CHAPTER EIGHT

CHAPTER EIGHT

There is a division in business today. A digital divide that separates higher-valued digital companies, which were born online and operate in bits, from lesser-valued traditional companies, which were born in the physical world and operate in atoms. Digital companies are not more valuable because they are tech companies; they are more valuable because their technological advancements have a profound effect on business. Digital changes the way we create value, what we create as value and how we monetize the value we create.

The ideal digital operating partner is an interdisciplinary in business strategy, in science and technology and in operations.

Bridging this digital divide is the digital operating partner, transforming traditional companies into digital-traditional companies. The private equity digital operating partner is a senior business executive with deep hands-on experience in strategy, technology and operations. This new PE operating role creates enterprise value for the PE’s portfolio companies by developing the digital investment thesis and then realizing it with a custom digital transformation.

Because of the functional and domain breadth of the role, the digital operating partner is both highly generalized and highly specialized at the same time. Let’s go through the digital operating partner’s unique qualifications.

BUSINESS STRATEGY QUALIFICATIONS

Digital transformation is initiated by the digital investment thesis. This defines the strategy behind making an investment in high technology to create new intangible assets and business models. The digital investment thesis identifies the areas of incremental alpha that can be achieved by increasing sales or expanding margins or ratcheting up the valuation multiple—all forms of value creation; value from innovation and invention, value from operational efficiency and value from new business models and other novel strategies.

To select the digital initiatives that support the digital investment thesis that make up the digital transformation, not only is the digital operating partner required to be an expert in operational value creation and monetization, but because value must be prioritized in context, the digital operating partner must also be qualified to analyze industry dynamics, the competitive landscape and customer needs (Figure 8.1). The goal is to choose initiatives that create the most value and both support and advance the overall investment strategy of the portfolio company.

Figure 8.1 Business Strategy Qualifications

STEM QUALIFICATIONS

The digital operating partner’s second area of qualifications is an all-around education in science, technology, engineering and mathematics (Figure 8.2). This is required to understand, then simulate and then innovate the value created by the smart product, service or environment.

Figure 8.2 STEM Qualifications

Digital transformation starts with understanding. Due to the wide variety of product functionality encountered, an academic background in basic science is necessary to grasp the connecting theory of the underlying physical, chemical or biological processes and their root causalities. Not understanding the theory behind the physical or chemical or biological product is folly, as this is the groundwork for every meaningful digital transformation.

To put that understanding into the context of a product requires applying the science. Applied science or engineering experience is required to appreciate the means by which the product creates value for the customer.

To quantify and then transcribe that knowledge digitally, a universal vocabulary is needed. The digital operating partner needs to not only understand the mathematics (calculus, linear algebra, differential equations) behind the engineering, but to create a digital representation of that value. The digital operating partner also needs to understand statistics, because this branch of mathematics organizes the data in a way that is consumable by data science. The most valuable intellectual property of digital transformation, and therefore of the portfolio company, is its data science models. These analytical or machine learning models are the origin of true incremental digital value.

And finally, developing data science models requires a deep and hands-on competence in technology. Not low tech, like IT and business systems. And not mid tech, like RPA, automation, digital marketing and ecommerce. But high technology like the internet of things, data science (analytics and AI/ML), the digital twin, sensor fusion, additive manufacturing, AR and blockchain, because these are the tech building blocks of any digital transformation.

Gluing everything together is computer science. The digital operating partner should know how to program—to understand in a practical way how science, engineering, mathematics and technology are pulled together and productized.

To be effective, the digital operating partner must gain the trust of the CEO and prove the value of the digital operating partner to the entire management team.

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OPERATIONAL QUALIFICATIONS

Once the digital investment thesis is approved and a custom digital transformation plan is designed, both need to be brought into existence by good ol’-fashioned hands-on execution. This is the third area of qualifications required from the digital operating partner (Figure 8.3).

A digital transformation, like every other business transformation, consists of many small steps. To execute these small steps, in this case, to execute the digital initiatives, requires both hard and soft skills.

Figure 8.3 Operational Qualifications

Hard skills here are the skills needed to deliver a software or data science project on spec, on time and on budget. This comes from experience in developing and delivering commercial digital products. Successfully delivering a digital transformation means hiring external digital teams and building internal digital teams. External teams are hired to quickly build critical mass and onboard the experience needed to get the project started. To be effective the digital operating partner will have a deep and proprietary ecosystem of technical vendors, service providers and subject-matter experts to choose from.

Developing a smart feature or a smart product or a smart service as part of a digital transformation is a technical challenge for sure, but developing any of them within a traditional company, with its unique culture and all its human idiosyncrasies, is a completely different challenge that requires softer skills. Although it’s easier to do this within a buyout-owned portfolio company (see Chapter 7), it is nevertheless challenging and essential to get right. These skills all start with credibility.

The most valuable intellectual property of digital transformation, and therefore of the portfolio company, is its data science models. These analytical or machine learning models are the origin of true incremental digital value.

Digital transformations are not managed; they are led. To be effective, the digital operating partner must gain the trust of the CEO and prove the value of the digital operating partner to the entire management team. The digital operating partner must have the business acumen, credibility and empathy essential to coach the CEO and be approachable enough to have domain-specific conversations with everyone from the functional group heads down to the specialized scientists, engineers and tradespeople. This comes from having done it all before: experience in leading a company or P&L and experience in delivering technical projects to commercialization are crucial qualifications. Not from a consulting perspective, but from the view of authoritative operating experience within an enterprise.

WIDE AND DEEP

The ideal digital operating partner is an interdisciplinary in business strategy, in science and technology and in operations (Figure 8.4). The ideal digital operating partner needs a wide enough and deep enough body of education and experience to make the right choices when creating the digital investment thesis, developing the digital transformation plan and then executing it. This is to have a knowledge canvas large enough to see patterns and connect the dots between disciplines to deliver outsized enterprise value.

Figure 8.4 Multidisciplinary Qualifications

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