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For Superior Returns, Private Equity Should First Look To Technology

By Christopher Steiner

Mergers & Acquisitions

Private equity has many options available to improve a company's operations, but the first play should almost always be on the technology side, where most companies can expand enterprise value 10% to 15% with quick wins.

For Superior Returns, Private Equity Should First Look To Technology

Cash has poured into private equity at increasing rates during the last decade, hitting a peak of $243 billion in committed money in 2017. These large reserves have enabled the best PE investors to build dynamic portfolios with complementary parts, but this abundance of capital has also kindled major competition for the best acquisition targets.

Winning deals in the current climate requires paying multiples on earnings that are higher than historical norms. With larger multiples on the front-end, seeking superior returns becomes more difficult. Simply riding out market trends won’t produce returns that compare favorably with the last vintage of funds.

With this in mind, private equity operators should carefully examine every dollar they put into a portfolio company. Capital should be concentrated on items that can multiply proprietary advantages and lever up the value of the company’s best people.

Given the business, there may be a few routes in which to do this, but there is one path that is almost always available: implementing best-in-class95% enhance your companies value by tightening technology integrations technology. Based on more than 250 technical and commercial diligences Liberty has carried out during the last two years, more than 95% of companies can greatly enhance their value by tightening technology integrations and putting the right platforms in place.

Using technology, companies can come closer to something Liberty refers to as digital synchronization. Driving further down the road toward digital synchronization is the most dependable way to increase margins, raise product efficacy and build enterprise value.

Most enterprises can expand their enterprise value 10% to 15% by achieving reasonable levels of digital synchronization. These results come from increases in EBITDA tracing to better productivity—fewer employee hours required around many operations—and better and more responsive experiences for customers, which helps fuel sales and reduce churn.

In short, smart applications of technology will almost always offer the best way of putting incremental capital to use in a portfolio company. With the right technologists and operators, investments here will lead to better yields.

Real World Examples

We have seen the results of this strategy borne out in an array of fields.

Leveraging up logistics:

Liberty worked with a logistics company that, through automated matching of loads, drivers and location data, was able to double the productivity of its operations staff compared with the average in the field. Needless to say, this company fetched an outsized multiple at exit not only for its superior margins, but the IP around the methodology that earned those margins.

Bridging the human-software divide:

Another successful implementation of these tactics came from a business that carried out in-home health services. Before technology intervened, scheduling hundreds of therapists required a full-time scheduling staff of 35 people at this company. By migrating to newer and unified data fields across several applications, the company was able to create a master scheduling engine that was flexible with many disparate sets of rules according to thousands of clients and therapists. On-demand algorithms took over the laborious process of scheduling and provided quick turnarounds on appointment requests, and therefore improved customer satisfaction and retention. The scheduling team, as a result, was pared from three dozen people down to five.

Big Pharma Data + Apps:

Companies in the pharmaceutical and healthcare industries can be faced with innumerable sources of data. Normalizing that data and getting it all into one place can positively impact EBITDA by tens of millions. Liberty worked with a national distributor of pharmaceutical products to merge all of its data and application outputs into one place that would give the company a clear view on spending, inventory on hand, and its responsiveness to customers. The work yielded a 5% improvement in productivity and decreased necessary inventory levels to two days, vastly improving the company’s relationship with working capital.

Automated lead generation to CRM:

One of our favorite examples of this work comes from a logistics company that configured its software to automatically add each recipient of a shipment, inputted by the company’s clients, to a master CRM. Then, custom-built algorithms ranked each new entry potential as a new customer using a number of fields auto-populated by web scrapers. This process basically eliminated the need for any other (and costly) lead discovery and kept the company’s sales team with as many targets as it can handle.

Notice that this isn’t about new servers, faster connections and new laptops (although those things are nice). It’s about achieving data harmony across all facets of business, squeezing out laborious processes, and injecting analytics into every decision.

Achieving digital synchronization across a company’s entire footprint offers the best path for a middle-of-the-pack performer to become a market leader that can produce better returns on capital. These superior margins can help further dominate competition, pushing up EBITDA, future valuations, and investor returns. Portfolio companies that don’t already view technology in this way may well be lapped by competitors who do.

The Four Stages of Digital Synchronization:

Investors can identify their portfolio companies as belonging to one of four evolutionary stages on the road to digital synchronization, from least sophisticated to most. Market shares of each stage are based on more than 250 technical due diligences carried out by Liberty during the last 24 months:

Stage 1 – 25% of the market: Companies with many manual processes still in place. Website may include lead capture, but disjointed back-end data systems limit productivity throughout the enterprise. Jobs have been created and continue to exist for sole purpose of bridging gaps between processes.

Stage 2 – 50% of the market: Connections have been made between different applications, and data flow between systems without human assistance. CRM to ERP connections exist; field techs have direct views and inputs into data systems. These companies have done much of the foundation work to reach stage 3.

Stage 3 – 20% of the market: Full integrations across platforms. Leads seamlessly transitioned to prospects, then to customers. Marketing automation is enabled and integrated. Scheduling of services and billing are all connected. Onerous keyboard work is automated. Data warehouses, analytics in place.

Stage 4 – 5% of the market: Data science is brought to bear not only around analytics, but also for real-time decision making. Data doesn’t suggest decisions—it makes decisions. This stage requires engineers with deep understandings of data science and AI. Customers can be parsed and sorted as they come in the door.

Driving Toward Stage 4

Investors can likely recognize where many of their portfolio companies fall within these four stages.

Portfolio companies in stages one and two should be viewed as opportunities. The best investments often come in the form of companies who know their space and business well, and therefore offer an excellent product, but who have not yet connected the dots to reach the upper stages of digital synchronization, which gives the business true leverage.

Technology offers these companies a road to larger market shares, bigger margins and a better platform from which to leverage their superior products. To get to this point, there are four areas on which company leaders must examine, evaluate and improve:

1.Data Structures, Hygiene:

A digital synchronization strategy won’t work if a company possesses incongruent data across different arms and applications of the business. It’s this kind of disconnect that leads directly to painful processes that cost companies time and money and drive down the efficacy of employees.

Plotting out what a master data structure should look like and then implementing this across a business where disparate data may be present is often the most troublesome step for companies looking to hone their operations with technology.

And just as all of the company’s data should be consistent, it also has to be clean if it is to be depended on to run and inform critical processes across the business.

Settling on a data structure is step one. Cleaning the data, which is a laborious process requiring all kinds of script-driven and human-driven exception handling, is step two. This is the ugly end of digital synchronization and it involves necessary grunt work. With this done, everything else, from a pure technology standpoint, can be wheeled into place.

2. Core Business Applications:

Before anything else happens along the road to digital synchronization, a team with a combination of operating and technology experience must examine the business, its core processes, its major machinations, from marketing to sales to customer service, and form a comprehensive view on the technology required to best run, grow and improve the business.

From here, the team must plot a course for migrating the company from its current technology stack to a state in the future that will facilitate digital synchronization, which will lead to larger valuations. The team must be flexible with the systems already in place; the costs of moving to new platforms, be they bespoke or off-the-shelf, must be weighed against the opportunity.

The tech-operator team will then produce a detailed roadmap for how the business’s technology backbone will fit with the core values of the company and its products. The roadmap must be vetted with an eye toward ROI, future flexibility, the automation of processes, and the inclusion of data analytics in business decisions.

3. Personnel:

The steady migration toward digital synchronization will require people with skill sets focused on the kinds of applications and data manipulations called out in the roadmap.

In many cases, the company may already have the right personnel in house. Good teams can adapt, even if their experience with particular proposed applications or a software system isn’t deep. What there has to be, however, is a willingness to adjust and integrate new technology without the carryover of dogma.

The separation of evaluation and planning, which may be done by a third party, from the actual execution on the tech front, can be healthy. It is not an indictment of the current team that the company’s systems can be improved; many technologists know this to be the case, but they simply aren’t afforded the time to gain exposure to all of the solutions and methods available to them.

In the case that the right personnel aren’t on hand, then a plan built around consultants or recruiting new talent must be put in place. With this in mind, a way of executing on the digital synchronization roadmap should be devised that isn’t limited by the current staff.

There are lots of jobs—such as data normalization and scrubbing—that can be farmed out at reasonable rates. Progress toward digital synchronization needn’t be a monolithic undertaking. Pieces of it can be picked off as necessary and as resources are available.

4. Analytics, Data-Informed Processes:

As the first three pieces of digital synchronization come together, this last and perhaps most rewarding piece of the bunch can be erected. Data-driven processes are impossible without consistent and clean data across all of a business’ vital applications.

This piece requires know-how, but the execution leg of this can be fairly straightforward if the foundation has been set ahead of time with the company’s data and applications. Good data analytics are driven by the work that went into building the foundation of the company’s data schema, and the prime sources of the data.

Even on the AI front, there exist playbooks that can be run, algorithms that exist, if the data is in place. Any experienced AI hand will attest that 70% to 80% of the job is cleaning up and normalizing data. If that part of the job is already done, then the path to getting granular, value-added, non-intuitive takeaways—the best kind—is clear.

For these things, there exist a host of high-quality canned applications, such as Tableau and Thoughtspot, that can add a lot of value. It’s usually the case that a company should build out a dedicated data warehouse that can function in parallel with its operations, serving as a separate feedstock for analytic and data engines. This is, again, a fairly straight-forward process once the data exists in a clean format across all instances at the company.

Getting on the Road To Digital Synchronization

This task breaks down into three parts: pattern recognition, prescriptive planning, and execution, plus a dose of QA.

Even the prickliest problems concerning a disconnect between a company’s operations and its technology systems can be diagnosed fairly quickly, with a solution prescribed in a matter of weeks. This is all the more possible when the prescriber has witnessed, documented and helped fix similar situations.

For instance, a company experiencing problems connecting real-time production data to an ERP might find the challenge daunting. But others have seen this kind of challenge many times, and have the right experience to help construct a prescriptive plan to address and upgrade the company’s operations with technology.

Execution comes down to having the right people with hands on keyboards, but it also means getting buy-in from the key people across a company’s sectors, from those on the factory floor, to those in IT and accounting. A lucid explanation and plan must be put together that explains why the planned technology solutions will make the company better, employees’ jobs better and, ultimately, create more enterprise value for all stake holders.

Taking the leap as a solid company with average systems to a dynamic one with technology that supports growth and innovation isn’t simple, but it’s the most proven path we’ve witnessed to outperforming the market and getting more yield out of a business and its existing expertise.

When the private equity funds that are currently acquiring assets look to divest, there will be a stark divide in returns from those who embraced technology and used it as a business force multiplier, versus those who simply stayed on their stale paths, viewing technology as a necessary cost versus the business jet fuel that it can be.

Christopher Steiner is a principal in the M&A practice at Liberty. He is a New York Times Bestselling Author of two books on technology, a Y Combinator alumnus, and the founder of ZRankings.

Liberty Advisor Group is a mission-focused advisory and strategic consulting firm. We partner with our clients to solve their most complex business issues and improve enterprise value. Our experienced team has a proven track record in Business and Technology Transformation, Data Analytics, Business Threat Intelligence, and Mergers and Acquisitions. We offer original thinking combined with factual data to develop comprehensive, situation-specific solutions that work. With straight talk and proven results, we accelerate growth, drive efficiency and reduce risks. We are experienced. We are doers. We are Battle-Tested.

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Christopher Steiner By Christopher Steiner