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M&A Success – and the Systems Harmonization Challenge

I’ll steal a bit of the title of an article I’m going to be referencing from Clayton Christensen et al – “The Big Idea: The New M&A Playbook” You’ll note that this article is from March 2011 – and sitting on this side of the decade, I can tell you that the failure rate of M&A’s is still unacceptably high – and for much of the same reasons as the authors quote.

While I’ve spoken and written quite a bit about cultures and mindsets, I’ve also done the same on costs – especially opportunity costs, foundations of change, process and making better use of the technology platforms available (get to the cloud!). So much so in fact, I created an entire personality & compatibility assessment & report that has raised interest in PE firms looking to drive M&A activity and board member selection – an unintended use but a happy surprise for the utility they’ve received from it.

Let’s go back to a key point in the article:

“…the acquirer uses the target’s business model as a platform for growth. Because the business models with the most transformative potential are often disruptive, they can be difficult to evaluate, and CEOs often believe that such acquisitions are overpriced. In fact, however, those are the ones that can pay off spectacularly.”

What that should tell you and me is that there is a fundamental benefit to M&As, they just tend to fall apart for one reason – the effort to truly integrate – culture, process, technology – all of it – isn’t being executed on.

Let’s unpack another great quote:

“A company can’t, however, routinely plug other elements of an acquisition’s business model into its own, or vice versa. Profit formulas and processes don’t exist apart from the organization, and they rarely survive its dissolution.”

And this is where we see many M&A’s start to breakdown. Beyond the technology & process harmonization, there’s the underlying condition of creating a new, harmonious system that is greater than the sum of its, formerly, two separate parts. And, as experience has shown us, technology and process – much less culture – are very much an artefact of their cultures. Too, the national culture very much leaves its fingerprints on the company culture, and it’s choice of technology & process stack.

Here’s a couple real world examples, but the caveat is that you will still find significantly differentiated examples. Company A, based out of Asia, transacting business throughout the entirety of the Pacific Basin and Europe. There is high power distance, and a very high level of formality within and across business units. Hierarchy is very much observed and not disrupted. Processes however are extremely loose and undocumented, and technology is largely open source with some cloud deployment to national cloud providers. Company B, based out of the United States, transacting business throughout North & South America, with some market penetration in Western Europe. Power distance is medium and there is a fair amount of informality & autonomy, however, hierarchies are still largely respected even if they’re not strictly observed. Process is evolving steadily and is mostly in ITIL Level 3. Technology has some one-of installations but the enterprise stack is otherwise standardized on a road map to be 20% hybrid & 80% cloud deployed within 4 years.

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Those two firms merged, many meetings were successfully held until there was a growing sense of unease that information flowing from A to B was coming up incomplete. Yet the entire reason for the merger was that A had much greater margins (22% on $12B revenue) on their business (as compared to B (8% on $40B revenue) and – you guessed it – the desire was to get B to run A’s processes and achieve similar margins!

Great idea. Yet already there were concerns on process & technology harmonization before communications became an issue. Dissecting those conversations would have shown that cultural tone-deafness, on both sides of the equation, was leading to increasing error-rates on communication back and forth – and it was starting to spin more and more out of control. Ideally, the merger plans would have included team building and culture change in both organizations towards something that was workable (at first) for both with the intent of understanding what was behind the greater margins and how to translate those between the two companies.

Yes, I’ve intended to end right back on the same topics that are central to our work – communication, and culture. Technology & Process are the easy parts – once you have transparent communication & a new emerging culture. When those components aren’t tended to, you’re going to have an increasingly harder time trying to harmonize systems. There are plenty of smart folks that built those system – and the harmonization challenge isn’t technology or process based. It’s having that same team environment that was there when these systems were built, tested & deployed – something that is distinctly not in place in the case of an M&A unless it is specifically planned for.

If you’re considering or are part of an M&A – think about team and company culture differentiations & differentiators – and what culture you want to create that’s a combination. Don’t go it alone. Make sure leadership and teams are involved in those very intentional, planned conversations. You want to focus on building rapport, establishing clarity in intent, actions & goals – and from there, trust will come about – trust, which is central to any type of relationship.

Here’s the TL;DR version:

If you’re in an M&A situation (regardless of role or work load), focus on these 3 things first:

  1. Build rapport by creating clear intentions, actions and goals
  2. Gradually establish transparent, candid, safe conversations – this will be the step where taking cultural differences will be critical
  3. Actively build trust by creating team building exercises – if your teams are virtual and remote this is important, and it can be done, it simply requires more effort

Finally consider this quote from Benjamin Franklin:

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“We must all hang together, or, most assuredly, we shall all hang separately.”

 

 

 

PS: We’ve done this a few times, drop us a note.

Hierarchies, Autonomy & Communication

You know how we keep bringing up communication?

Marcel Schwantes‘ article in Inc. Magazine really drives that point home.

The article cites examples from Elon Musk and Hubert Joly – and the benefit they wanted, and saw, from introducing autonomy to hierarchical organizations, highlighting how detrimental hierarchies can be to the modern organization. Our CEO & Founder made a similar point when he was interviewed by Kelly Wilson at Edge.

In the modern company, especially for knowledge & information workers, hierarchies are a barrier to – well a lot more than not. We’ve seen first hand how hierarchies impede innovation, the entrepreneurial spirit, uncovering risk and impede the execution of complex tasks that are the fiber of every modern company. They are an anchor.

The antidote? Autonomy! It does require real, intentional work to execute & we absolutely understand how hard & challenging that can be. Culture has to change, leadership and contributors need to learn new skills, the organization has to become accustomed to a new way of operating. But the benefits far outweigh the cost of such an exercise.

Autonomy is a force multiplier to any organization. It accelerates that critical time to value. Even more importantly it fosters the creation of tight horizontal bonds that are elastic & resilient. When the next inevitable crisis hits, the fires don’t stand a chance as people will organically come together and self organize to make sure of it.

If you’re going to change one thing this year – do this first. Contact us – we’ll help you start!

The Great Reset (not The Great Resignation)

Resignation – the word itself conjures images of giving up and walking away – which is why I think we’ve all got this wrong.

How about we look at this is an opportunity – we can make it one – and sure, in some cases, you’re still going to want to – and in fact – should quit.

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A lot of this comes down to culture, communication & workspace.

People leave bad leaders (and to that I’ll add work cultures) – it’s an amorphism everyone states – but what are we actually doing about it!?

Ratchet goals, inspection & monitoring, poor communication, whipsaw directives, unbalanced work/life, recrimination, stack ranking, exhaustion as accomplishment, employee surveys with no tangible outcomes – it’s a long, damning, list that we could each add to. But let’s use those as lessons!

People are leaving and don’t want to spend 1/3 of their lives in those cultures, anymore. Maybe it’s the pandemic, maybe it’s the younger, more aware generations that have grown up in a mutable, flexible, diverse world where terms such as equity, quantum, AI and metaverse have really expanded their awareness as to the art of the possible. And it’s infectious! Of course they’re not going to stand for the antiquated antics of antediluvian anicients. I’m damn near one of them and I’ve never stood for that kind of ossified thinking.

Think about how IT, perhaps the biggest source of this movement, is managed overall, and how 95% of the time its culture is incongruous with the overall corporate culture – because no one took the time to integrate those cultures and maybe refresh how the business operates. Consider the example of how hard it is to implement Agile in older shops, but how it works exceedingly well when it is implemented! Consider how many times you’ve seen an ERP or CRM engagement become 95% customization! What is it about your specific processes that are so effective – or is it just because that’s how they’ve always been done. Be honest. Tie them to financial performance before we have this conversation.

I get change is hard. That’s precisely why change is necessary – you know what happens when you stay in your comfort zone?

I got into IT leadership exactly because I wanted to wield IT like it was a swiss army knife. I wanted to tie business goals to IT results. I wanted to inject financial awareness as to the cost impact or the revenue benefit of IT decisions! Business operates on cash flow – how can I not speak their language and expect them to speak mine?

And here’s the truth – even when one of teams I was running was turning in top results and driving highly profitable growth for a division from $60M to $100M – I STILL locked horns with a CIO who would die on the Stack Rank hill and push one more mandatory RIFF head count to my team because there was that ONE person who disagreed with their technical design decision and was RIGHT to do so. I offered to RIFF myself if he was so insistent!

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These counters and deal sweeteners are temporary and will only last so long when faced with these broken cultures.

Here’s another story. About a month ago I talked with a business exec who was considering just transitioning everything IT overseas – IT to IBM, development to Eastern Europe & call center to the Philippines.

We made 3 calls and 60 minutes later and armed with real world war stories, this is what he said: “You know, I REALLY hate it when you’re right!”. But he still wasn’t getting the message – and you know, that’s on me.

You can’t make those moves if you have broken processes, leadership and cultures. Fix those first, then, yes, absolutely scale up when you need to. Guess what? You might be surprised at how infrequently you have to do that when your system is operating much smoother!

There is a hidden cost to the inefficiencies of bad leadership, broken cultures and poor communication. We track it, we fix it, and we show the benefits on the other side.

Don’t just nod along – do something about it!

Unless & until companies are willing to address their cultural, communication and leadership debt, this problem is going to linger and employees are going to vote with their feet.

That’s why I’ve been calling it the Great Reset and not The Great Resignation

This is a golden opportunity for leaders. It’s in our hands what we do with this.

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Riding the Tiger

Riding the tiger is, ostensibly, as all good sayings are, an ancient Chinese proverb. It indicates an action that once taken is dangerous to stop. You could equate this to taking a known risk, or even sunk cost.

We see this so often in our work rescuing technology programs that have been going sideways. Everyone is afraid to stop. A little more effort, work harder, bring in some high priced consultants, part the Red Sea.

How about stop, drop & roll? Or even just slow your roll. A crisis is often when organizations fly into high gear – and proceed to spin their wheels fruitlessly.

Instead what we do, what we’ve done and what we teach our clients to do is a very fast, very accurate assessment of root cause & remediation steps to tamp the fires, realign and refocus out of crisis mode. We bring our unique IP to bear. And yes we still focus on culture & mindset, so you can face the next crisis with elastic resiliency and thrive – not just survive – through it.

After all, what’s the point of us helping you get off that tiger, if you’re just going to jump on another one?

Leadership Challenge

Yesterday our Founder & CEO posted about seeing more “skill cards” from leaders. Today he wanted to speak more to that. We agree – and we’re not just saying that because he pays us!

Skill accomplishment posting are fantastic – and those getting those achievements should be proud of the hard work & dedication they’ve demonstrated – their accomplishments will go a long way in their careers and professional journeys. We like seeing those pop up in our feed on LinkedIn.

But what about our leaders? Granted it’s a tougher to measure in the same way as technical skills, which is interesting because it’s obvious, to all of us, what the difference is between a great leader, a good leader and a leader who needs some more time baking the oven. No, not literally, gosh, more coaching or mentorship.

We’re convinced that classes (example from a MBA) and books (some listed below) are all great ways to start. We’re also equally convinced that for leaders to be successful, coaching & mentorship are equally, if not more, critical – and often missing in the professional work.

We’ve heard “that person was great at their task work, but gosh, they’re a horrible leader, how did they ever get promoted?” so often. Because they became great at their task work and got thrown into the deep end of the leadership pool with no support. Expecting them to do more than wade in place is a Greek tragedy waiting to happen.

So – how about a leadership challenge. Brag about your leaders, call out what they’re doing to help, what they could do to help. Leaders, listen. It may be uncomfortable, but it will go a long way to creating an empowered culture of trust, empathy & resilience.

Any takers?

Falling, Failing & Flailing Forward

We’ve all heard of falling forward when it comes to entrepreneurship, and innovation.

Recently Simon Sinek mentioned choosing different language -falling vs failing – because it matters to shifting our mindset. No matter how much we talk about not fearing failing, that concern remains, especially in larger organizations that continue to evolve what it means to them to innovate – to build centers of entrepreneurship within. They are still operating under cultures that don’t reward, or encourage failure!

When one falls, intentionally or otherwise, our reaction, especially as leaders, is to help them up and continue to encourage them. Makes sense, right?

Look, as innovators & entrepreneurs we have to expect that we’re going to fall. None of us are prescient or perfect – but, and we’ve said this repeatedly – mindset matters. So the simple change form failing to falling makes a lot of sense, removes fear and drives engagement and encouragement to take those risks.

Now – and we always coach this regardless of the size of the client we work with – it’s still about intentionally taking smart risks. So to this we’ll add – don’t FLAIL forward. Don’t just do & do & do to see what sticks, and then think it’ll just be a pivot.

You know what we call something that keeps pivoting – in place? A top. It wobbles to & fro and doesn’t really make much forward progress.

By all means, try, and try, and try – entrepreneurship for us is about intentionally taking risks until we achieve success. So now to this we’ll add – don’t fail, don’t flail, but fall forward.

You’ll be helped up, you’ll be encouraged, you’ll learn and you’ll always make forward progress.

BELYONS OF ROWS!

Let’s talk about selection criteria for that AI\ML platform you’re considering. (ed: yes, I know, I said let’s stop calling it AI\ML, ships turn slow)

We’ve been seeing a lot more ads about different AI platforms out there and they’re typically along the lines of “…crunch through billions of rows of data in 9 seconds flat!” – or some such. While those are great metrics to consider, they really need to be second, or even third, on the list of what you’re thinking of.

Here’s how we approach ML platform selection with our customers.

First – you really want to consider how the platform ingests all the data you have. It used to be there was a lot (a LOT) of data normalization – and that shouldn’t be the case anymore. Make sure you understand what data formats you can export (or which and how you will allow connections into your sources) and the capabilities of the platform to ingest, understand and draw inferences from that data.

Second – what questions are you trying to answer? It’s great to just look forward to being delightfully surprised by unexpected pleasant surprise correlations – or causations – and be able to tell between the two. It’s even more important you set out with a list of questions you want optimal answers to and find those pertinent patterns in your data.

Third – accuracy! Even after training the model, is accuracy being actively, reiteratively measured and are you ensuring you keep training your model as you discover new, pertinent, patterns? This is critically important to ensure you’re tracking to reality and new emerging and changing old patterns. Data, business – the world – is never a static snapshot in time. This, by the way, is where a lot of ML projects come up short – the process of ensuring reiterative training doesn’t occur. ML is not a one shot.

A quick shout out to ClosedLoop.ai. No they didn’t sponsor this post, we just really like their current direction for healthcare!

Finally, keep in mind that most ML platforms today are focused on post-encounter or post-service transactions. If you have pre-encounter or pre-service questions or patterns you are looking for, consider something that’s more of a heuristic platform. We’re still researching and sorting through those now, and tinkering with one of our own making. We’ll make sure to update when we have something tangible.

Thanks for tuning in!

Cultures & Software Engineering!?

Let’s talk about cultures & software engineering!

Uh … What?

Hear us out. Every company has its unique culture, even if there’s cultural similarities between companies in the same domain or vertical. They’ve developed and evolve over time.

Just like most mergers or acquisitions fail because culture differences are not tended to, most software engineering projects carry that higher risk, or cost, or longer time-to-value, because software engineering has its own culture and if it’s not tended to – or if it is expected to operate under the same culture as the organization – you’re going to run into significant challenges.

Almost every time we’re called into a software project at risk, we see cultural clashes that aren’t being tended to which are leading to process, communication, productivity and efficiency breakdowns. The antidote – work harder, work more – is counterproductive and harmful.

We address those issues and we also address the cultural differentiation at the root of those challenges. If we don’t, those issues are going to keep coming up and future software projects will be at risk. We’ve shown, first hand, it’s necessary and indeed possible to do so.

If your company is struggling with their own software development projects – please! – call us. We’re happy to spend an hour on the phone with you, getting to know you, your project and sharing pertinent tips to get you started in the right direction.

Reminder: Take Breaks During Your Work Day!

We’re talking to your schedules today. They’re back to back with meetings – where’s the you time in there? We don’t take breaks at work, especially when we’re working at home. Those long hours working a task staring at your screen slinging code or laboring away at a project are actually gradually reducing your effective productivity – and sapping your energy.

The solution is simple. Create a new habit of taking frequent breaks. Once an hour if you can, but no less than every two hours. Get your blood moving, move your energy, set your brain on simmer and breathe with intention! You’ll find yourself a little bit invigorated and sometimes you’ll get that “Aha!” moment you were looking for.

Try it today, wrangle that schedule, create some break times for yourself. We’re eager to hear what difference you see!

Artificial Intelligence is Neither

Artificial Intelligence is neither.

Let me explain. There’s been growing interest and commentary in the last several years on Artificial Intelligence (AI) and as a wannabe writer, relapsed polyglot, software engineer in remission and AI enthusiast, I would like to share some insights, stop budding AI luddites in their tracks and start a movement to reduce popular use of terms such as AI and Machine Learning (ML) – because, well, they’re neither. For the sake of clarity I will continue to use those terms in this article.

Will we create true Artificial Intelligence (or Sentient) systems? The answer to that question, as to any other is, yes, with time, energy and resources. If we can imagine it, we can make it happen. But we’re definitely not there and don’t have the hardware or software for it. It’s zeroes and ones, and even if it’s fuzzy logic or quantum compute, it’s still simulated via zeroes and ones. Intelligence isn’t bound to binary.

Ex Machina - Film4/DNA Films

Today’s AI systems are typically (but not always) statistical model number crunchers taking advantage of utility compute power and freely available oceans of data to find patterns and trends that meet some desired outcome, in the hopes of being able to predict those desired outcomes. One great example of this is ThyssenKrupp’s MAX Predictive Elevator Maintenance Program. It’s a bunch of some wicked statical math and some really cool modelling. There are, of course, other types of AI systems – as mentioned below.

In fact, nearly every example you can think of today isn’t intelligence – it’s really not. Even when it looks like it. For example, autocomplete – isn’t intelligent or smart (but it is cool!). Something like autocomplete is number crunching through immense amount of data (thanks Cloud Compute and everyone who accepted EULA’s without reading them) to generate likely outcomes.

But it learned what you really mean to type when it autocompletes duck!

Not really.

What it did was notice that you kept changing duck to puck when texting with your hockey buddies. Then duck & puck to cluck with your 4H alumni. Then duck & cluck to puck back again. So now, sure, it seems like it’s learning and sure it seems smart because now it knows to send puck to Wayne and cluck to Jimmy instead of the ever confusing duck to exactly no one ever. But was that a process of learning? Pedantically, yes, but it’s not really learning when you’re applying it to a narrow problem in a single domain. What you’re doing is (math & models!) changing desired outcomes based on who you’re interacting with. There is a discrete, bound box it operates in. There is no knowledge or skills acquisition.

Wizard of Oz - MGM\Disney

Are there companies that have\are creating AI platforms that you can use? Absolutely! After you train them (lots of data!) and specify (bias) towards your ideal outcomes, they’re a cost effective on-ramp to leveraging the power of these tools. They’re still not AI, and it’s a stretch to call them ML. Look behind the curtain and you’ll find … Oscar Diggs! Same thing. But what a fantastic business model. Now, if I can take one of those systems trained for predictive maintenance for Sunbelt’s construction equipment (made that up) and drop it into Pinch-a-Penny’s pool proactive summer maintenance program (made that up too) and it remembers both … ? Well it’s not going to – and really, nor should it because these are tools and platforms we use to solve problems in a specific domain. And because these systems cannot inherently gather knowledge and skills, it’s not quite right to call them AI or ML systems. Those platforms are great for democratizing those tools, but they’re still neither AI nor ML.

A.I. Artificial Intelligence - Warner Bros

But they’ve created Art! Music! Faces! Again, let’s think about this. They had to have a massive set of data to ingest, real world approximations and a model (there’s that word again) to work within to create something that sounds or looks better than what a room full of monkeys smashing away at keyboards, easels and instruments will create.

Which, if you really think about it, is sort of like the real creative process only with less discordance and poo flinging. I’m pretty sure that’s not how Da Vinci, Prince or Austen created.

So what should we call them? Well, Enormous Cloud Compute Assets Statiscally Calculating and Modelling Things is a bit of a mouthful. And there’s a collection of nicely descriptive names for simulacra “AI” systems such as Expert Systems, Neural Networks, Genetic Algorithms, Blackboards, etc. But they’re still, generally, the same thing at the end of the day. Massive gobs of data, statistical or simulated modeling or meta/heuristics to achieve some desired (and therefore previously known) optimal solution.

I propose we just abbreviate it all down to Simulated Modeling (SM).

Because, Artificial Intelligence, is neither.

(… with apologies to our future sentient machine overlords, please don’t skynet us)