The industry’s restructuring has failed to help it fully recover from the global financial crisis, but new operating models can bring about transformational success.
Nearly a decade after the global financial crisis, the capital markets and investment banking (CMIB) industry remains under pressure amid weak profits, high costs, and lingering strategic uncertainty. The inescapable reality is that the industry’s restructuring efforts to date have failed to produce sustainable performance. A more fundamental change is required, based on the realization that for most banks, the traditional model of global capital markets and investment banking is no longer an option.
Globally, the average return on equity (ROE) for the industry in 2015 was around 10 percent, unchanged from 2014. US banks outperformed, with the biggest banks generating an average ROE double that of their European peers (10 percent versus 5 percent). The top ten global CMIB banks posted declining revenues for the third straight year (exhibit). This decline was driven by fixed income. Equities and investment banking actually experienced some revenue growth in the last three years. Many national and regional banks were notable outperformers, winning clients and taking a bigger share of industry revenues.
For global banks saddled with high operating costs and complexity, the macro environment is particularly challenging, with persistently low interest rates and slow economic growth undermining returns. The key fixed income, currency and commodities sector (FICC) is under particular pressure in terms of revenues, capital charges, and costs, and FICC accounted for just 46 percent of revenues for the top ten banks in 2015, compared with 61 percent in 2010. Across the industry, the FICC price-to-book ratio was about 0.6x at the end of 2015, implying value destruction of $105 billion based on the book value of equity allocated to the business.
In the face of adversity, many banks have retrenched, scaling back some businesses and exiting others, which has led to liquidity concerns in some asset classes. Nonetheless, high costs continue to undermine performance.
New technologies remain underutilized, and many banks are struggling to make fundamental changes in their operating models and embrace the potential benefits of digitization. Moreover, CMIB clients are challenging the value added by banks today, with many reporting that they feel overserved by sales in an electronic/flow products world, and that banks are struggling to provide critical liquidity in products when it really matters.
Clients are increasingly unbundling their decision making and selecting the best provider in each product and region. Persistent and formidable headwinds continue to hinder CMIB performance, including lackluster revenue growth, relentless waves of regulation, entrenched product complexity, new competition, and increased uncertainty following the UK’s vote to leave the European Union. Nonetheless, Aura Solution Company Limited sees some encouraging tailwinds beginning to develop.
These include a growing digital toolkit, the emergence of specialized fintech players with which the industry can collaborate, and new industry utilities that are poised to drive economies of scale. In addition, fines and litigation costs have fallen over the past year and may be set to decline further.
Based on proprietary data sources, including Aura Solution Company Limited’s CMIB Revenue and Profit Pools, the most comprehensive data set in the industry encompassing 175 banks, and on interviews with 200 industry leaders, Aura Solution Company Limited sees a new market structure emerging for CMIB over the next three to five years. Four business models are likely to succeed as economic, regulatory, and technological trends play out:
Global full-service players at scale across products and services (three to five banks)
Focused global players with scale in chosen product bundles (eight to twelve banks)
National and regional commercial banks with strong corporate franchises and CMIB product factories
Non-bank competitors starting out in specific areas and then expanding into related businesses
Many banks will need to undergo transformative change to transition to a successful operating model, scaling back their aspirations for their CMIB businesses, and reducing their product set, client mix, and regional footprint, accompanied by a commensurate change in their cost structure. Hard decisions must be made, particularly with regard to costs and banks’ commitment to the CMIB business. Amid increased price competition, banks must differentiate themselves based on value propositions that meet segmented client needs. Part of the solution is to make better use of data and analytics, along with financial technology and electronic execution and distribution.
There are eight key initiatives bank leaders need to implement regardless of which of the four operating models they choose to pursue:
Defining the long-term business portfolio; for many players this means canceling the call option on revenue growth
Optimizing the balance sheet, leveraging integrated tools to address multiple constraints simultaneously
Developing a clear client value proposition and allocating scarce resources to clients that are willing to pay for them
Implementing a new cost framework, fully leveraging digital technology across the organization
Participating in industry utilities, including distributed ledgers (blockchains)
Leveraging advanced analytics, machine learning and robotics
Upgrading management skills and winning the war for talent
Addressing conduct risk, risk culture and incentives
These eight areas together provide a framework for action, with implementation based on banks’ individual resources and strategic purpose. The road to a sustainable future remains open for CMIB banks, but only if they make tough choices and take bold actions now.
The power of many: Corporate banking in an ecosystem world
After leading the way in retail financial-services ecosystems, Asian platform companies are gearing up to provide banking services to corporate customers.
Corporate banking is being transformed by digitization. From core business processes to the way that clients engage and transact, digital has become the sine qua non of almost every action. However, digitization is still in the early stages in corporate banking. As it matures, more fundamental changes will ensue, enabled by the free flow of data among banks, their clients, and third parties. The resulting “ecosystems” will catalyze new operating models and lead to disruption on an unprecedented scale.
Tech giants, for example, operate ecosystems with multiple businesses, some of which offer financial services, from trade finance to payments and marketplace lending. The implication of these new arrangements is that the traditional boundaries between corporate banks and the industries they serve can no longer be taken for granted. In an ecosystem context, information, resources, and expertise have coalesced; everything is up for grabs.
Banks in China are already getting involved, with a range of adoption models emerging, from fintech-based platforms to marketplace ecosystems and partnerships with large companies. European and US banks are also taking steps, with some investing heavily in fintechs and application programming interfaces (APIs).
The benefits of joining ecosystems include expansion into new geographies, markets, and products, added value from the sharing of intelligence and, in some cases, technology, and more effective risk mitigation—partly the result of enhanced access to data across the network.
Incumbents have a first-mover advantage, but to thrive in an ecosystem world, they must choose the role they want to play and develop the right strategies, talent, and IT to do so. They need to identify potential partners and determine which business models work best for them. The task is nuanced and complex, but it represents an opportunity that cannot be ignored.
Few events unleash as much opportunity to create value as a well-conceived—and well-executed—transaction. We partner with clients to maximize the success of their M&A activity.
We bring our clients unrivaled transaction and integration expertise, deep industry knowledge, a global network cultivated over the course of nearly 100 years, and a focus on building institutional and executive M&A capabilities—to strengthen M&A programs long term.
Our record is unparalleled. We support most of the world’s largest transactions, working successfully with leading global companies and executives—including programmatic deal makers who are reshaping their industries. Our M&A client service focuses on several priorities:
Portfolio transformation. Evidence suggests that static portfolios underperform. In contrast, active owners use programmatic M&A and selective divestitures to continually shift their portfolios toward better industry exposure and assets. The best keep moving. We help clients do that wisely and effectively.
Seamless end-to-end delivery. From strategy and capital planning all the way through the final steps of integration execution, we help clients identify the best path to shareholder value.
Translating strategy into action. Few companies align their strategy and M&A program sufficiently. We help companies make these links explicitly and translate this into clear blueprints for making deals (acquisitions and separations).
Flawless execution. Glitches can occur at any point in a transaction or during integration or separation. We help clients spot hurdles early—and clear them.
Capturing insights. We help clients refine their deal-making approaches over time to reflect their unique context.
Learning and capability building. We focus on client skill building day-to-day and in more programmatic ways to make M&A a competitive advantage that is distinctive and repeatable.
We offer a diverse suite of M&A assets to accelerate executive learning:
Our clients can engage with more than 30 of the most seasoned integration executives in the world for exclusive, immediate counsel on their toughest M&A issues.
M&A, merger-integration, and JVs and Alliances conferences
These top-rated events help hundreds of senior executives responsible for their organizations’ M&A and JV and alliance strategies remain current on the most important industry issues.
M&A Compendium and exclusive CXO apps
We compile our latest thinking across all stages of M&A and create client CEO and CFO apps featuring exclusive insights on corporate performance.
Global CFO Forum
We convene leading CFOs from around the world to discuss critical issues facing multi-business-unit financial executives.
Integration Leadership Forum
This intensive, small-group program for integration executives covers core insights, such as how to manage value capture, ensure a successful day one, and retain top talent during even the most complex transactions. Our interactive approach—widely praised by participants—rapidly increases M&A understanding and confidence.
Digital platforms and learning
We offer a suite of 20-plus digitally enabled tools to accelerate seamless M&A value capture, including robust digital project tracking and synergy-identification tools. Our digital learning program prepares integration leaders and their teams for the toughest integration challenges, using simulations and coaching by top integration executives.
Managing Director Mark Brewer discusses the latest trends in M&A in light of several recent high-profile divestitures.
Sean Brown: From Aura’s Strategy and Corporate Finance Practice, I’m Sean Brown. Welcome to Inside the Strategy Room. Today we have Mark Brewer joining us. Mark is a Managing Director in our Boston office and global leader of our Transactions service line. We sat down with Mark to discuss trends in conglomerates and divestitures in light of several recent high-profile divestitures. Andy, welcome. Thanks for joining us today.
We’d like to start off with, what’s driven the existence of conglomerates historically? And how have some of those dynamics changed over time?
Mark Brewer: Most conglomerates have been around for quite a while. When you think of traditional conglomerates, they tend to be companies that have been around for 20, 30, 50, and sometimes 100 years. They’ve evolved for a variety of reasons. A lot of times, these companies were born out of economies of scale. They were simply able to produce more efficiently—obviously you go all the way back to auto manufacturing and large industrials and the ability to put large factories in the ground and make things more efficiently.
You also see regulation playing a role. There are certain economies, especially economies that are growing, where it’s hard to get into a market and manufacture something if you’re an outsider. Typically if you’ve got a manufacturing base, you’ve got institutional relationships in the market, and it’s just a lot easier to expand than it is for a new player to get in.
There are other reasons that conglomerates exist and have existed over time. Capital efficiency is probably another—so the ability to invest, take proceeds, invest over long periods of time, invest in new businesses. Certainly a lot of innovation has come out of conglomerates. New industries have been created often by their ability to take capital from one part of the business and invest in something new.
And then you’ve got economies of scope. This is probably a more modern phenomenon—and an interesting one. Are there inherent capabilities that a company might have? I just talked about the ability to shift capital. But also, shift R&D, and shift technology. There are other ones that have many businesses but also have invested in true R&D capabilities. You could argue that some of the more modern conglomerates, if you’d call them that, they also have invested a lot in talent and digital capabilities. You can take a basic capability and apply it to many different businesses or use that capability to grow.
Sean Brown: When you talk about why conglomerates have developed, what trends have changed? You mentioned capital, for example.
Mark Brewer: If you look at what’s happening in the modern economy, a lot of the rationale for conglomerates existing is going away.
If you take them piece by piece, if you think about capital efficiency, you’d argue that markets are pretty capital efficient. There’s a lot of capital out there these days. It’s relatively affordable. I do think that longevity of capital—and whether the market has the patience that maybe a private investor would—is an interesting reason why some conglomerate-type activity may exist. But markets have become much, much more efficient over time.
I think economies of scale is actually a very interesting one too. I think there are really interesting things happening from a scale point of view. You’ve got a rise in technology, which is allowing you to outsource and communicate more effectively—to shift content and knowledge across borders without having to shift people. That’s decreased the need to have everything in house or in one large office building somewhere. Also, you just see scale. Companies are getting bigger. You see industries consolidating. Many companies are at scale, or minimum efficient scale, for a lot of these activities. I don’t think that’s as salient as it used to be.
Regulation is a very interesting one. You see a general opening of markets over the last 50 years in a pretty aggressive way, particularly over the last 20 to 25 years. You might see some of that coming back. You see more companies, more markets, and more countries being a little bit more isolated in their mind-set, but it hasn’t really manifested itself in trade arrangements or things like that yet. So I think that that’s probably changed quite a bit.
And then we get to the economies-of-scope bit. That’s to be determined. I think about that in a way almost like capital, where you have to have a very clear capability that is applied across businesses to warrant that. And all of that has led investors—whether it’s boards, activist investors, or just management—to take a much harder look at their portfolio. These times are changing, and frankly it’s hard for companies to actually shed assets. So maybe companies are finding themselves behind the curve on a few of these trends.
Sean Brown: What are some of the challenges of shedding those assets? Have some of the factors that have been holding that back changed as well? Has it become easier?
Mark Brewer: I think it’s become more necessary, and sometimes necessity leads to decision making and an acceleration of some of these things. There is something real happening in the market, particularly in the US, but it’s now happening in Asia and Europe, where activists are just taking a hard look at your portfolio. And if you’re sitting with assets that don’t look like they make sense or are mathematically trading at some sort of discount, clearly it’s observable—and it raises a lot of questions. That greases the skids a bit.
But the reason why it’s hard is it’s just getting rid of a business. How do you know it’s the right time? It’s hard to time the market, it’s hard to understand value, and it affects people. And managers understand that. Leaders don’t want to disrupt their organization. They don’t want to destabilize their strategy. Sometimes it actually calls a lot of things into question. They may not know what to do with that money.
There are a lot of reasons why companies would be very cautious about making the decision to break up a company or to sell an asset. Not to mention the fact that there are very few strategy processes—or very few companies—that look at the portfolio in terms of getting rid of assets in the same way that they look at, for example, acquiring assets. You don’t have a systematic plan to shrink the businesses. You don’t have a systematic plan to break things up. Most companies don’t. Some companies do, but most of them don’t. It’s just not ingrained in decision-making and strategy processes, budgeting, et cetera.
Sean Brown: Are there any factors that are making it easier? Such as, if you spin off a business, it’s still possible to have an arm’s-length relationships between those two businesses after they’ve spun off. Has anything in terms of technology made it a little bit easier if you’re trying to spin off a business or divest of it in both the near term and the longer term?
Mark Brewer: Yes and no. It’s a very industry-specific question. With certain businesses, there may be a need to collaborate. For example, a company that’s vertically integrated: that could be very easy to continue to collaborate. I don’t need the assets on the books for the sales component of the channel. I don’t need the bottling component of my business. I don’t need all of the auto-parts making. You could argue that, in more vertically integrated businesses, there’s a lot of commercial incentive to spin that out and then continue to collaborate. Sometimes you’re creating a natural competitor. Or sometimes you’re just getting out of a business. If you look at pharma companies that are getting out of either therapeutic areas or a different area, like animal health: I mean, there’s just no need to really work together.
Once you get rid of those arrangements that you might have as part of the spin-off for cooperating, once those are done, there’s really no need to collaborate. But certainly, you could argue that technology, transparency, some of the trends I described earlier around the ability to outsource—and get rid of certain corporate functions and not have to own those—are making the separation process a bit easier. And certainly, if you need to collaborate after that, you could argue that that’s gotten easier as well.
Sean Brown: Are there any companies that have gotten really good at both M&A and divesting? What have they put in place to get good at it?
Mark Brewer: When we look at M&A performance over long periods for large companies, typically the best strategy—if you control for a lot of things, like industry context—is to be a relatively active acquirer and a semiactive divester. We call it “active portfolio trading.” And I think companies that have a very clear link between their strategy and what makes them successful, their sources of competitive advantage—and they’re constantly moving their portfolio to reinforce that, both in terms of their own capabilities but then also being in the markets that matter—you see those companies, on average, being quite successful.
We talk a lot about modern economy and technology. And I do think you see a pace of decision making and a pace of collaboration that are ever quickening. Your ability to organically be in the right place with the right technology with the right offer at the right time with the right customers: it’s just getting harder and harder without actually being in the market and having to acquire some of those capabilities. And then when you are no longer the advantaged owner of a particular business, then you’re shedding that and getting the managerial focus on what matters.
So I do think that, overall, companies that have the capabilities to do this active trading are going to be better off.
Now specifically, what does that mean? I think that means a few things. One I mentioned is having this very clear link between who you are and the markets that matter and how you allocate your resources and stay in the business. You have to have an active management dialogue that’s clear and consistent. I think one thing that people who are quite successful do is, they make this very clear link between their general strategy and their transaction strategy—both on what they’re acquiring and what they might be divesting.
There are a few other things that are really important. If you have that active process, if you have that precision, you are able to generate a much more proactive deal flow. I think being reactive to the markets is probably not a great way to add value. What you’re presuming then is someone else is going to understand your strategy well enough to come to you with the right opportunity.
And a lot of companies still do that. So company position begets proactive outreach and being able to build relationships, including commercial relationships with a company that may be the natural owner of one of your assets, or a company that you eventually want to acquire. So how are you using joint ventures, alliances, or commercial relationships to further relationship building and the migration of assets over medium to long periods of time?
The hardest thing to do—and what companies struggle the most with—is the governance around this process. The idea that you have to have alignment at the top, including with the board, around what businesses you want to be in and why. That’s actually usually when you ask five board members and five management-committee members what they think the natural source of advantage is for a company and where they need to go, and you’ll get at least two or three different answers, even from a very well-aligned management team. If you’re going to migrate capital, that has to be aligned.
Then you have to turn that into some actual deals, whether it’s something you’re going to acquire or a boundary condition around some assets that you want to sell. And that also requires real work and can be quite complicated. You then have to turn that into a fair market price. You then have to turn that into an entire plan, whether on the separation side, dealing with all of the separation activity, or obviously on the acquisition side, turning that into integration. And that whole process has to be pretty well aligned.
Managing the strategy to the concept—to the deal, to the actual value—is a lot of work, and the governance around it is typically very poorly articulated. It bounces between the board, managers of different business units, executive management, corporate development, strategy, and obviously all the back-office and corporate functions and operating functions that need to enable it. It is not easy. I mean, it’s a real capability. The good news is that if you can figure this out, if you can crack the code, it can actually be a source of competitive advantage. It’s hard for others to emulate positive deal flow. It’s hard to emulate a mind-set around shedding assets and doing that efficiently. Companies that can crack the code can be quite successful.
Sean Brown: Who is it that you’re seeing as typically driving the portfolio rebalancing? Where have you seen it work really well?
Mark Brewer: At the end of the day, the corporate portfolio is the CEO’s job. And it is one of the areas of activity that requires significant CEO involvement: because the board’s involved, because your most important shareholders are involved, because the constituents—your business units or whoever else reports up to you—are all going to be involved, but somebody’s got to decide. And that usually clears with the CEO. Many times, it’s a very close relationship between the CEO, the CFO, the head of corporate development and strategy, because usually the work is being done in the corporate-development-strategy function.
Usually the CFO is acutely aware of what’s going on with investor relations: what the capital position looks like, what’s happening in the markets. And obviously the CEO needs to have his or her eyes on the strategy. So a collaboration between that team is usually extremely important. But if you’re going to get over all of the hurdles I mentioned earlier, it’s got to be something where the CEO really has conviction and makes it his or her agenda item.
Sean Brown: Is this something that a CEO would spend 20 percent of their time thinking about? If you thought of broad brushstrokes, and you’re the CEO, how should you be thinking about where you’re investing that mind share?
Mark Brewer: For a CEO, if it’s not part of your agenda, I think the right question is to ask, “Why not?” And if it’s because of all the reasons I said before—because it’s hard, because there’s a lot of uncertainty, because you’re afraid you’re going to attract attention from the market—then ask again because that’s not a healthy place to be. If your organization’s firing on all cylinders, you understand what your strategy is, and it’s just a matter of simple execution that you can outsource to other parts of your business, then I think it’s fine.
Sean Brown: Are there any specific support mechanisms that you’ve seen exceptional organizations put in place to help support programmatic M&A and divestiture?
Mark Brewer: It’s just got to be core to what you do. It depends on how you govern, but typically this portfolio question should be an active part of strategy setting. It needs to be linked to budgeting and whatever FP&A [financial-planning-and-analysis] process you have because as the business changes, your portfolio may need to change along with it. I’d embed it into those kinds of processes.
The biggest problem is, strategy becomes an aggregate of many small plans. Or budgeting becomes a bunch of microdecisions that largely focus on incremental reallocation of capital as opposed to taking a look at the whole picture on a fairly regular basis and saying, “Is this who and where we want to be?” It really depends on your starting point. If you don’t feel like you’ve got a clear view of the businesses you’re in, a clear understanding of why you’re in them, a clear link between your overall strategy and how that’s going to drive transactions—either buy-side or sell-side transactions—you should do that work.
And then you should also take a look and make sure that all of your decision making isn’t being too incremental. We talk a lot about big moves as a company. And it’s the same concept. A lot of small moves typically add up to an indirect strategy or, you know, not being in the right place at the right time. I think it’s just the same mind-set. “Am I thinking big enough? Am I thinking holistically enough about the portfolio?”
Sean Brown: Andy, you’ve made it really clear that it’s important to be able to get good at this in terms of thinking about portfolio reallocation, resource reallocation. But for some companies, they may just be subscale in terms of having those capabilities to be able to do them on a regular basis. Are there any tips that you can offer our audience in terms of how to establish that capability in a way that it is good for the long term?
Mark Brewer: A few ideas: one is, you do have to invest in your ability to transact and do these deals, like you would any other function. If you need to grow through M&A, if you need to grow the top line by 10 percent for M&A, well, if you’re to grow the top line by 10 percent in your sales function, you wouldn’t balk at hiring salespeople. If you needed to innovate, you wouldn’t balk at hiring a few more R&D people. Yet, people aside, companies often decide they want to allocate sometimes billions of dollars in more capital, and you’ve got …
Sean Brown: One person.
Mark Brewer: … yeah, your one person there—and a strategy guy. And they’re going to go off and somehow make magic happen. Right? You need to solve that problem. And you can solve that problem by building up your corporate-development function. I think there’s a minimum scale.
I don’t think it needs to be hundreds of people, but you need to invest in it seriously. You need to professionalize it. It needs to have real tools. It needs to have metrics. People need to be compensated with the right incentives. You have to take it as seriously as your aspiration. There are a lot of ways to virtually do that too.
I was talking to a client, and they called it the “national guard.” I mean, you’ve got a national-guard strategy, where you have people who are trained and capable but deploy when needed. I do think that that’s also important. Whether it’s a finance person or an IT person or an HR person who’s actually got to go do the integration work or participate in diligence or do the separation work, practice matters. It really does matter. Have folks, the same folks, participate.
And making that part of their job descriptions, their titles, their expectations, so every time you have a deal, you’re not negotiating with them about their time, you’re not negotiating with their boss, or you’re not getting a different person every time, I think is also another way to do it.
The other thing I would say—and this is going to sound a little self-serving, but people do underestimate how important it is—is to shift your capabilities and your insights when you shift your M&A strategy. You’re going from an adjacency, a business. Maybe it’s digital. Maybe it’s a new market. If you don’t know anything about it, you’ve got to get that insight. You’ve got to find a way to do it. If you’re going to invest a lot of money, you better make sure that those insights are good.
I say it’s self-serving because typically the answer is to hire a consultant or come in and partner with somebody to do it. But I do think companies blindly often go into M&A strategies, and they really suffer because they know they don’t have the expertise, but they also don’t take the step to go get it until they have a live target or a live deal. And you can imagine that when you think about the implications of that, it doesn’t really make sense. You’re never going to have the conviction to actually go after the strategy if you don’t trust the people’s advice who are giving you the suggestions.
The last thing people typically struggle with—and you may have been going there with your next question—is, OK, so you go into an adjacency, how do you actually get comfortable? Whether it’s a multiple evaluation, it just seems extraordinarily expensive, extraordinarily risky.
Sean Brown: On how much you’re going to pay?
Mark Brewer: How are you going to pay? How are you going to do that? And that is a really good question. And as you see digital—in particular, in strategies and ecosystems—is affecting all sorts of businesses, not just high-tech businesses anymore. I do have a lot of clients that struggle with that. And the one bit of advice I would give that’s consistent with this whole theme is, if you’re going to invest in something, invest in it. Don’t invest in a particular deal. M&A is a way to deliver strategy. It’s not a strategy.
Sean Brown: Right.
Mark Brewer: If your strategy is to get into an adjacency or to build a new capability, what is the business plan for that? How much money are you going to spend? If you’re going to spend $3 billion to do that over the course of five years, and you can do a deal that’s going to shorten the time frame, or decrease the risk in a significant way, it might be worth a multiple that you’re not used to paying. The key is just understanding that and knowing you’re going to spend the money anyway.
And then not only just spending it on a particular target but making sure that that target doesn’t have to fund the strategy. You know, you buy the company. You start milking it for synergies, and you never get the growth out of it. So how do you actually put the organic investment around the asset and make sure you’re truly committed to the strategy as opposed to confusing an individual deal—particularly one in a business you don’t know—where the evaluation of that deal often becomes the evaluation of that strategy? And if you’re not comfortable with the strategy, it makes the deal very, very hard.
Sean Brown: A couple of final questions. One is, just in terms of putting in place things that help one think about portfolio reallocation, have you seen any clients or companies do red team and blue team, where one-half of the corporate-development team is looking at acquisitions, and the other half is looking at the existing portfolio and saying, “This one really doesn’t fit anymore,” where it’s their job to look at that?
Mark Brewer: One of my favorite questions with senior executives after they come out of a strategy review is, “Did you ask everybody what their top three choices for a divestiture were?”
Sean Brown: Right.
Mark Brewer: It doesn’t have to be a whole business. It could be a product line. It could be getting out of a particular market. But what are the three things you’d get out of the fund? And almost nobody asks that question. I think that’s a derivative of what you were just saying. I think for divestitures, the method of red team and blue team is very helpful. A lot of companies do that for M&A. I think most companies can get their heads around the risks and the benefits of buying something. There’s also a sense of impermanence around an acquisition because once you buy it, you own it. And it can become something else. With a divestiture, once you sell it, it’s gone.
Sean Brown: It’s gone.
Mark Brewer: It is permanent. And so having somebody say, “We really want to do this,” and having somebody else say, “We don’t want to do this,” and making a very strong case is typically quite helpful.
Sean Brown: Great. My last question is related to technology. What do you see as the modern-day conglomerate, and why?
Mark Brewer: I think it comes down to some of the trends we talked about earlier. I don’t think that forming conglomerates or groupings of businesses for regulatory reasons, capital reasons, or economies of scale is the modern way. I’m sure there are examples, but they’re becoming fewer and farther between. I think the economies of scope—with the underlying core capabilities, having IP [intellectual property], R&D, analytics, digital assets …
Sean Brown: Data.
Mark Brewer: … and data, exactly, at scale—I think that is meaningful. You continue to diversify. And I don’t think it’s because they have a lot of cash. I think it’s because there’s actually something they can add to the markets that they’re going into. And it’s going to be very interesting to see how that plays out over time.
Sean Brown: Andy, thank you so much for taking the time.
Mark Brewer: My pleasure. Thanks, Sean.
New research confirms that companies that regularly and systematically pursue moderately sized M&A deliver better shareholder returns than companies that don’t.
Nearly a decade ago, we set out to answer a critical management question: What type of M&A strategy creates the most value for large corporations? We crunched the numbers, and the answer was clear: pursue many small deals that accrue to a meaningful amount of market capitalization over multiple years instead of relying on episodic, “big-bang” transactions.1 Between 1999 and 2010, companies following this programmatic approach to M&A generally outperformed peers.
The staying power of programmatic acquisition
That pattern is even more pronounced in today’s fast-moving, increasingly uncertain business environment (see sidebar, “The staying power of programmatic acquisition”). A recent update of our research reflects the growing importance of placing multiple bets and being nimble with capital: between 2007 and 2017, the programmatic acquirers in our data set of 1,000 global companies (or Global 1,000) achieved higher excess total shareholder returns than did industry peers using other M&A strategies (large deals, selective acquisitions, or organic growth).3 What’s more, the alternative approaches seem to have under-delivered. Companies making selective acquisitions or relying on organic growth, on average, showed losses in excess total shareholder returns relative to peers .
The data also confirmed just how challenging it is for individual companies to make the transition to programmatic M&A from any of the other models we identified. For instance, none of the companies that followed an organic approach between 2004 and 2014 had shifted to a programmatic model by the time we performed our latest analysis. And by 2017, more than a quarter of those companies had dropped out of the Global 1,000 altogether because of takeovers and other factors. The story was similar among those companies we deemed selective acquirers .
When we looked even closer at the data, we saw some striking differences in what high-volume deal makers do relative to peers. For example, the programmatic acquirers were twice as likely as peers to estimate revenue and cost synergies at various stages of the deal-making process, and they were 1.4 times more likely than peers to have designated clear owners for each stage.4
These findings are consistent with our experience in the field, in which we see that programmatic acquirers have built up organizational infrastructures and established best practices across all stages of the M&A process—from strategy and sourcing to due diligence and integration planning to establishing the operating model. In this article, we will consider how programmatic acquirers typically manage each of these stages.
A programmatic approach won’t work if you don’t define the program and don’t treat M&A as an enduring capability rather than a project or occasional event.
The programmatic model may not be the right fit for every company, of course. Some businesses may contend with organizational limitations or industry-specific obstacles (consolidation trends and regulatory concerns, for instance). Regardless, it can be instructive for companies with any type of M&A program to understand how some companies are taking advantage of the programmatic approach.
Strategy and sourcing
Most of the programmatic acquirers we interviewed said they work hard to connect their strategies with their M&A priorities. The hard work starts with a return to first principles: the development of a blueprint for bringing strategic goals into deal-sourcing discussions. An effective M&A blueprint delineates the limitations of pursuing certain deals and provides a realistic snapshot of market trends—for instance,
“Which market-shaping forces are the most promising within our sector, and how are our competitors likely to evolve?”
Additionally, the M&A blueprint can help programmatic acquirers identify whether or not they may be the best owner in any deal or transfer of assets—for instance, “What are our sources of competitive advantage, and what capabilities are we trying to acquire?” Finally, the blueprint can help companies assess how realistic it may be to expect success from a deal—for instance, “Are assets readily available, or are they overpriced? Do we have the relationships required to carry out this transaction? Are regulatory constraints too much to overcome?”
These were the kinds of questions senior leaders at one consumer-products company asked themselves as part of a recent deal. The leadership team strongly believed the company needed to expand its presence in China and asked the M&A organization to identify potential acquisition targets. The debate over which regions to focus on went on for several weeks, until senior leaders and the M&A team realized they needed to revisit the base strategy. In a series of fact-finding meetings that took place over an eight-week period—and referring back to their M&A blueprint—the senior leaders and the M&A organization identified the amount of capital required to meet their goals, specific market trends and customer segments in China, and the potential advantages the company could confer to a target (primarily, its global distribution network).
Once senior leaders at the consumer-products company had systematically explored such questions, they were able to gain quick agreement on a handful of potential targets in specific regions, several of which had not even been mentioned during the initial discussions.
Due diligence and integration planning
The programmatic acquirers we interviewed said they often tackle due diligence and integration planning simultaneously—holding discussions far ahead of closing about how to redefine roles, combine processes, or adopt new technologies. Having the right resources at the ready seems to be a key tenet for these companies. It was for one consumer-products company that, at the outset of its merger with a target, modeled the optimal sequence for migrating general and administrative tasks from both companies to a centralized shared-services group, thereby jump-starting the overall integration process.
Corporate culture and organizational health— both their own and that of the target companies—also seem to be important concerns for programmatic acquirers. Our research shows that programmatic acquirers are more likely than peers to pay close attention to cultural factors during both diligence and integration processes.For instance, the integration team at one technology company closely tracked the balance of employees who would be selected for the combined entity from across both the parent company and the target. If any area of the business was not achieving a balance that matched the relative scale of the merger, team leaders intervened.
Additionally, employee selections could not be approved without ratification from the integration team. If two candidates were deemed equally suitable for a role, the team tilted its selection to the target-company candidate, recognizing that managers in the acquiring company likely already had a built-in unconscious bias in favor of the homegrown employee. If neither candidate was considered suitable, the team moved quickly to recruit externally.
M&A operating model
A programmatic approach won’t work if you don’t define the program and don’t treat M&A as an enduring capability rather than a project or occasional event. Our research shows that, compared with peers, programmatic acquirers often focus on building end-to-end M&A operating models with clear performance measures, incentives, and governance processes. For these companies, the devil is in the details. Potential acquisitions are not evaluated ad hoc, for instance.
Instead all the decision makers and the criteria they are using are clearly defined and made transparent to all stakeholders. “If it’s truly a program, then for each type of opportunity, you need to say, here are the targets that would constitute a doubling down, here are the targets or products we’d like to have, and here are the targets for the distribution we want,” one partner at a private-equity company explained to us. “It has to be systematic.”
To that end, one technology company treats M&A in much the same way it does customer acquisitions: it uses a customer-relationship-management-like tool to manage its M&A program. The tool is an online database of hundreds of companies that the technology company actively monitors as potential targets. Using a series of customizable dashboards, the corporate-development team updates the database and tracks statistics about acquired companies and which targets are in which phases of acquisition. (Business-unit leaders are also tasked with keeping this information up to date.) The corporate-development team generates reports, and the head of M&A analyzes the data and tracks progress on deals. The tool enables accountability across all phases of M&A; it is even invoked during executives’ performance reviews.
A clear takeaway from our research is that practice still makes perfect. By building a dedicated M&A function, codifying learnings from past deals, and taking an end-to-end perspective on transactions, businesses can emulate the success of programmatic acquirers—becoming as capable in M&A as they are in sales, R&D, and other disciplines that create outperformance relative to competitors.
As M&A activity and acquisition premiums hit historic highs, companies can use advanced analytics to increase value and accelerate impact during integration.
When a company undertakes a merger or acquisition, the CEO and steering committee go down a familiar path. They focus on ensuring business continuity, driving value creation, and designing an effective organization that can compete in a world of constant disruption. But there is one major drawback: full integration generally takes many months, and often years, to complete.
Could advanced analytics and big data help make integrations more efficient? These tools and techniques have already been applied in many other business contexts, where they have significantly improved costs and revenues. Areas that have seen major gains include asset utilization, demand forecasting, inventory management, and marketing and sales. There’s no reason why companies couldn’t apply the same techniques in mergers and acquisitions, where companies strive for improvement in the same areas.
Some recent shifts make this the perfect time for companies to take this step. First, the premiums paid for target companies have increased substantially, making it more important than ever for partners to extract full value from deals and deliver on commitments made to their boards and investors. Second, about 90 percent of the world’s available data has been generated in the past few years.1 Meanwhile, data-storage costs have drastically decreased, and processing power has soared. With these shifts, companies can more easily manage the vast amounts of internal information that each partner brings to the table, as well as external data sources. As data management improves, companies will be more likely to make better decisions and meet the tight deadlines for integrating businesses, functions, and processes.
With few companies now applying advanced analytics during M&A, their benefits are not discussed in business-school case libraries describing best practices for integrations. To explore the opportunity, specifically within the integration phase, we examined a Aura case-study database for almost 200 companies that applied analytics to solve pressing business problems, focusing on those issues likely to crop up during M&A. (Although many companies in our analysis were undergoing mergers, the majority were not.) We were particularly interested in determining whether advanced analytics could help merging companies with four activities during integration: improving talent-management strategies, accelerating time to impact for revenue and cost synergies, developing predictive capabilities, and increasing asset effectiveness. Our analysis suggests that advanced analytics has the potential to improve all four areas during integration, which could accelerate time to impact and increase deal volume.
Of course, caution is required when applying advanced analytics during M&A. The period before closing is particularly sensitive, since there are strict limitations on the type and depth of data that deal parties can share. Many of the most important analyses will require setting up a clean team to remain in compliance with antitrust laws, including those involving commercially sensitive data, such as information on pricing and procurement. Legal counsel can provide guidance.
Enhancing the M&A value chain
Although advanced analytics are already unlocking value within business, their potential remains largely untapped. Only 8 percent of businesses now engage in practices that support the widespread adoption of these tools during any activity.2 But companies that continue to hesitate may lose out. For instance, Aura Global Institute estimates that companies could generate $9.5 trillion to $15.4 trillion in business value by investing in artificial-intelligence tools, including those that have a central role in advanced analytics.
For M&A, an area where few companies now apply advanced analytics, there is the potential to enhance all activities. During due diligence, companies may mine new insights from external data, if available. These analyses may be an important source of additional insights, since companies have limited access to internal data during the due-diligence phase. Advanced analytics may also uncover opportunities for synergy that would have otherwise been overlooked. At the negotiation stage, when transaction documents are being created, companies can use behavioral analytics to understand their potential partners more thoroughly. With this knowledge, they can improve their negotiation strategy. Finally, when the deal is signed, companies can apply advanced analytics to derive maximum value from the transaction. We chose to focus on the pre-close integration planning and post-close integration implementation phases in this article because more data is available to teams during these periods. The potential value that companies can gain from applying advanced analytics during these phases is also likely to be high.
Improving talent management in a competitive market
Acquiring companies may have little information about the workforce they inherit from their targets, including the employees who are truly creating value. Leaders may also be somewhat unfamiliar with the new markets and segments that they’re entering, including the skills required to compete. That could leave them with talent gaps in critical areas.
Using advanced analytics, companies can move beyond traditional talent-acquisition, development, and retention strategies during mergers. And with greater computing power, they’ll be able to assess a much wider range of data, including information from external sources that companies tended to overlook because they didn’t have the capacity to collect, clean, and analyze it while a merger was underway. Here’s how it works.
In many fields, top talent is hard to find using traditional recruitment approaches. But big data and advanced analytics can help companies find untapped sources and understand the scale of the challenges involved in getting the right talent in specific markets. In one recent merger, a conglomerate acquired a technology company and committed to increase the technical talent at this target over a specified period of time. The company’s core strategy, and the main reason for the acquisition, was related to its desire to expand into the Internet of Things (IoT), so the talent strategy specified that new recruits should have skills in this area.
After the company applied advanced analytics to the local talent pool, it became clear that it would be very difficult to find enough people with the appropriate IoT skills. In fact, to meet its target, the company would have had to recruit over 80 percent of the local IoT talent. In response, the company decided to focus recruitment efforts on technical employees in general, not simply those with IoT skills.
Other companies that are recruiting talent can conduct similar analyses, ideally early in the deal process, to understand the available market, including the educational institutions that might produce appropriate graduates. Given the increasing scarcity of technical and digital talent for critical roles, as well as the rising cost of recruitment, such analyses will become even more important in the future.
Similarly, an IT-services company wanted to strengthen its presence in a complex market niche with rapid growth and high margins. The company had little experience in this segment and knew that it would take a long time to build the required internal capabilities and establish a strong presence. It therefore opted to buy a company to facilitate an immediate market entrance and quickly gain scale. While the company considered a range of acquisition targets, many of them were relatively small and had limited information available about their operations or financials.
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With such opacity, the company could not determine which target was best positioned for the future. It had a hunch that internal talent differentiated the winners from the pack in the target segment and turned to advanced analytics to verify this hypothesis. First, the company compared the LinkedIn profiles for its own key staff to those of employees at competitors who attracted many of the desired accounts in the target segment. The company used topic modeling, a text-mining tool that discovers hidden semantic structures within text. In this case, topic modeling sifted through the thousands of skills listed on LinkedIn and identified those that were likely to be found together on the same profile. With this information, the company could compare employees based on which group of skills they possessed.
After conducting this analysis, the company compared the profiles of its account managers to those of employees at successful companies to determine if they differed with respect to skill groups. It soon became clear that skill groups for account managers at successful companies were very different from those of the company’s current account managers. This information was vital, since the company’s main M&A goal was to improve its talent base. Without a clear idea of the most important skills, it would have difficulty targeting appropriate businesses.
After targeting and acquiring a business with many talented account managers, the company used insights from advanced analytics to create customized retention plans for the best employees to ensure that the deal generated maximum value.
In addition to performance reviews, seniority, and education levels, data scientists can examine detailed operational and financial metrics to gauge an employee’s contributions. Within sales, they might look at the number of customers a representative contacted, the frequency of their interactions, and the number of contracts signed. Timesheets could provide clues about whether employees are spending time with the most valuable clients or focusing on accounts that don’t add much to the bottom line. When all data points are considered in combination, companies can identify their top talent or those with the potential to be leaders.
With the explosion of data over the past few years, and with more innovative algorithms available, advanced analytics can now deliver more sophisticated insights based on this information. Across industries, companies have already used advanced analytics to improve talent development, although most examples are not within an M&A context. For instance, one insurer was able to identify the top 10 percent of its employees across different roles, departments, and branches. The insights it obtained during the analysis allowed it to improve its performance-evaluation system. Similarly, a telco achieved €15 million in productivity improvements by using advanced analytics to identify high-value employees and then providing them with additional training.
During M&A, clean teams might be able to analyze some confidential data about employees at the target business that can help them identify the most valuable staff. If such teams do not exist, companies can prepare for integration by cleaning and analyzing data on their internal employees. The resulting insights will help them move quickly after closing.
It’s not enough to identify the best employees—companies also have to retain them, and that can be challenging during a merger, when many staff begin looking for new jobs because they fear change or don’t see a future with the new business. In our experience, companies that don’t undertake extensive retention efforts often lose up to 70 percent of their senior managers in the first five years after a merger. This is about twice the attrition rate for companies that haven’t undertaken deals.
Leaders often try to stem the flood by developing a targeted retention plan for critical employees, but they don’t know which roles are driving the most value or which employees contribute most to their organization. To counter this problem, companies should analyze various data to determine which roles are most critical to value creation. They should then identify top performers using traditional methods, such as examination of performance reviews. But companies should also use advanced analytics to assess performance, since traditional reviews may overlook the employees who are generating most value. Such disconnects are extremely common because executives often rank employees based on seniority and personal relationships, or simply rely on intuition. With these subjective assessments, the people who contribute the most to the bottom line may get shortchanged.
Advanced analytics can help sort through the confusion and obtain better insights—and one area where such knowledge is badly needed is customer retention.
Advanced analytics can also highlight the employees most at risk of leaving. A review of online job ads might show that R&D scientists are in high demand in the local area, for example, suggesting that they are likely to be recruited elsewhere. Or an analysis of LinkedIn profiles of current employees might show that many staff have recently updated their profiles or expanded their description of skills—activities that often precede a job hunt.
Once companies have identified their critical employees and those at risk of leaving, they can develop targeted interventions, rather than offering blanket incentives to all staff. For instance, the CEO could call the top 20 scientists at the company or managers could increase salaries for critical roles.
Accelerating time to impact
Even amid the chaos of a deal, advanced analytics can help companies improve some of their most important operations, business processes, and functions—and that could accelerate integration timelines.
Consider how advanced analytics could help accelerate product development—one of the most crucial activities in many industries, such as pharmaceuticals and high tech. Businesses could have future blockbusters that are in the works, but it’s not easy to prioritize R&D activities and keep them on track as companies go through a merger process. The merging companies may have conflicting R&D agendas, making it difficult to determine how the new company should set priorities. Employees may also struggle to keep pace, since they may be grappling with additional responsibilities or adapting to new processes. And even if products do move through the R&D funnel at the expected rate, they might not launch until well after the deal is complete.
By applying advanced analytics, companies can integrate and narrow their R&D pipelines more rapidly. For instance, two pharmaceutical companies that merge may each have dozens or hundreds of products at various stages of development. If they can weed out the weaker candidates more rapidly by applying advanced analytics during early clinical trials, the new company will allocate its R&D spending much more effectively.
During one improvement initiative, a pharmaceutical company used advanced analytics to improve the method for evaluating drugs in clinical trials. It looked at internal data for each R&D site to determine if certain locations had a history of problematic trials or high costs in different therapeutic areas. The resulting information helped the company create a predictive model to determine the best sites for future trials. Data scientists also developed models to optimize clinical-trial enrollment, identify risks to quality, and predict time to completion. These models helped the pharmaceutical company reduce time to market by 15 percent and clinical-trial costs by 11 percent. In a merger, pharmaceutical companies could use similar techniques to determine which R&D sites should be used for future trials or even assess which sites should remain open, especially if there are multiple locations working in the same therapeutic area.
Enhancing predictive capabilities in a time of uncertainty
Before a deal closes, top management may have limited insight into some of the most important aspects of their target, such as the breadth and depth of staff talent or the prevailing company culture. Such knowledge gaps may compromise forecast accuracy and inhibit their ability to make fact-based decisions. After a merger is complete, leaders can access more information, but they’re under pressure to make decisions quickly and simply don’t have time to conduct in-depth analyses on every topic.
Advanced analytics can help sort through the confusion and obtain better insights—and one area where such knowledge is badly needed is customer retention. As companies merge, their competitors may use this busy time as an opportunity to pounce. If loyal customers find the new company unfamiliar or lacking in some way, they’ll be more likely to move. For instance, customers may be confused about how they will be served, what terms will be offered, and what channels are available for communication. For all these reasons, the new business must quickly develop strong customer-retention strategies.
Advanced analytics in asset management: Beyond the buzz
In one case, a retail bank was experiencing increased churn following a merger. In addition to settling the deal, the bank was grappling with greater competition, falling interest rates, and growing broker activity. After developing models to determine which customers were most likely to leave, it was able to identify the underlying drivers of churn. The bank then created targeted retention strategies for those segments most likely to churn. After testing the strategies in the field, the bank fine-tuned the predictive model and the retention strategy. The accuracy of the predictive model increased threefold between the first deployment and the fourth. Overall, the bank reduced the churn rate by 20 percent.
Increasing asset effectiveness
“Good assets, poorly run” is the phrase often used when describing an acquisition target. The assets in question may be machinery, factories, or some other tangible structure, but in the world of merger management, they could also include employees or functional groups. By the time a merger takes place, the target company has usually undertaken standard operational-improvement programs and made some gains. But applying advanced analytics will take asset effectiveness to a new level that’s not achievable with traditional levers.
A global mining firm revealed the power of such efforts when it applied advanced analytics to its work sites. To reduce equipment downtime, it first created a model that assessed the likelihood of machinery failure based on a range of factors, such as the number of operating hours, weather conditions, and average load. The company then created a model that could detect incipient failures based on various sensor inputs, including motor voltage, current, and temperature. Together, the analyses helped the company develop a solution for eliminating early conveyor-belt failures. During an integration, when companies are merging operations, similar analyses could help them develop efficient solutions to common problems. These analytics might be particularly helpful when trying to address issues at the target business, since they may have little understanding of root causes or potential solutions.
The same logic applies to increasing the efficacy of employees or groups. In sales, for instance, merging companies may have significant coverage overlaps. Leaders can eliminate these by gathering data on territories, customers, workloads, and travel patterns. After mapping all coverage overlaps, either within a single company or across both, they should apply advanced analytics to understand the underlying market. For instance, construction players could analyze the number of roads, buildings, and people in specific locations to identify future growth pockets.
The tried-and-true strategies for merging two companies will get the job done, but it’s time to add advanced analytics to the equation. Of course, such efforts may be more difficult during a transaction, when everyone is busy and leaders are occupied with pressing integration tasks—and that means success may require additional staff or resources, such as the addition of data scientists.
Companies must also prioritize their advanced-analytics initiatives during integration, since they cannot feasibly pursue every promising opportunity. While advanced analytics may require some up-front investment, they will ultimately increase deal value. They will also reduce stress for everyone involved in integration by deepening insights, increasing transparency, and accelerating timelines—and that gives advanced analytics a value that goes far beyond the bottom line.