Connected, powered, delivered with trust: KPMG’s ambitions for its clients  

KPMG’s approach to digital transformation revolves around the firm’s concept of the “Connected Enterprise,” an organization fully embracing information technology, networking and data to take every advantage of existing and emerging technologies. In KPMG’s view, fully embracing IT requires an enterprise’s transformation efforts be sustainable and cross-functional; that is, not simply transformation to a new state, but an ongoing, ever-evolving change process, executed across an entire company, not simply within one functional area, geography, or line of business. As a comprehensive vision of digital transformation, KPMG’s Connected Enterprise serves as both an aspiration and a road map, particularly when coupled with the expertise, capabilities and experience KPMG believes it brings to clients. During the event, both formally and in sidebar conversations, KPMG professionals reiterated the firm’s commitment to delivery, from strategy and road mapping through advice on funding transformation, based on KPMG’s core expertise in finance, and through to implementation and managed services. Multiple client examples, some described in this report, brought forward that commitment and reinforced KPMG’s strategy-heavy emphasis.

When the firm shifted to emerging technologies, the Connected Enterprise became empowered: According to KPMG, the firm brings clients functional transformation advice, deep industry knowledge and expertise transitioning to the cloud. And underpinning the firm’s core strengths around strategy consulting and emerging capabilities around technology, KPMG touted the trust clients have developed with the firm and KPMG’s ability to reassure clients their digital transformations will be connected, powered and secure. In TBR’s view, KPMG’s framing around digital transformation does not differ sharply from its Big Four peers, with “connected, powered, and trusted” echoing both the structures and themes used by PwC and EY, in particular. In the near term, minimal differentiation may not matter to clients. As these firms all begin to more aggressively court new logos, KPMG may need to find a unique way of describing its digital transformation vision if it has yet to establish enough differentiation.

KPMG may find differentiation with its Ignition Centers, even as the field is increasingly crowded with these kinds of immersion, innovation and transformation spaces. As described in detail by KPMG’s leaders, the 25 globally dispersed Ignition Centers “make technology real” for clients and allow clients to “see what tech feels like” within a KPMG setting, but attuned to the client’s specific needs. For KPMG, these centers supply the engine for the firm’s innovation agenda, providing the culture and the space for an “ideas to outcomes” framework for clients’ people processes and technology. Further, the firm’s leadership described “sensory advantage capability” — the ability to look at markets and trends, anticipate what will be coming, and then draw conclusions, with specific context, for clients — as critical to both the Ignition Centers and how KPMG views innovation.

In KPMG’s view, the firm has developed expertise around reading “signals of change from an outside perspective” and relating those signals to client-specific content. All of this — the innovation, technology and future sensing — enables KPMG to translate clients’ needs into strategy for a Connected Enterprise, deliver a detailed and tech-supported road map, and then implement the digital transformation.

As with the firm’s overall framing around digital transformation, TBR cannot be certain the Ignition Centers differ substantially from PwC’s Experience Centers, EY’s wavespaces or the 20-plus other centers TBR has visited in the past three years. In discussions with KPMG professionals around client selection and preparation, staffing and talent management, and technology partner inclusion within the Ignition Centers — all concepts researched extensively by TBR — no substantial differences emerged, suggesting KPMG has at least kept pace with the evolutions to date, if not necessarily leading peers in developing new ways of leveraging these centers.

In mid-June, KPMG hosted more than 50 analysts for an extensive series of large sessions and breakouts intended to showcase KPMG’s capabilities, offerings and innovations. With multiple clients on hand for both the opening dinner and presentations across the following daylong session, TBR had the opportunity to hear why clients select KPMG and the different digital transformation challenges KPMG has addressed. TBR also met one-on-one with KPMG leaders and partners, hearing directly from them the firm’s overall strategy, internal metrics, and sense of where KPMG fits within the consulting market.

TBR believes that creating common terminology and understanding around data is key to successfully implementing an evolutionary digital transformation strategy, one that enables the organization to transform incrementally, as it capitalizes on new opportunities and deals with new challenges. Essential to this approach to digital transformation is an organizational cultural transformation, one that embraces continual innovation and ongoing collaboration across departments and disciplines and that enlists all parties in the process of harnessing organizational data assets to move the organization forward.

The many uses and users of data

It is commonly accepted that IoT represents the intersection of IT with operations technology (OT). This is true, but only part of the story. Business management is another key player in many projects, and TBR believes it should be a component in all IoT projects. In fact, potential users of data from IoT projects extend beyond these three stakeholders, including many of the departments throughout an organization, such as marketing and sales. To deliver the greatest possible value from any project, including but not confined to IoT, all the potential users of the data should be considered in the design and evolution of each project.

In the early stages of the recent surge in IoT, three to four years ago, the different stakeholders were often brought together for workshops or ideation sessions to invent new solutions made possible by IoT. As IoT has become more common and relevant players are more familiar with common use cases such as status monitoring and asset tracking, there has been less need for this challenging and expensive invention phase of IoT projects. Instead, new projects are often undertaken entirely or almost entirely by OT, sometimes working with IT to ensure compliance with company standards. These projects can confidently deliver a positive ROI while only using data for a single purpose, usually operational efficiency. Potential other uses for the data, or from data that could be generated by the solution, are often not considered in the design. This can be a waste.

The data generated from an IoT project often have value beyond the immediate purpose of the project. For instance, data from a status monitoring solution can be used to identify patterns that could predict service-related incidents. Similarly, comparing status reports across different assembly lines or factories might help identify superior or deficient configurations. Status reports could be correlated with operations speed to help identify either capacity problems or the potential for greater capacity. Capacity limitations or windfalls affect both marketing and sales.

The same kind of potential repurposing of data can be found for most IoT projects. Data has multiple uses. Different people within the organization are able to recognize different potential uses. Uses can be classified into short term and long term. Status data is valuable immediately. Indeed, for the purpose of reacting quickly to status deviations, the data has no long-term value. A solution built for only that purpose would often discard the data to minimize project cost, resulting in a loss of the potential value of the data for long-term analyses. To extract the greatest value and meet broader organizational needs, other people in the organization should be involved in the project design.

Manufacturing scale matters less as we pivot to a knowledge economy

Economies of scale as a barrier to entry have been a fundamental precept taught for years in economics classes worldwide. Capital had to be invested ahead of being able to create value, and then people could be hired to staff the capital equipment to produce goods. Having both capital assets and existing volume gave companies a distinct competitive advantage. It drove both vertically integrated companies as well as horizontal holding company models, with the latter made famous by Jack Welch’s oversight of U.S. blue chip company General Electric.

Technology today has greatly reduced scale as a competitive advantage. Virtualization and abstraction have led to business theorists talking increasingly about asset-lite business models and asymmetric competition. Clouding this pivot is the emerging discussion around consumer scale. This is a competitive edge gained not necessarily from capital scale, but by capturing consumer brand loyalty that generates the scale. This concept is often discussed as the “force multiplier” or the network effect of the ecosystem. It is giving rise to additional new terminology, such as multi-enterprise business networks, in which partnering and the joining of complementary assets enable all participants to benefit from the aggregation of intellectual property, which is fed to the entire ecosystem of loyal customers.

Humans have the big ideas; curating those ideas into scalable advantage requires technical skills, automation and patent protection

When consumer loyalty generates cash, that cash can be deployed to fund projects, such as small-scale, smaller-dollar-volume projects akin to becoming an internal venture capital (VC) arm for any future product and service innovations. This concept manifests itself in the notion of fast failure and rapid iterations that are anathema to scaled manufacturing best practices. Being successful requires having people who are insightful about what businesses or consumers want and how to turn those wants into an automated piece of software — in short, algorithms.

As virtualization and software abstraction move the economy ever closer to utility computing, first discussed in the late 1980s by technology futurists, and as quantum nears economic advantage, the mission-critical business competency will be writing algorithms to apply against the ubiquitous data traffic being generated and stored throughout the computing utility network. Faster compute leads to faster exploration and discovery. Faster discovery leads to shorter product and service cycles and therefore shorter competitive advantage windows.

As such, algorithms that generate these new insights will increasingly become the way enterprises generate wealth, as well-skilled individuals push the limits of conventional wisdom and then deliver these new insights. Preserving that ever-shortening advantage will come from increased vigilance in protecting intellectual property. Thinking and creativity provide the advantage. We hear time and again at analyst conferences about how skills are in short supply and how people are a firm’s greatest asset. TBR expects to hear more frequently about the patent protections around these automated ideas.

Clean blockchain data fed to quantum will accelerate the value of algorithm patents

Accurate data will be available in real time for these algorithms to run against to generate real-time decision-making guidance. As automation removes more and more human toil from the economy, only individuals at the point of creation or the point of consumption will be critical to the business, with the algorithms mining the consumer demand to test against the next big idea to come from well-skilled humans and converted into competitive advantage through an automated algorithm run against real-time, accurate data.

As explored further in TBR’s Quantum Computing Market Landscape, in the quantum computing realm, where insights and actions can be obtained exponentially faster, the IP advantage is also exponentially greater. Think of the traveling salesman example that comes up regularly in quantum conversations: If a delivery company can patent an algorithm that speeds up delivery rounds and makes deliveries more efficient overall, that could swiftly create extinction events in the delivery market. If we extrapolate this, emerging technology has the potential to fundamentally alter competitive landscapes by generating faster and more accurate insights.

TBR analysts will be attending the Quantum.Tech conference Sept. 10-11 in Boston. Please contact your account executive to coordinate a conversation with TBR analysts at the event.