymakers and employers are in search of new strategies to not just get Americans back to work but also ensure that the country’s workforce is prepared to navigate a volatile and increasingly tech-driven economic landscape. The events of the past year have also cast a harsh light on the pervasive and painful equity gaps that have always been endemic in American society — and sparked new efforts to create economic mobility paths for workers who face systemic barriers to advancement and opportunity.
Against that backdrop, the demand for tech skills continues to spread across a range of industries. It’s a shift that presents opportunities and questions: What fields are seeing the greatest increase in demand for technology skills, and how can the needs of those fields be met? How do the perspectives of enterprise tech and talent leaders align with and respond to shifts in demand? How can a better understanding of what’s happening now help us understand what may happen in the future?
But despite – or, perhaps, because of – all this attention, the actual term “digital skills” is not always clearly defined. And trying to pin down a more precise definition is not always a straightforward task. In fact, the most important question to answer may be a more fundamental one: what do we mean by “digital skills” in the first place, and how do those skills manifest in today’s complex and volatile labor market?
To begin to answer some of these questions, we joined forces with Emsi Burning Glass to develop the Digital Talent Forecast, which draws on our unique collective viewpoints and taps into the real-time talent and skill needs faced by both employers and geographic regions at this time of economic change. The report incorporates original research from Emsi Burning Glass, as well as insights from our standards board members, to shed light on the present challenges and opportunities facing a labor market that is increasingly defined by digital skills.
Get a sneak peek of our findings by having a beer with Emsi Burning Glass below:
In celebration of our 10-year anniversary, we’re highlighting some of our best people, partners, and instructors. Over the next few weeks, you’ll have the opportunity to be inspired by some incredible stories that have driven the success of our enterprise business.
Our current focus is being a tech-driven company, with making insurance more accessible as our mission.
So, what can that mean? For instance, it means offering to our partners BNP Paribas Cardif as a service or as a platform, with digital capabilities at its heart. And of course, it means providing our customers with the right solutions to reach their goals and supporting them through difficult situations. For instance, we developed an “employability ecosystem” with a local partner in Latin America, alongside our unemployment insurance.
GA: How does learning fit into all of these big transformation plans you have?
When we launched the program with GA, we knew we were the leading company in creditor insurance, but we didn’t want to take our place in the very challenging personal insurance market for granted. There are always new players coming in, so we wanted to have a culture of being a learning company. When I say a learning company, it includes having people learn new skills. This is what we did with the Skill Up program we built with GA. We set a goal to upskill and reskill more than 1,000 people between 2018 and 2022.
It was important to have an inclusive program to which all employees could apply. Applicants write a letter of motivation explaining why they’d like to take part in the upskilling or reskilling program.
As I said before, the ambition was to reskill and upskill 1,000 employees by the end of 2022. We are on track, having already trained more than 900 unique participants from all over the world, including Europe, Asia, and Latin America. An important part of this program’s ambition was to make sure it was truly international and build a strong universal vocabulary and skill sets across geographies.
Participants are from different areas throughout the business, including operations, finance, accounting, and marketing and communications.
Overall feedback was really good.
GA: What impact has this program had on your workforce?
That’s why we worked with General Assembly to create and deploy managers’ workshops. It’s a two-day training that explains why it’s important to be customer-focus, data-centric, and digital-ready.
Managing people is developing people, and once we demonstrated that we were giving them the tools to do just that, it was easier to get them on board.
GA: What advice do you have for leaders taking on digital transformation?
Investing in training programs puts your employees at the heart of your transformation. They need to know that this is a win-win situation: the staff gain new skills and the company has exactly the skills it needs.
GA: What excites you most about the future of work?
I have been working in the BNP Paribas Group for 20 years and have held many different positions. I’ve lived in various countries and worked with a lot of different people. I think it’s very exciting to be able to have such wide career path possibilities from companies.
Another thing that I find very exciting is that in the past, you were working in big corporations or you were an entrepreneur. Today, you can be working in a big corporation and be an entrepreneur. We have programs in our company for people who want to do entrepreneurial projects that are very interesting and nurture our entrepreneurial culture— this is key to staying agile.
So yes, while there can be some fear about the future because we are talking about tasks being automatized, it also brings lots of opportunities. Having the right mindset and tools to seize these opportunities is key. So, I’m quite optimistic about the future.
Stay tuned for more incredible stories from our team and partners in the coming weeks. Want to learn more about how GA can make a difference in your business today? Get in touch.
In celebration of our 10-year anniversary, we’re highlighting some of our best people, partners, and instructors. Over the next few weeks, you’ll have the opportunity to be inspired by some incredible stories that have driven the success of our enterprise business.
Keep reading to meet Kimberly Graham, who works as an AI transformation leader at Sage — one of our incredible clients. Over the past six months, Kimberly has partnered with us to upskill engineers on data and AI principles for transformation.
GA: Where are you located, and what is your role at Sage?
Kimberly Graham: I’m originally from Southern California, but I’m based out of Hayden, Idaho, about 100 miles from the Canadian border. I’m Director of AI Transformation for the Sage AI Labs team.
Sage is a leading accounting and business management software company with worldwide customers. Sage AI Labs is chartered with helping Sage become an AI-enabled organization. Our customers depend on Sage to manage their businesses. By enabling AI, we’ll help transform the customer experience and provide efficiency and insight gains.
My role as the director of AI transformation helps facilitate that process and develop a path forward with AI and machine learning. Upskilling our internal engineering resources is a big part of that.
GA: Why did you need a training partner? What was your goal?
Kimberly Graham: Sage AI Labs is a team of individuals with AI, machine learning, and infrastructure experience. We’re working with General Assembly to bring that skillset into the business outside of the Sage AI Labs team — within our product groups. By upskilling a subgroup of our engineers who don’t currently have AI and machine learning training, we can learn from GA and then work in concert with our more tenured AI and machine learning resources. The work that we’re doing with you leverages very current and effective GA training processes to upskill our engineers rather than tackling the upskilling externally.
GA: What made you decide to partner with General Assembly, and what has the experience been like?
Kimberly Graham: I was very picky when selecting a vendor and did a lot of due diligence since it’s such an important decision. When I found General Assembly, it was a natural fit. Working with the GA team feels like a partnership — and I sensed that immediately. We wanted to find a long-term partner to build out a customized training process; GA not only had a strong program but an outstanding reputation and excellent reviews. So, we wanted to start small with a pilot.
The initial pilot included a small group of participants so that we could work closely to understand the experience and content as they worked through the 10-week pilot program. It was very clear that General Assembly understood our mission, what we were looking for, and delivered on that.
Working with GA has been a true partnership. Communication has been very candid, very thorough, and regular — we initially met weekly to set expectations, hear best practices from GA, and provide feedback. What has impressed me the most is feeling like GA is an extension of our team rather than a vendor.
GA: You have been running your program throughout COVID-19. Can you tell me about your experience with live remote training?
Kimberly Graham: When COVID-19 hit, the entire Sage organization went remote. Luckily, the Sage AI Labs team is close to 100% remote anyway. Our team is dispersed worldwide. Therefore, while there were many impacts of the remote working situation due to the pandemic, the impact on our team was somewhat minimized.
One thing that has been wonderful with our first full cohort post-pilot is that we chose participants from Western North America and India. We included participants from Canada, Washington, Oregon, California, and India. It’s brought together engineers from different Sage product lines and engineering teams that wouldn’t have had the opportunity to work together otherwise. The feedback from our participants has been outstanding.
We wouldn’t have done an in-person course anyway due to our distributed team. So, the fact that General Assembly offered remote upskilling was beneficial, seamless, and very easy to roll out.
GA: Your first cohort is just about to end — congratulations! Have you seen any immediate impact or results through this training?
Kimberly Graham: One of the things that struck me the most during our initial pilot was midway through, just five weeks into the program when Sage hosted an engineering team hackathon. Two of our pilot participants teamed up and participated in recommending an AI feature for a Sage product based on what they had learned from General Assembly in the data science pilot. They won a prize in our hackathon, and five weeks later, they co-delivered the idea as their capstone project for the GA course.
Post-program, they went on to present it in various engineering meetings, an AI brown bag, and more. We’re currently in the process of building and implementing that feature into our product. These two developers were able to address a long-standing product challenge through AI and machine learning. This problem couldn’t have been solved with traditional programming — and that was just five weeks into our pilot program!
The participants from the full cohort will be delivering their capstone projects this evening, so our first cohort of 30 engineers is close to completion. I’m looking forward to seeing what they deliver and am really excited to see what they come up with! I’m also looking forward to continuing our partnership with the GA team to review the program and modify as needed, moving forward, as we expand with additional cohorts.
GA: How does Sage think about the post-program experience for participants?
Kimberly Graham: The sense of community that is created during the course, such as collaborating, sharing resources, projects, and tips in the Slack channel, is extremely important. I monitor those closely. It’s very collaborative.
I’ve picked up on the need for an ongoing community post-General Assembly upskilling since our participants have valued the collaboration and learning process so much. I’m in the process of working on creating an internal community so that our team members can continue to interact and learn from one another. We already have things such as a Yammer group that I’ve created for AI collaboration, but I want to take that a step further — that’s going to be key. It’s not just a matter of being educated, and then it’s done. It’s very important that our engineers continue to interact, experiment, and collaborate.
GA: When it comes to transformation, many organizations think about technology before people. It sounds like Sage has a different approach. Can you tell me about that?
Kimberly Graham: I moved over to the Sage AI Labs team a year and a half ago and came from a customer success and marketing background. Our team’s executive leader identified the need to have somebody from the business that didn’t have a technical background come in and understand what it takes to transform the business.
This is my first role as part of an engineering team, and I’m far from technical. Regardless of technology, we’re people who need to adopt technology to make our business work and be at the forefront of our customers’ needs. A big part of the transformation process is to look at things from our customers’ perspectives rather than just technology. One of the biggest elements of our transformation process is factoring in how we can use technology for the betterment of employees and our customers rather than just technology for technology’s sake.
Stay tuned for more incredible stories from our team and partners in the coming weeks. Want to learn more about how GA can make a difference in your business today? Get in touch.
Everything — including the way marketers used data — came to a halt when the pandemic hit. Given that all data builds upon the past, many companies found that what worked in 2019 suddenly became irrelevant in 2020 — a quick and jarring pivot.
The effectiveness of marketing is measured by the consumer behavior it’s designed to predict. What can marketers do to meet the challenge of consumer behaviors that have changed due to COVID-19 and wider shifts in cultural psychology?
Changes in consumer behavior necessitate changes in how we think about marketing strategy. This expert-driven webinar encouraged marketers to rethink their approach in three key ways:
1. Data doesn’t drive everything.
Marketing strategists have increasingly found themselves taking a back seat to big data. This is not to say that data-driven marketing strategies have no value, but COVID-19 caused many businesses to flounder as the data they relied on was no longer as informative and impactful as it had once been.
All told, what became expected consumer behavior morphed in a way that was not effectively predicted by marketing data; there was no precedent in the data most businesses were leveraging to address the psychological and emotional impact that a global pandemic would have on how consumers spend.
2. Marketing must be future-focused, not past-focused.
An ever-present consequence of data is that it’s reactive and not proactive. Ben Harrell sums this succinctly: “What worked yesterday won’t work today. What worked today won’t necessarily work tomorrow.” Never has that been more true in a post-COVID-19 era, when many consumers have altered not just how they shop, but why they shop and where they shop. Many are questioning whether they need a product at all and opting instead to purchase products or services that deliver deeper meaning or enhance their connections to other people.
Sutherland importantly notes that “People don’t buy what something is; they buy what it means”.
3. Engage relationally, not transactionally.
Marketers must keep pace with changing customer profiles. Consumers saturate the internet, but COVID-19 accelerated already prolific online activity. As Sutherland explained in an intriguing keynote speech, “Understanding consumers’ wants, needs, motivations, and fears has become much more important following COVID-19.”
This is hardly more visual than with Gen Z, which is distinctly digital-native and cause-driven. Marketing challenges change with every generation, and companies must adapt to how upcoming generations effectively respond to marketing, but Gen Z has proven to upend many cultural marketing expectations. It’s a generation that values an emotional, authentic approach and is quick to flee from companies too heavily focused on the traditional transactional method. If Gen Z is an indication of a longer-lasting trend, marketers really must be quick to adapt.
On to the next. And next…
As Salim Holder of 4th Avenue Marketing pointedly asks in the webinar, “Do we know our consumers as well as we think we do?” This question helps define big ideas you’ll experience in this engaging webinar filled with actionable insights from a panel of marketing experts. Watch the entire webinar here.
Want to learn more about how General Assembly can help you unlock marketing skills for a post-COVID era? Get in touch.
AI is a powerful tool that can help businesses achieve monumental success. For the last few years, AI has been inaccurately depicted as a tool that will steal jobs from humans. The media, movies, and more have consistently created a false image of AI, what the technology is capable of, and what it means for businesses and society. Truthfully, it’s the people behind AI that determine the outcomes of its use — not the technology itself.
Gonzague Dromard, our head of France, sat down with the co-founder of Siri and Renault chief scientific officer, Luc Julia, for a webinar discussion on demystifying AI and the big data that makes AI function. Here are the top three things we learned from that discussion.
Essentials To Know
AI is more than just a buzzword and less than the harbinger of the next tech-driven apocalypse. Instead, AI is a tool with the enormous potential to uplift industries and workers worldwide. Yes, this is daunting — but, no, this does not make AI dangerous.
1.AI’s Framework: It’s Older Than You Might Think
Although AI may seem to be a modern invention or trend, the groundwork has existed for decades. Artificial intelligence and big data are built around maximizing the efficiency of repetitive processes. Leaning into his new role at Renault, Julia highlighted how the car industry has been using automation for decades, starting in the 1960s with the introduction of industrial robots capable of simple tasks like spot welding. Lan Turing’s landmark paper “Computing Machinery and Intelligence” was published in 1950, giving us decades to properly define, create, and deploy early concepts of AI.
Although not as “smart” as some might expect, AI, at its fundamental level, is a repeatable set of rules that a machine follows — an instructional map, but certainly not the driver.
2. AI Does Not Destroy Jobs — It Accelerates Them in New Areas
Among the biggest questions that stymie wider acceptance of AI is whether the technology will replace human workers, destroying the livelihoods of millions of people. Dromard and Julia spent a significant portion of the webinar dismantling this misconception by underlining these AI truths:
There are multiple levels to artificial intelligence. If it becomes possible, we are far from a future where AI will completely replace human workers in most industries since AI relies on repetition — and the world at large is dynamic, not static.
Organizations must be proactive and introspective by identifying where efficiencies could exist and how AI can be used.
Companies thrive and innovate best when existing teams — with diverse backgrounds and experiences — are trained to use big data and AI.
When applied properly, AI creates entirely new industries and provides existing workers the chance to reskill while working alongside AI systems that make less enjoyable, routine tasks easier to accomplish. Since these tasks don’t change, the big data backing them can perform those tasks more quickly and efficiently than human workers.
3. AI Programmers Must Counter Personal Biases
News-making examples of bias within AI systems, such as facial recognition technology and hiring algorithms, have raised legitimate questions about whether AI will always be applied ethically. Dromard and Julia also took on this challenging question with strategies for how to ensure that the big data working in the background mitigates the risk of bias in AI systems:
“If we see that people can use it the wrong way, we have the responsibility to raise the flag. Data can be biased because the people designing and creating the data can be biased.”
As AI integrates more into daily life, data ethics has become imperative to ensure AI does not harm societal equity.
Take the Next Progressive Step With Big Data & AI
As Julia noted in our webinar, “AI is a tool. We have the hammer.” In other words, if you give that hammer to the right person, innovation will happen. Not all workers will know how to use the tool right away or in the right way, but dedicated and ongoing training can create lasting relevancy for businesses and build loyalty among workers.
Bottom line, people are only innovative if they’re trained with intention. When your teams bring their existing skills to the table — and merge that with newly acquired knowledge — real innovation happens. Watch the full webinar here.
Want to learn more about how GA can help you build a data-driven team? Get in touch.
In celebration of our 10-year anniversary, we are highlighting some of our best people, partners, and instructors. Over the next few weeks, you’ll have the opportunity to be inspired by some incredible stories that have driven the success of our enterprise business.
Keep reading to meet Steven Longstreet, one of our instructors, who teaches data to enterprise businesses to help them upskill and reskill their employees for the future of work and is a member of our AI and Data Science standards board.
GA: Where are you located, and what is your role at GA?
Steven Longstreet: I work out of the DC campus and live nearby in northern Virginia. I work as an instructor, and I am also a member of the AI and Data Science standards board.
I first discovered GA through a team member, an instructor for GA, who took the 10-week part-time data science course. She wasn’t confident with the content, so I decided to take it with her to support her. I had a blast, and then the GA team asked me to become a data science instructor.
It was fun to take this class and see how different people were learning and how the program broke down the barriers to data science.
GA: What is the instructor’s role in learning?
Steven Longstreet: People who sign up for our classes truly want to learn and better themselves. That’s actually one of the coolest things to be a part of. However, the reality is some of the things that we teach are complex, with barriers to learning. My role in learning is making these topics approachable and removing those barriers for each student’s personal journey.
When learning something new, you’re making yourself vulnerable. The instructor has to create an environment where it’s okay to be wrong. It’s my job to understand the student’s barriers and make sure they are okay to be vulnerable and ask questions.
GA: Why did you get involved in our AI and Data Science standards board?
Steven Longstreet: The whole purpose of the (AI and) Data Science standards board is that the term “data scientists” means absolute dribble. To some people, a data scientist needs to have a Ph.D., and there are other groups who just give out the title to anyone.
I’ve always struggled with this concept. Part of joining the board was coming together with a group of like-minded people and saying, “What is this term for us? What does it mean? What are the aspects of the new data scientists? What does a career look like? How can we best empower and leverage these people?”
The concept of a scientist is someone who pushes human understanding, and it doesn’t have to be something incredibly dramatic. It can be one microscopic new thing that you uncover that allows human advancement. A data scientist within the organization pushes the understanding of data in a more usable way. We set a clear definition that worked across the range of companies participating in the board.
The other jobs of the AI and Data Science standards board are explaining what a career in this field looks like and making it clear what fields someone can specialize in. We need to be clear about the roles and career path and delineate what these terms mean.
GA: What do you think the most critical data skills are — right now?
Steven Longstreet: Let’s break it into two parts: data engineering and data literacy.
I’ll start with data engineering because it’s part of your workflow. No matter what. Data needs to be built in the context of the problem you’re trying to solve. These skill sets are both rare and powerful, as a data engineer looks at the needs and resources across the organization to build core data assets with the most powerful and broad applicability. We’ve been talking about big data pretty heavily for about seven years, which can be summarized as more data than you have the resources, skills, or knowledge to wrangle. Maybe 5% of people feel comfortable working with big data, and those people jump into that challenge head-on.
Data literacy is understanding basic data concepts. When I talk about data literacy, I want people to articulate the problem they are trying to solve. Are they trying to forecast something or classify something? It’s about understanding data isn’t perfect and has biases. We build data for a particular context, so you can take the same raw materials and build a pick-up truck or a car, depending on what you’re trying to do with it. In other words, you have to understand why you built your data in the first place.
It’s about knowing what’s possible with data in your field, asking the right questions, and effectively communicating with data people to get the answers.
GA: What advice do you have for leaders who are trying to prepare for the future of work?
Steven Longstreet: You have to listen to your team, but you also have to recognize that there’s a problem you’re trying to solve. I’m in an industry where people are serving people. Most of my employees are in front of people, but for the last year, we’ve all been working from home.
The future of work at my company, Hilton, isn’t changing from the face-to-face experience, but we’re listening to our team and realizing many people want flexibility. We are thinking of new ways to bring people together because there are aspects of work that you can’t replicate virtually.
I think the future of work doesn’t change the fact that human interaction is incredibly important to advance any problem. If one person could work entirely in a vacuum, we wouldn’t talk about Tesla and SpaceX; we’d only talk about Elon Musk. The reality is that a lot of people make work happen; one person rarely solves all the problems by themselves.
Stay tuned for more incredible stories from our team and partners in the coming weeks. Want to learn more about how GA can make a difference in your business today? Get in touch.
As companies across industries race to digitize, maintaining the pace of change required to get across the finish line can be overwhelming — especially for those leading the digital transformation efforts.
We’re here to break it down.
Through our deep experience across many types of organizations, we’ve seen leaders’ transformation challenges boil down to four key goals:
Create digital mindsets across the company. This includes understanding digital trends, growing digital mastery, and building a product-driven organization.
Upgrade capabilities to reflect cutting-edge technical skills across marketing, technology, and data functions.
Accelerate technical hiring by upskilling and reskilling current employees and new hires.
Understand what good looks like — a skill necessary in achieving every goal.
This series, Jobs To Be Done, unpacks each of these four goals, providing actionable recommendations that organizations can put into practice to help set their businesses on the path to sustainable digitization and success.
Finally, we’ve come to our final overarching concept: understanding what good looks like. Whether you’re evaluating a digital culture, growing capabilities, or filling talent gaps, it’s hard to know how you’re doing without clear benchmarks. We have some tips.
Defining Success in Uncharted Waters
Congratulations: you’ve bravely inspired your organization to try new things, creating a company with a more agile, empowered workforce, building on the latest cutting-edge technologies and best practices… But what are the details of those practices? Once you’re deep in uncharted territory, how do you know when you’ve truly succeeded?
It can be difficult to specify what good looks like — especially when the fast-paced nature of digitization often means the goal line keeps moving as you work toward it. A lot of business leaders are largely unfamiliar with the technicalities of digital fields, especially when it comes to the details of the many roles they oversee. This makes it challenging to do simple tasks like mapping out leveling frameworks or evaluating talent.
When it comes to knowing what good looks like, getting an outside perspective can help you chart your way. One of the most helpful, multipurpose tools you can bring into your process is a well-built, quantitative assessment.
The Gold Standard: Map Success Against Data-Forward Assessments
Data-forward assessments that measure adeptness in key skills are tools you can use throughout your digital transformation. They give precise, repeatable data to track over time and leverage in decision-making.
There are several touchpoints across your workforce pipeline where an assessment can be a big help in defining good — from analyzing candidates in interviews to tracking progress in your reskilling efforts.
We recommend assessments to help companies improve many areas, such as:
Identify unique skills gaps in existing teams to develop your learning goals. Once you understand the specific areas your team needs to grow, the data will point you in the right direction for your transformation. You can even leverage them to prescribe personalized learning paths that target the specific strengths and areas for growth of each team member, which can be more tailored and effective than a one-size-fits-all approach.
Benchmark the skills your teams have compared to the industry. With a broadly-used assessment, you not only understand your team’s skills but also how their scores relate to others in your field, allowing you to align your skilling investments with your strategic goals.
Track improvement of skills over time. Multiple data touchpoints help you learn where you’re making progress and where a new approach may be needed — a key element of an agile workforce. You can also use this data to inform performance reviews, as your top performers set tangible goals and achieve them.
Guide hiring and staffing decisions. Adding quantitative assessments to your interview processes help remove bias from candidate evaluations and allows you to compare internal and external candidates on a level playing field. In addition, they can identify surprising aptitudes or highlight areas where more evaluation is necessary.
Over the last few months, we’ve talked about the top challenges we encounter from leaders of digital transformation efforts. Whether you are beginning to build the broad digital fluency that is a foundation of digital culture — investing in the technical skills upgrade of your teams and expanding top talent, we hope you found valuable tips within these series to help guide your way.
If you’d like to explore the range of courses that GA provides (and get a sense of how your teams stack up to the skills we teach), you can explore our catalog here, which covers roles from IC to strategic leader across digital fluency, marketing, data, and technology.
Want to get specific about how GA could help your organization? Get in touch.
This concludes our Jobs To Be Done series. We wish you luck on your digital transformation journey!
