AI promises to be a transformative force across many industries, offering immense potential for innovation and growth. However, successfully scaling AI deployments will only be possible if we overcome a major hurdle: Building trust in AI.

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We can attribute many answers to the WHY that fueled the great recalibration, but during that time one central truth started to prevail:

The employee experience could no longer be an afterthought — second, at far too many companies, to the customer experience.

Prior to 2020, the era of customer centricity was at an all-time high. Brands would proudly boast that they were customer-first. Sizeable investments were poured into creating game-changing products, services, and offerings that would WOW customers. Town hall meetings dominated around revenue metrics, Net Promoter Scores, client acquisition costs… the list goes on… sending a signal to employees that the customer was the north star.

But 2020 and the Great Resignation did something to business. With the employees suddenly holding huge power — in terms of if they would stay, or if they would go — the concept of “experience” expanded considerably. Because having a solid approach to customer experience (CX) was no longer enough.

Enter total experience

At the end of 2020, Gartner pushed the envelope forward on the concept of rethinking experience by introducing a new term to the market: “total experience.” Listed among its top 10 strategic technology trend predictions for 2021, Gartner described total experience (TX) as:

“A strategy that connects multi experience with customer, employee and user experience disciplines, Gartner expects organizations that provide a TX to outperform competitors across key satisfaction metrics over the next three years… TX strives to improve the experiences of multiple constituents to achieve a transformed business outcome. These intersected experiences are key moments for businesses recovering from the pandemic that are looking to achieve differentiation via capitalizing on new experiential disruptors.”

Suddenly, companies across the globe were thinking “total,” ensuring they were taking steps forward to equally prioritize, shape, and invest in experiences across employees, customers, shareholders, users and so on.

The concept of TX changed business conversation forever. Instead of companies focusing on being superior at just one experience pillar — e.g. customer experience — pressure mounted for them to master all. Because the Future of Work model in which we were all thrust into made one thing super clear…

If even one of your experience pillars was at risk, the whole of your organization was at risk.

3 Ways to jump-start total experience

Though the term TX might still be fairly new, the concept of winning at the experience game dates back almost 30 years ago.

Coined in a 1998 Harvard Business Review article, “Welcome to the Experience Economy,” the “experience economy” described mounting pressure companies faced to differentiate their approach, as “the next competitive battleground lies in staging experiences.”

But in 2024, the fight to win the experience economy has never been greater.

Experience has become disruptive, personalized, and customized. Individuals expect the same level of experience across all brands — from tailored messaging to robust self-service options to AI-powered recommendations. And macro trends continue to support a move to TX, or a fresh, holistic approach to standardizing and holistically thinking about experience.

So how can you jump-start your TX initiatives? Let’s dive into 3 tips to get started:

• Unlock your why: Just as any initiative needs a north star, total experience needs a compelling reason to get ignited. Consider your organization, team, or department for a moment and reflect on where you think your experience journey might be at risk or falling behind. If you lead a Product team, for example, are you equally prioritizing the experience of your existing users, as well as the desires of future users you need to acquire? If you lead HR/People, have you unintentionally spent more time creating a WOW existing employee experience, but your candidate experience is lagging and precluding you from hiring top talent? Understanding your current state and what is motivating your total experience approach is the first step in building out your strategy.
• Data as your compass: With your why clear, it’s time to put your data to work and leverage it as a compass as to where you’ve been, where you want to head and how you will ultimately measure TX impact. Instead of worrying too much about the data you have available today, consider answering this question as if you had no barriers: What new KPIs should we stand up and track either org-wide or within our department so that we can gain a more multi-dimensional approach on how our stakeholders feel about the experiences we’re creating? Think of what you want to measure, versus what you feel you can measure. Dream! Challenge yourself to think disruptively. And remember that a shift to TX requires an adjustment in terms of how you think about using data.
• Technology as the accelerator: As you zero in on your TX WHY and lean on data to set the direction, now comes the exciting part: introduce emerging technologies to accelerate momentum. When you blend together disruptive technologies with human ingenuity, your ability to create memorable, WOW experiences across your stakeholder base soars. One tech accelerator to fast-track? Artificial intelligence. AI can support everything from new-age customer satisfaction scoring methodologies to predictive new feature demands to optimizing day-to-day workflow processes, allowing you to compete in the experience game like never before

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It sounds so easy! As a chief executive, I would be reading this stuff and thinking to myself, ‘Why the hell aren’t my people doing this already?’.

In fact, I am hearing from digital and technology practitioners in councils all over the country saying that this is happening. That the AI hype is putting pressure on teams to start delivering on some of these promises, and to do so quickly. I find this troubling.

It’s always worth referring to my 5 statements of the bleedin’ obvious when it comes to technology in organisations:

1. If something sounds like a silver bullet, it probably isn’t one
2. You can’t build new things on shaky, or non-existent, foundations
3. There are no short cuts through taking the time to properly learn, understand and plan
4. There’s no such thing as a free lunch – investment is always necessary at some point and it’s always best to spend sooner, thoughtfully, rather than later, in a panic
5. Don’t go big early in terms of your expectations: start small, learn what works and scale up from that

How does this apply to using AI in public services? Here’s my take on the whole thing. Feel free to share it with people in your organisation, especially if you think they may have been spending a little too long at the Kool Aid tap:

• The various technologies referred to as ‘AI’ have huge potential, but nobody really understand what that looks like right now
• Almost all the actual, working use cases at the moment are neat productivity hacks, that make life mostly easier but don’t deliver substantial change or indeed benefits
• Before we can come close to understanding how these technologies can be used at scale, we need to experiment and innovate in small, controlled trials and learn from what works and what doesn’t
• Taking the use of these technologies outside of handy productivity hacks and into the genuinely transformative change arena will involve a hell of a lot of housekeeping to be done first: accessing and cleaning up data, being a big one. Ensuring other sources for the technology to learn from is of sufficient quality (such as web page content, etc) is another. Bringing enough people up to the level of confidence and capability needed to execute this work at scale, for three – and there’s a lot more.
• The environmental impact of these technologies is huge, and many organisations going ham on AI also happen to have declared climate emergencies! How is that square being circled? (Spoiler – it isn’t.)
• The choice of AI technology partner is incredibly important and significant market testing will be required before operating at scale. There’s an easy option on the market that is picking up a lot of traction right now, because it’s just there. This is not a good reason to use a certain technology provider. Organisations must be very wary of becoming addicted to a service that could see prices rocket overnight. More importantly perhaps is whether you can trust a supplier, or those that supply bits of tech to them, to always do the right thing with your data. There’s always going to be an element of risk here: but at least identify it, and manage it.
• Lastly, the quality of the outputs of these things cannot be taken on trust, and have to be checked for bias, inaccuracies and general standards. Organisations need to have an approach to ensuring checks and balances are in place, otherwise all manner of risks come into play, from the embarrassing to the potentially life-threatening.

This ended up being a lot longer than I first imagined. But I guess that just shows that this is a complex topics with a whole host of things that need to be considered.

Just remember – any messages you see claiming that AI is a technology that takes hard work away for minimal investment or effort, is at best just guesswork and at worst an outright lie.

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In the organisations we are advising about AI adopting these tools is leading staff to ask a host of other questions. Do we have the right governance? Is our data ready, and secure enough, to be used by AI tools? Will our culture help or hinder how we adopt AI? 

AI and how it is changing organisations is on my mind at the moment. We are gathering data about how charities are adopting AI as part of the survey to build this year’s Charity Digital Skills Report. We want to hear from more charities how they’re using AI, how they are learning about it and whether there are any barriers they face in adopting it further, so we can make the case to funders and sector decision makers about the resources and support they need. 

What I’m observing in my day job, and am excited about gathering data on as part of our survey, is the ripple effect that AI is creating in organisations, beyond the tools. The organisations who I see making progress with AI are the ones who are looking at how they can make changes in areas from skills to leadership to strategy, in order to make the most of AI. 

How are organisations using AI? 

Organisations such as banks and energy suppliers have been using AI as part of their services for some time. What’s been exciting over the last year is seeing how charities are beginning to incorporate AI into their service delivery, meaning that it can help them increase their impact. 

Citizens Advice Stockport, Oldham, Rochdale and Trafford are using AI to manage the demands they are facing due to the cost of living crisis. AI tools means that they can help their advisers get the information they need quickly and easily, and support more individuals. 

Stuart Pearson, their Head of Innovation, says, “We created an AI advice-service “co-pilot” tool powered by LLM and RAG technology. This tool assists advisors by rapidly locating and sharing pertinent data from dependable sources like GOV.UK and Citizens Advice resources.

This tool has accelerated response times, resulting in quicker assistance for callers. It has also facilitated faster training for new advisors, empowering them to provide accurate answers promptly.”

These developments have led Stuart and his team to collaborate with Citizens Advice and the Incubator for Al to refine their prototype and develop their tool Caddy, which will be tested as part of a wider pilot phase in many local Citizens Advice offices this month. 

Over at the charity Dementia UK, Victoria Lyons, their Head of Digital and Dementia at Work, has been exploring new ways to use AI. Her organisation is now on the second phase of this work. Lyons explains, “We have plans to develop our use of AI in the coming year and I am looking at a number of tools that will allow us to provide our unique support to families that need our help in an efficient digitally agile way.

Some of this is providing staff with useful tools to speed up some of the parts of their jobs.Some of this work may also be about creating externally facing resources powered by or using AI.” 

How are organisations changing in response to AI? 

It is impossible for organisations to make the most of AI without growing skills.  Victoria Lyons and her team at Dementia UK  have invested in this area. “All staff have been given the opportunity to attend drop-in sessions with myself and another colleague, “she says. “At these sessions we highlighted some of the uses of AI and the issues and risks with AI as well as showed people how to use Ai to support them with their work. We taught  people how to write a prompt and got people interacting with Co-pilot in real time as part of these sessions.”

Whilst offering staff skills development and guidance is vital. AI is also forcing organisations to consider their ways of working. Pearson’s team at Citizens Advice Stockport, Oldham, Rochdale and Trafford committed to working transparently through the design, development, and implementation process for Caddy, and has also prompted a collaboration with Citizens Advice Manchester to establish an Innovation Hub. The hub will help their organisations pilot more ways to use Caddy together. 

Yet one of the most important lessons to emerge from this process is how important it is to adopt AI responsibly. Pearson says,”we have approached this work with the unwavering belief that doing so in an ethical and responsible manner is non-negotiable. Therefore, transparency, accountability, and security have been the core principles guiding our development. To ensure this, we have begun developing an ethical framework for AI for the organisation, it will focus not just on development but also procurement rules.” In addition, Pearson’s team will be beefing up their existing governance with an AI oversight group. 

What should organisations do next? 

The pace of change that we are already seeing in AI indicates that we could see a lot of things happen quickly. That’s why it’s so important to develop a robust approach to issues such as data security now rather than later. Richard Seiersen, Chief Risk Technology Officer at Qualys, a company focused on cloud security and compliance solutions, warns that, “we are at the start of building AI projects. We can try to make those projects secure by default through collaboration, or we can try to implement security later, at additional cost and in longer timeframes to deliver. I know which approach I would rather be part of, both for the security team and for the AI side as well.”  He encourages organisations to make following best practices around security when working with developers part of how success is measured. 

This points to how critical humans are to successful adoption of AI- for now. Pearson points out that AI is not a substitute for people, and this needs to be signaled loud and clear through your ways of working. “Organisations should prioritise this collaborative approach to maximise the benefits of AI. Involve all your teams in the discussions, everyone is going to need to understand and navigate this new AI powered future,” he advises. 

AI will create wholesale changes in how we live and work. We are only at the start of this journey. Getting to grips with these tools can feel daunting, as can thinking how your organisations might have to change course to accommodate their successful adoption. Yet this is an opportunity. It’s a chance to consider why and how your organisation does what it does- and whether this needs to change so you can keep adding value in an age of rapid technological advancement. 

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These modern trains will have received a warm reception from travellers, especially in regions where outdated models have been in service for long periods of time. But despite some benefits being seen, operators are failing to harness the full capabilities of these new vehicles, constraining them from delivering the best services possible.

Utilising untapped data

The modernised trains that are being introduced onto our rail networks capture a wide range of data, a lot of which isn’t being used to its full potential. They are equipped with a range of technologies, such as Internet of Things (IoT) sensors that monitor various parts of the trains and rail infrastructure, from counting passenger numbers in carriages, through to heat sensors which check track and break temperature to make sure they are at safe levels. 

If these data sets are effectively leveraged, they can deliver substantial benefits to rail operators to passengers. Building on our previous examples, the ability to gather information about passenger travel patterns through IoT sensors gives operators the ability to optimise the allocation of their train fleets, ensuring services have capacity and meet passenger needs.

Simultaneously, scrutinising track and brake temperatures in real-time presents a significant opportunity to reduce maintenance costs. By being able to immediately and proactively resolve issues before issues escalate, operators can prevent potential disruptions that might mean trains or railways need to be taken offline. 

Embracing digital expertise and training

Not all providers are unaware of the valuable data their trains gather and many do want to use it to improve their services. But they face challenges in doing so. The main problem is that they lack the tools and abilities to collect and analyse specific insights from their data and then make decisions based on what they find. This is largely because having access to large datasets is new to the industry.

If operators want to use their data to make services better, they need help. They need to be working with data experts who can help effectively capture the vast swathes of information they collect. These digital partners can create and implement solutions, such as AI analytic tools, that allow operators to easily gather and study their data, while at the same time use the findings to make smart decisions about their services.

While partnering with outside experts to implement data solutions like artificial intelligence can be beneficial, it’s not the only requirement for rail providers. Operators also need to be focussing on training and educating their staff, working with digital experts who can upskill staff to effectively understand and harness data. This way, they can ensure that employees have the necessary skills to make the most of datasets and make informed decisions from this information.

The upgrades and incorporation of new trains onto UK rail networks has already enhanced services and are expected to keep doing so. However, it’s essential for operators not to overlook the significant untapped potential within the data gathered by these trains to further enhance services. Through collaboration with experts capable of harnessing this potential, operators can develop more efficient and cost-effective rail services that benefit all stakeholders.

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Two months ago, I did something that both exhilarated and terrified me by signing up and attending a half-day financial training workshop called, “Understanding Financial Statements for the Non-Financial Executive.” A workshop all about understanding core finance and accounting concepts, learning how to read financial statements, and being able to pinpoint financial statement nuances among different industries/verticals.

As a total right-brainer — and someone who sees the world through a sea of words, idioms, grammar, and stories — this was intimidating work for me. But I’ve long believed that as leaders we need to get ahead of things that scare and excite us and commit to owning our accelerated understanding in that focus area… versus waiting for someone to ask us to take action in that area and then feeling like it’s a race to catch up.

Now I’ll be honest. The course was hard! I mean really hard! It no doubt brought me back to my high school math days, along with those dreaded teenage feelings that I might never learn how to crack calculus.

But it was also incredibly empowering and motivating to remember that we are always one decision away from shifting our understanding from “not knowing” to “foundational” to dare I say eventually “strategic” in terms of our comprehension and application!

The business world continually throws pressure at us as leaders to understand and to shift from foundational to strategic, particularly when it comes to megatrends, macro shifts, and emerging technologies. Just consider the pace of adoption when it comes to innovation as a reminder of how important it is for us to keep up. What is nascent and disruptive one day — think cloud, VoIP, AI, IoT — becomes ubiquitous and even commonplace seemingly days later. The risk of falling behind has never been greater, as the window to be among the Early Adopters is ever-shrinking, while the consequence of falling into the late laggard group has never been so steep.

This pressure to keep up is perhaps no more felt than when we consider the impact of data and advanced analytics in business. Let’s dive in a bit further.

The race to keep up

It seems like only years ago that terms like “big data,” “artificial intelligence,” and “data science” were first becoming prevalent… often conjuring up images of overwhelming Excel spreadsheets, robots, and mathematicians running algorithms at cubicles.

But today, you’d be hard-pressed to find any leader who isn’t thinking about things like…

• Is my department data-backed or gut-based when it comes to decision-making?
• Are we measuring the right things?
• Does our data tell a positive story of our impact on the business?
• Is our data trustworthy, accessible, and leverageable?
• What impact will AI/ML have on my role/my team?
• Is my boss expecting me/my team to do more with data?
• Am I keeping up the way my fellow peer leaders are when it comes to analytics adoption?

In many ways, when it comes to data and advanced analytics, it’s not enough to just have a foundational understanding. All leaders are expected to be data-confident — leveraging data and analytics daily to power their teams, decisions, and focus areas.

Regardless of what you lead — Data, People/HR, Marketing, Sales, etc. — you can always supercharge your team/function’s efforts around data. Here are 3 ways to immediately propel your data maturity further:

• Set intentional vision: What do you want to use data for? And more importantly, WHY? Set bold vision for what data needs to do for your department (think business goals versus using data to report on what happened). For leaders of People/Culture, that might mean unearthing correlations that allow you to predict at-risk employees well before they quit (more on that here). For Marketing leaders that might mean illuminating dark data around voice of customer to land on your next best product offering. For leaders of Data, it might be helping the organization unlock hidden revenue opportunities via efficiency plays. Align your data vision to the overarching corporate strategy and think of the questions you most need to answer with data.
• Quick wins: In addition to focusing on your long-term data vision, consider what quick wins you can have with data. Things like: unearthing correlations and new patterns from the data you already have, standing up artificial intelligence proofs of concept, remedying quality and integration issues, unlocking new growth opportunities, and so on. Consider what data you already have that you can harness, as well as what new data you can create instantly. These quick wins are a great way to build data momentum and buy-in for how you’re approaching your data leadership.
• KPIs for today and for tomorrow: One of the best ways to supercharge your data efforts? Consider what you need to measure for today, as well as what you need to measure for tomorrow. Start with the tried-and-true KPIs (employee retention, marketing qualified leads, YoY growth, sales pipeline, etc.) and ensure that not only do you have KPIs stood up, but that you are analyzing the data you’re collecting via dashboards and visualizations. Once you’ve nailed the tried-and-true KPIs, consider what you need to measure for tomorrow. One of the ways we help our clients think about this is by asking them, “What do you want to measure that feels immeasurable?” By removing the constraints of what “feels” measurable, as well as what data you believe you do or do not have, the real creativity unlocks in terms of what you actually wish to measure next.

Our ability to shift from foundational to impactful is always within reach, particularly when it comes to business imperatives for today and tomorrow. In the world of data, what move do you want to make next?

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By harnessing the power of technology, companies will not only increase revenue, but also achieve significant cost savings.

Here, I highlight 5 ways companies without a digital transformation strategy are losing money. And I’ll also give you 7 key ways digital transformation can (and will) save you money and increase your profits. 

5 ways your company is losing money by not having a digital transformation strategy

Missed market opportunities

Companies without a digital transformation strategy risk missing out on emerging market trends and opportunities. In an increasingly tech-driven world, failing to adopt digital capabilities can result in losing market share, revenue, and profitability to agile competitors who successfully implement digital strategies. 

Inefficiencies and higher operational costs

Traditional manual processes can be time-consuming, error-prone, and resource-intensive. Companies without digital transformation strategies often face operational inefficiencies and higher costs associated with manual labour, redundant paperwork, and outdated systems. This leads to decreased productivity, increased expenses, and reduced profit margins. 

Limited customer engagement and reduced loyalty

In today’s digital arena, customers expect seamless interactions and responsive, highly personalised experiences. Companies lacking digital strategies may struggle to engage customers effectively and deliver tailored solutions. This can result in lower customer satisfaction, reduced loyalty, and ultimately, loss of revenue.

Ineffective marketing and sales tactics

Without digital transformation, companies may rely on outdated marketing and sales tactics that fail to reach today’s savvy consumers. With the rise of social media, online advertising, and influencer marketing, digital channels offer unparalleled opportunities to engage with potential customers. Failure to leverage these channels can lead to ineffective marketing campaigns, reduced customer acquisition, and decreased sales.

Vulnerability to disruption and cybersecurity risks

Technological disruptions are reshaping industries at an unprecedented pace. Without a digital transformation strategy, companies risk becoming obsolete as competitors embrace innovative technologies. Additionally, the absence of robust cybersecurity measures can leave businesses vulnerable to data breaches, resulting in financial losses, reputational damage, and costly legal ramifications.

Leveraging new technology and digital solutions

By leveraging new technology and appropriate digital solutions, your company is guaranteed a more competitive edge in the marketplace. This strategy allows C-suite leaders to replace outdated legacy systems, foster innovation, optimise internal resources, and enhance and expedite processes. Business transformations aim to enhance overall performance by driving revenue growth, reducing operational expenses, and improving customer satisfaction and workforce productivity.

Creating a culture that fosters continuous learning and embraces emerging technology is crucial for companies to leverage their abundant resource: people. This approach enables leaders and employees to explore new possibilities in technology, customer experience, business models, and supply chains, providing companies with a significant advantage in the tech-driven market. 

7 ways digital transformation can make your company more profitable

Expanding market reach through online platforms

Digital transformation allows businesses to extend their market reach by establishing a strong online presence. By leveraging digital platforms and e-commerce capabilities, companies can tap into global markets and attract a broader customer base. The ability to sell products and services online opens up new revenue streams and maximises profit potential.

Happier employees

Digital skills extend beyond just your marketing or IT departments. People play a critical role in driving digital transformation. A business culture that prioritises enhancing digital skill sets across all departments not only contributes to digital maturity but also signifies the value placed on employees. It is essential to acknowledge that digital technologies are constantly evolving, making upskilling an ongoing process rather than a one-time goal. Continuous investment in developing skills required to leverage the ever-changing digital landscape should be ingrained throughout the entire organisation. By investing in your workforce, the resulting improvements in their knowledge and credibility will be recognised and appreciated by your customers.

Enhancing customer experience

Investing in digital technologies enables companies to provide personalised and seamless customer experiences. Through data analytics and AI-driven insights, businesses can understand customer preferences, anticipate needs, and deliver tailored offerings. By delivering exceptional customer experiences, companies can drive customer loyalty, repeat business, and ultimately increase sales and revenue.

Capitalising on data-driven decision making

Digital transformation empowers organisations with robust data analytics and business intelligence capabilities. Analysing data helps identify market trends, customer behaviour patterns, and emerging opportunities. By making data-driven decisions, companies can optimise operations, target specific customer segments, launch innovative products, create targeted advertisements, and forge strategic partnerships based on data collaboration. This improves overall business performance, resulting in higher revenue generation.

Automation and streamlining operations

Digital technologies such as robotics process automation (RPA) and artificial intelligence (AI) can streamline repetitive and time-consuming tasks. By automating core processes, companies can achieve operational efficiency, reduce human error, and free up resources for more value-added activities. This increased productivity can lead to cost savings and improved profitability.

Monetising data assets

Digital transformation enables organisations to capitalise on the value of data assets. By carefully analysing and monetising customer data through analytics, companies can develop new revenue streams. This can include offering data-driven insights, creating targeted advertisements, or forging strategic partnerships based on data collaboration. 

New revenue streams

Digital transformation goes beyond the enhancement of sales funnels to revolutionise the way businesses operate, unlocking innovation in products and services. By harnessing technologies such as big data analytics, AI, machine learning, blockchain, and the Internet of Things, businesses gain the power to track trends, seize opportunities, and swiftly launch new streams of revenue online. Additionally, this transformation enables businesses to expand into new markets by offering their products on various platforms and channels, reaching a larger audience and making informed decisions with improved efficiency.

In conclusion, by expanding market reach, enhancing customer experience, leveraging data-driven decision making, automating operations, and monetising data assets, businesses can significantly boost their revenue streams. I believe that creating a culture that fosters continuous learning and embraces emerging technology is crucial for companies to leverage their abundant resource: people. This approach enables leaders and employees to explore new possibilities in technology, customer experience, business models, and supply chains, providing companies with a significant advantage in the tech-driven market. 

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A strategy, in essence, embodies a commitment to a cohesive set of policies or behaviours aimed at achieving a specific competitive goal. Effective strategies foster alignment among diverse groups within an org, providing clarity of objectives and priorities while channelling efforts towards them. Companies often define their overall business strategy, outlining their scope and positioning, along with how various functions like marketing, operations, finance, and R&D support it. However, at Whitespace we’ve observed a lack of strategies explicitly designed to align innovation efforts with broader business goals. 

In the absence of a dedicated innovation strategy, attempts to improve innovation can become a haphazard collection of widely touted best practices. Decentralising R&D into autonomous teams, nurturing internal entrepreneurial ventures, establishing corporate venture-capital arms, pursuing external alliances, embracing open innovation and crowdsourcing, engaging with customers, and implementing rapid prototyping are just a few examples. 

While these practices are not inherently flawed, the real challenge arises from understanding that an organisation’s capacity for innovation is intricately woven into an innovation system—a coherent set of interdependent processes and structures that dictate how the company explores novel problems and solutions to transform ideas into viable business concepts and product designs and selects which projects to fund. 

Each individual best practice involves trade-offs, and adopting any specific approach necessitates complementary changes throughout the entire innovation system. A company lacking an innovation strategy struggles to make these critical trade-off decisions and fails to harmonise all the elements within the innovation system effectively. As a result, the pursuit of innovation becomes a disjointed and frustrating endeavour. 

To break free from the shackles of stagnant innovation, companies must recognise the indispensable role of an innovation strategy. A well-crafted strategy not only brings coherence to the innovation system but also helps in making informed decisions regarding which practices to embrace. By aligning innovation efforts with the broader business strategy, organisations can pave the way for a more purposeful and successful journey towards innovation excellence. With an innovation strategy at its core, a company can harness the full potential of its creative capabilities and create a resilient foundation for sustainable growth and competitiveness in an ever-evolving marketplace.

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Onshore development

Onshore development refers to the practice of developing software locally, using skilled IT professionals or development companies. This approach is the most traditional model, and it has been used for decades. The benefits of onshore development include better communication, proximity, cultural alignment, and the ability to work in the same time zone. Additionally, onshore development is an excellent choice for projects that require a high level of collaboration, input from stakeholders, and a fast turnaround. This however can be a more expensive option, sometimes having an onshore team can mean higher day-rate or recruitment costs, employment legislation to navigate, or when using an outsourcing service it may not always be possible to fix the scope or budget for the development work.

Offshore development

Offshore development refers to hiring an external development team in a different country. The benefits of offshore development include lower labour costs, access to a broader range of talent, and the ability to take advantage of different time zones. However, offshore development has its challenges, such as communication barriers, time zone differences, cultural differences, and language barriers. With offshore development, you need to understand that the quality of work might differ, due to geographic and cultural differences. Offshore development is often a more cost effective model to onshore development as many providers are able to utilise local market rates across their development pool. They’re also likely to have built efficiencies of scale as well as the ability to recruit from a more global market, often passing on the cost efficiencies to the end client.

Hybrid development

Hybrid development combines onshore and offshore development by leveraging resources from both local and overseas teams. By decoding when to use either their existing workforce or an onshore lead, project leads can create an approach that combines the best of both worlds. Here, the benefits of onshore development include better communication, proximity, cultural alignment, and the ability to work in the same time zone. Meanwhile, offshore development provides access to a broader range of talents and lower costs. Here the programme manager would be the best position to consider and allocate the right resources from both team. Here at Reed Professional Services, we have been able to utilise this approach to deliver some award winning household brand name digital products and services. Our trusted talent network can augment teams from both international and local markets to create tailored teams.

Choosing between onshore development, offshore development, or a hybrid approach depends on several factors such as expertise, timeframe, budget, and logistics. Deciding on the right development approach for your business is a critical decision that warrants careful consideration and analysis. By understanding the characteristics, advantages, and disadvantages of each development model, you can plan and assess which model would work best for your unique needs. With customised services such as those offered by Reed Professional Services, you have the freedom to select the best options for your company that offers the most substantial ROI for the best value and creates a team that deliver against your projects.

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Public and mass layoffs

Ongoing market volatility

Remote vs. in-office debates

Shrinking budgets and head count

Increased pressure to create companies, brands, products, and services that cut through the noise

Culture is something that has always been susceptible to macro forces like the ones listed above, but perhaps it has never felt more at risk when we also consider things like…

• The surge of quiet quitting, and the fact that 96% of workers are looking for a new job in 2023 (Monster)
• Employee engagement declined for the first time in a decade. In 2022, only 32% of full- and part-time employees are now engaged. 18% are actively disengaged (Gallup)
• Three in four employees are looking for a more supportive work culture to motivate them to stay in their current role (Adobe)

These stats underscore an important point. CEOs, heads of People and departmental leaders need to not only build unbreakable, remarkable cultures. They also need to understand the stages of culture they are in at any given moment of time based on what’s happening at the macro as well as right inside their four “walls.”

Let’s unpack this further…

Culture lifecycle stages

At team, department, and organization levels, businesses go through what we like to refer to at SQA Group as Resurgence Cycles that are triggered by macro and internal shifts. At the highest level, we categorize the phases of culture as:

Build Back: A period marked by pervasive volatility, uncertainty, fear, and risk that may be piquing as a result of shifts such as layoffs, reorgs, mass team departures, bad company press moments, beloved leadership departures, etc. During this stage, morale is at risk, producitivty is hampered, mistrust is brewing, gossiping is pervasive, and so on. The organization is greatly at risk of further team exodus, distracted employees, diminished output, and compromised quality, among other factors.

Double Down: A period characterized by company goals being hit, teams rowing in the same direction, strong belief in mission/vision, healthy culture, and ignited innovation. Clarity has emerged about what is working so that the organization can double down on it and shift into the fast lane. There’s a focus on developing the career equity of employees, continuing to build upon a strong cultural foundation, and starting to stretch the next level of impact… Soar Ahead.

Soar Ahead: This is the 10X era. Growth and organizational health are soaring. Goals are being exceeded. Top performers are the great majority, not the rarity. Employees are activating their zones of genius regularly. The company’s services, products, and brands are reaching the next level of relevance and staying power. In this phase, the focus shifts from maintaining good, to inching towards great, with all eyes on reaching the extraordinary.

Now what makes these stages even more nuanced is that there is no final destination. Rather, companies dip in and out of these phases over and over as they brush up against new macro tidal waves and new priorities from their people.

For example, an organization might have been in the Soar Ahead phase for the past few months, but then a competitor introduces a new product that immediately captures market share and shifts the organization back into the Double Down phase. Or a company is in the Build Back phase and successfully rebuilds morale and belief within some departments (e.g. Marketing, Ops, Finance) so those departments shift ahead to Double Down, while other departments (e.g. Sales, Customer Success, Product) are stuck in Build Back a bit longer for a number of factors (e.g. their team leads are not as strong at instilling faith, those teams were hit by greater macro forces, etc.).

So what does all of this mean?

It means that as leaders of companies and people, we need to always be reflecting on three core questions as it relates to our culture lifecycle…

1. What stage is our culture in today — either org-wide or at the departmental level?
2. Are we introducing the right actions and initiatives that actually drive us to a better paradigm?
3. How are we using data to both validate and predict that we are driving towards the better paradigm?

It all comes down to what we’re measuring and when. Let’s dive in…

Data across the lifecycle

There’s no disputing that tried-and-true culture metrics will always have a home in the world of all things People. Things like eNPS, pulse surveys, retention scores, etc. But, unfortunately, they don’t give the full picture for a Future of Work era.

They capture moments in time. They are lagging, not leading indicators. And most importantly, they don’t account for the differing lifecycles that our organization and our individual departments are weathering at any given moment in time.

Let’s take one small example within the Build Back phase.

Imagine a company is in this phase as a result of massive employee churn. They’ve lost a lot of their A-players and are committed to stop the bleeding. In this case, it’s not enough to just keep their eye on attrition and retention metrics. Those metrics will only tell them what just happened (lagging) versus what is about to happen (leading) so they can prevent additional churn and other negative outcomes.

In this scenario, the company should start to focus on identifying the factors that cause employees to quit well before they actually give their 2 weeks.

By reviewing historical data they already have — as well as new data sources and correlations they can create — the company can pinpoint the variables that cause employees to become flight risks in the first place. Things like:

• What department the employee is in (e.g. turnover in certain teams might be much higher than in others)
• If communication “after hours” starts to surge (a sign of over-working, burnout and boundaries not being respected)
• Specific team leads/managers who are negatively impacting culture
• PTO underutilization… meaning employees aren’t taking time away from the business

By shifting the focus away from retention/attrition (lagging) to instead fixing the culture that is most causing flight risk to exist in the first place (leading), the company can use both strategy and advanced analytics to build back morale and win back unsure employees.

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