четверг, 27 августа 2026 г.
понедельник, 25 мая 2026 г.
What Are The Top 5 Business Challenges in 2026?
Daniela Koleva
The organizations that are pulling ahead in 2026 are the ones that have figured out how to execute faster than the rate of change around them.
That's harder than it sounds. The business environment has never rewarded speed more than ever. Boards are impatient. Markets are unpredictable. AI is moving faster than most organizations can absorb. And the gap between companies that are adapting and those that are falling behind is widening quarter by quarter.
What separates them isn't access to information or capital. It's the ability to translate strategy into aligned, measurable action consistently, at scale, before the window closes. Here are the five business challenges most enterprises are navigating in 2026, and what it actually takes to overcome them.
Challenge 1: Aligning AI adoption to real business outcomes
Every enterprise is investing in AI. Very few can point to measurable business outcomes from those investments.
The challenge in 2026 is the gap between deploying AI and actually knowing whether it's moving the business forward. Generative AI, automation, and analytics are being embedded across products, sales, service, and operations at speed. But without clear ownership, outcome metrics, and a governance structure that ties AI initiatives to strategic priorities, those investments become siloed experiments rather than competitive advantages.
The organizations winning with AI in 2026 have three things the laggards don't:
- Clarity about which AI bets are connected to which business outcomes
- The mechanisms for measuring impact in real time
- The discipline to stop funding initiatives that aren't moving the right metrics.
What to prioritize:
Start by connecting every AI initiative to a measurable business outcome. Define what "working" looks like before deployment, not after. Build governance that distinguishes between AI investments that are core to strategy and those that are adjacent experiments. And create a cadence for reviewing impact — not just adoption metrics, but the business results the adoption was supposed to drive.
Challenge 2: Closing the strategy-to-execution gap
Executives can see the destination. Getting the organization to move toward it at the pace the market requires is where most enterprise strategies break down.
Research consistently shows that the majority of strategic initiatives fail not because the strategy was wrong but because the organization underneath it couldn't translate direction into coordinated action. Teams optimize for their own priorities. Alignment is assumed rather than verified. Review cycles are too slow to catch drift before it compounds into a miss.
In 2026, the strategy-to-execution gap is costing enterprises more than most leadership teams realize — in speed, certainty, and strategic outcomes. The organizations closing that gap are the ones building execution into the operating model: clear OKRs cascaded from company strategy to team level, a weekly cadence that keeps priorities visible, and real-time data that tells leaders where execution is at risk before the quarter ends and the damage is locked in.
What to prioritize:
Make strategy visible at every level of the organization. Every team should be able to answer:
- What are we trying to achieve this quarter?
- How does that connect to the company's priorities, and how do we know if we're on track?
If the answer requires a meeting to find out, the system isn't working. Build the operating cadence by implementing weekly check-ins, monthly reviews, quarterly retrospectives into the structure of work.
Challenge 3: Solving the talent and productivity equation
The talent equation in 2026 has two problems operating simultaneously, and they pull in opposite directions.
On one side: persistent skills gaps in the areas that matter most — AI, data, cybersecurity, and change management. Organizations can't hire fast enough into these areas, and competition for well trained talent is fierce. On the other side, pressure to extract more productivity from existing teams without burning them out, in an environment where engagement is still fragile and quiet quitting hasn't disappeared.
The answer most enterprises are landing on is making the people they have dramatically more effective. AI agents that absorb administrative work, returning hours of management time to strategic activity. Upskilling programs that develop internal capability faster than external hiring can. And operating models that give teams clarity on what matters so they're not splitting attention across competing priorities.
What to prioritize:
Measure productivity in outcomes, not hours or headcount. The question should always be "are we moving the metrics that matter?" Invest in developing the capabilities your strategy requires rather than waiting to hire them. And eliminate the administrative drag such as status meetings, manual reporting, redundant check-ins which consume capacity without creating value.
Challenge 4: Navigating economic uncertainty without losing strategic momentum
The macro environment in 2026 is unpredictable. Tighter capital markets, cost pressure, shifting trade conditions, and uneven growth across regions are forcing enterprise leadership teams into a familiar but uncomfortable position: protect margins without sacrificing the investments that drive future growth.
The instinct in uncertain times is to cut. The organizations that emerge from uncertainty in the strongest position are the ones that cut most precisely. They know exactly where resources are creating value and where they aren't, because they have real-time visibility into the connection between spending and strategic outcomes.
The organizations that struggle are the ones making resource decisions based on gut, politics, or outdated annual plans. They can't see, in real time, which investments are moving the right metrics and which are absorbing capacity without a measurable return.
What to prioritize:
Build spending visibility before you need it. Create a clear line between every significant resource allocation and the strategic outcome it's supposed to drive. Establish a cadence for reviewing that connection — not annually, but quarterly, with the flexibility to reallocate as conditions change. The goal isn't to predict the environment. It's to move faster than it does.
Challenge 5: Modernizing without fragmenting
The digital transformation challenge has evolved. In 2026, most enterprises are asking how to integrate years of transformation investments into a coherent operating model that actually works.
Legacy systems coexist with new SaaS platforms, AI tools, and data pipelines in ways that create friction rather than capability. Integration complexity slows innovation. Multiple simultaneous change programs — new CRM, new analytics platform, new goal-setting infrastructure — compete for organizational attention and create confusion at the front line. And new team members, newly acquired companies, and newly formed functions often operate on entirely different systems from the rest of the business.
The result: organizations that have invested significantly in digital capability but can't access the insight that investment should be generating, because the data sits in silos and the systems don't talk.
What to prioritize:
Choose integration over proliferation. Before adding another tool, ask whether it connects to the operating model or fragments it further. Prioritize platforms that integrate with your existing stack and surface insight where decisions are made. And manage technology change as organizational change: the human adoption problem is almost always harder than the technical integration problem.
And in 2026, prioritization is the competitive advantage.
"The pace of change used to be measured in 5-year cycles, then in 1-year cycles. Now, plans change constantly. Strategy must be 'always on' — and you need tools to help adjust and pivot."— Stephen Shafer, President & CEO, A.O. Smith
https://tinyurl.com/3v6hj5bm
In 2026, the global business landscape is defined by
rapid technological leaps and persistent economic volatility. The top five
defining challenges leaders face today revolve around execution, security, and
market adaptability:
1. Navigating AI Integration & Governance
Simply adopting AI is no longer a competitive
advantage; achieving repeatable, measurable outcomes is. Organizations are
struggling with the transition from pilot programs to scalable integration,
while also attempting to govern ungoverned GenAI use to prevent hallucinations,
brand damage, and regulatory fines.
2. Rising Costs & Economic Squeeze
Persistent inflation, fluctuating interest rates, and
uncertain consumer demand continue to squeeze profit margins. Businesses are
challenged with balancing higher operational and customer acquisition costs
against pressure to keep pricing competitive, making cash flow management and
resource efficiency paramount.
3. Cyber Resilience & Digital Trust
With AI amplifying both the sophistication of
cyberattacks (e.g., deepfakes, AI-powered phishing) and defensive tools,
cybersecurity has become a critical board-level growth constraint.
Organizations must manage a widening digital blast radius that increasingly
involves third-party vendors and supply chains.
4. The Talent Gap & Workforce Evolution
Building a workforce with the necessary skills to
leverage automation and AI is kulturally and structurally difficult. Leaders
face the ongoing challenge of closing the skills gap through continuous
training while meeting employee demands for flexible, secure, hybrid work
environments.
5. Shifting Regulatory & ESG Pressures
Staying compliant has become significantly more complex as data privacy regulations, international trade/tariff policies, and Environmental, Social, and Governance (ESG) mandates continue to evolve. Companies are challenged to meet strict reporting standards while aligning their operations with polarized consumer and societal expectations.
воскресенье, 16 февраля 2025 г.
Dave Ulrich: The Market Oriented Ecosystem
My last post on this suggested that Dave’s new organisational logic means that we need to think about what happens outside of an organisation before we look at its internal arrangements.
However, for me, my logic from The Social Organization (TSO) still applies, ie we need to understand the capabilities an ecosystem will provide and the principles it uses in doing this in order to identify the most optimal organisational solution for a particular environmental context.
For Dave and Arthur, the key thing about the external environment is that it is uncertain and fast changing - or superdynamic. This means organisations need to be more market oriented, and they suggest the key ecosystem capabilities an ecosystem needs to provide are information, customer, innovation and agility.
Josh Bersin - network of teams
They also suggests some ecosystem principles (which provide a basis for an ecosystem’s common shared values / style) to respond to the new environment:
- Establish a consistent set of priorities
- Create the future by anticipating what the market will be
- Win through a focus on growth
- Stay a step ahead of the market by anticipating targeted and future customers
- Effectively use different options to execute a growth pathway: buy, build or borrow
- Seek and inspire agile employees
- Use scorecards and data to drive a growth mindset
- Always reinvent strategy because strategy is never finished.
The book reviews seven main case studies of this organisational form - Amazon, Facebook and Google in Silicon Valley and their digital cousins - Alibaba, DiDi, Huawei and Tencent in China (as well as Supercell in Finland, which is a bit of an outlier, organisationally as well as geographically, as explained below).
The MOE is first of all, an ecosystem (generally defined to mean a network which extends beyond an individual firm). Given the logic reviewed above, a MOE is deliberately designed to involve external allies - partners providing staff, skills, structures and systems and stakes in the ecosystem.
Niels Pflaeging - value creation structure
But the MOE resembles an ecosystem within the orchestrating organisation too, with autonomous teams (cells) working alongside each other through a network rather than as a result of hierarchical coordination. Amazon’s single threaded teams is a great example. And I think this logic works - if an organisation is cellular internally, it also makes it easy to work with cells which are outside. It also provides the customer focus required by the MOE (see TSO on horizontal teams).
The other distinguishing feature of the MOE is that this uses a digital platform to support the operating network. As I noted in TSO, it’s quite hard to scale a network without a common platform, so this makes good sense too. It also provides most of the required information and agility, and together with the cells, innovation. The use of a platform makes the MOE a highly centralised ecosystem though. (Work is done autonomously within the cells, but the leadership of the ecosystem is centralised under the platform owning part of the MOE.)
Note, however, that I don’t think Dave and Arthur are referring to what I would call a platform based organisation where a digital platform enables autonomous groups to work together without hierarchical management or other forms of co-ordination. (I think the best example of a platform based organisation is Haier who also presented at the Drucker Forum last year. If you’ve not seen it, then Gary Hamel has provided a great case study of this company / platform / ecosystem in HBR recently. I particularly like this example because Haier’s platform treats internal and external micro enterprises in just about the same way, so it’s much more similar to a biological ecosystem than a MOE.)
Dave Gray - podular organisation
My favourite case study is Tencent as I think this makes Dave and Arthur’s ideas about platforms very clear. “Tencent shares its expertise and resources in technology, legal affairs, government affairs, and talent and organisation management with its strategic partners. For instance, Tencent offers technological and service infrastucture through Tencent Cloud…” In addition, Arthur's in-house consulting team “offers consulting, training, and coaching support to help key strategic partners upgrade their leadership, key talent, and organisational capabilities”.
Therefore, although the platform fits mainly within the structure element of an organisational systems model, there can also be an aspect which is more about the style that people work in, within and across their organisations, too.
Of course, none of this that new. That's not a criticism of the idea or the book, in fact it reinforces the suggestion that this is happening, and it is important.
Michael Arena - adaptive space
However, if you've not come across some of these examples of platform enabled organisation, then firstly, it already exists in Dave and Arthur’s case study organisations, even if this is largely limited to two main geographies.
But it’s also not that new in terms of the ideas being articulated as an organisation form. Eg the book's platform enabled organisations are similar to the following models which I have illustrated throughout this post:
- Niels Pflaeging's value creation structure (with the informal network formalised through the platform)
- Dave Gray's podular organisation (with a more formalised version of the technological part of his backbone making up for a less significant cultural aspect)
- Michael Arena's entrepreneurial teams and communities (once again, with the adaptive space network formalised through the platform)
- McKinsey's agile organisation
- BCG's dynamic platform structure
- My own melded network organisation, from TSO.
McKinsey - agile organisation
I agree, and do state, that internal and external are becoming more blurred. But for me, the best thing for most organisations to do is sort out their internal organisation - before they grapple with the additional complexity outside. These organisations can still create internal networks of teams, and use internal platforms.
In fact, although Dave’s organisational logic suggests we need to look externally, beyond a single organisation, before we look internally, most of the book’s examples focus on their internal networks of teams, not the way their ecosystem involve allies from outside the organisation.
In particular, the book’s other main case study, Supercell in Helsinki, is a great example of a network of teams approach. However, this company doesn’t really do much externally. Yes, it has partners with shared resources, as most organisations do these days, but I don’t see any evidence of an external ecosystem. And the company’s website provides interesting points about its team focus but says nothing to suggest it followed Dave’s new organisational logic in developing this.
Dave also suggests Amazon first created its capabilities within the organisation and only later magnified this throughout its ecosystem.
BCG - dynamic platform structure
My insights from this are:
- I do think it will be useful to look externally at potential parters and the opportunities for creating an ecosystem before focusing on internal organisation design (see TSO for how to do this internal piece). I’m fully persuaded of this evolution in organisational thinking.
- This won’t always result in creating a MOE or even an external ecosystem and that is fine.
- Regardless of this, creating an internal network of teams is an increasingly good idea. It provides many of the benefits of an MOE with less bother, and provides a great basis to extend externally later on as well (and one again, see TSO for how to create this internal network of teams, or other melded network options).
https://tinyurl.com/49bzch4u
суббота, 8 февраля 2025 г.
RoundMap® : Framework 48 Lenses
The RoundMap™ framework addresses many focus areas and suggests multiple mindsets to comprehensively understand your business, its environment, and its dynamics. By putting on multiple Thinking Caps, you can obtain a panoptic view of your team, division, or business situation (panoptic is derived from the Greek panoptēs, meaning “all-seeing”).
We advise clients to select between 6 and 12 dimensions most relevant to their (desired) situation. As each Thinking Cap comes with 30 questions, selecting 6 viewpoints will provide a 180° Panoptic, while 12 dimensions will provide a 360° Panoptic. We’ve mapped 12 random Thinking Caps in the image below for illustration purposes.
Overview of Thinking Caps
Brand
Thinking Cap
Brand
thinking focuses on developing and managing a strong, memorable brand identity.
It shapes perceptions, builds trust, and creates a positive brand image through
consistent messaging and experiences. It requires understanding the target
audience, crafting a compelling brand story, and effectively communicating
value. Brand thinking involves continuous brand management and adaptation to
stay relevant in the marketplace. It drives brand loyalty, recognition, and
long-term business success.
SCOPE:
Corporate identity, PR, brand value, reputation management
RELATED:
Marketing communications, customer loyalty, attraction
OPPOSITE:
Profit-driven, short-termism






















