Sunday, December 2, 2018

TECH SPECIAL...... Tech-enabled disruption of products and services: The new battleground for industrial companies PART II


 Tech-enabled 
disruption of products 
and services: The new 
battleground for 
industrial companies 
PART II
Optimizing R&D processes with tech enablement
With an estimated $8 billion to $25 billion in incremental industry revenue growth, this is the smallest value-creation opportunity of the three. But it is still important, given that traditional approaches to R&D efficiency—peer benchmarks, lean engineering, trial and error—are producing diminishing returns and ceasing to confer competitive advantage. The fundamentals of tech-enabled R&D efficiency are a shift to agile iterative product-development cycles and the rapid deployment of digital- and analytics-based productivity techniques. Consider a typical company where engineers use ten or more systems in a typical day’s work, ranging from timesheets, emails, and project plans to bills of materials and suppliers’ systems. By integrating data from all these disparate systems into a common structure, the company can use machine-learning algorithms to track metrics dynamically and extract powerful insights that provide a fact-based, granular guide to sources
of value.
One aerospace and defense company applied advanced analytics to identify productivity drivers and metrics in its software engineering. It began by creating a data lake that combined data from a dozen or so sources, including the enterprise value-management system, software code tracking, timesheets, and Microsoft Exchange. Then it ran multivariate algorithms to identify factors that correlated to productivity metrics. It found, for instance, that replacing late-stage software testing with early-stage testing using automated scripting would improve productivity by 5 percent.
Finally, the company created a business case and action plan to address target initiatives. This entire process was completed in just 16 weeks, thanks to a sprint-based approach that combined traditional engineering practices with advanced analytics. The company found opportunities to reduce software defects by 35 to 50 percent and increase engineering capacity by 20 percent.
How to capture the value
For all their promise, few industrial Internet of Things (IoT) products have reached full maturity and scale as yet. In our experience, one of the main barriers to adoption is a lack of understanding of how to capture the value of technology. Developing new offerings is only half the battle; companies must also invest in an effective go-to-market approach. This involves two elements:
Knowing where the value is created
Those industrial companies that have succeeded in scaling connected products or data-enabled services understand where the value is created (by direct customers, end users, or ecosystem partners, for instance) and how it is created (through lower transaction costs, improved safety, fewer defects, or some other benefit). This knowledge is fundamental to developing appropriate business, pricing, and revenue models, quantifying value creation, and understanding how much value accrues to each party. For many connected products or data-enabled services, the end user is the primary beneficiary of the value created. Component and subsystem suppliers will need to find a path to monetization that reaches the end user, perhaps via an ecosystem approach or partnership with OEMs.
In upstream oil and gas, for example, the value created by reducing downtime at a fracking site or oil rig is captured by drilling contractors but delivered by a combination of players. Data ownership is fragmented: the drilling contractors control the data from the large equipment they manage; manufacturers of, say, frac blenders own the algorithms and data that generate insights into the equipment and how it works; and component manufacturers, in turn, own performance data on individual products such as pumps. In this environment, creating value will entail forming partnerships with multiple manufacturers and designing a model that enables value to be fairly shared among the partners.
Establishing the right monetization model
Industrial companies can monetize their products directly or indirectly. Direct options include bundling products, launching add-on services, and delivering an offering as a service. Indirect routes include capturing new market share, developing preferred-supplier status with OEMs, and so on. To maximize value capture, companies need to select a monetization model that is appropriate to their position in the value chain and the criticality of the value at stake.
Take the example of an agricultural-equipment manufacturer selling productivity services to farmers. In general, measuring the improvement in crop yield or quality that can be generated by data-enabled farming equipment is difficult, as it depends on multiple variables over the course of the year. However, on occasions when farmers need to harvest a crop within a short timeframe—as with sugar cane, for example—they want their equipment running at maximum productivity, opening up opportunities to create value by optimizing uptime or output. Meanwhile, a component manufacturer in this value chain may find that its best monetization strategy is to develop a preferred position with the OEM.
How to get started
Most industrial companies are still at an early stage in transforming their innovation and product development through technology. Some hesitate to take the first steps, others are stuck in pilot mode, and still others struggle to build a viable business case in the face of traditional development cycles and limited monetization opportunities. But delay could cost companies dearly: late adopters risk not only leaving value on the table but also losing market share to nimbler competitors. A McKinsey Global Institute survey found that being a first mover conferred an advantage of about 7 percent in earnings before interest and taxes—more than double the roughly 3 percent achieved by average responders.
So where do you start? We suggest five steps:
·         First, listen to your customers. They know what they want when they see it, even though they may not be able to articulate it in advance. Invest heavily in customer insights to identify pain points in the user experience, and pressure-test your new offerings with customers to ascertain what they are willing to pay for.
·         Second, place big bets. It’s fine to fail fast, but avoid spreading your investment across too many ideas. Successful organizations prioritize a few big bets that get the lion’s share of management attention. Having identified your big bets, consider novel ways to organize around them. Some tech-enabled industrial companies use a VC-like governance structure with a digital unit reporting directly to a “digital board” comprising the CEO, CTO, and CFO. Such a structure ensures that funding is based on reaching milestones, that issues are resolved quickly, and that the core business stays focused on the core.
·         Third, adopt agile product development. Set up small, autonomous, cross-functional teams that can get close to customers, fail fast, and pivot to the next opportunity. Traditional product development cycles are a recipe for failure, as they can’t keep up with advances in technology and data.
·         Fourth, build out your ecosystem. Commercial as well as technological partnerships are essential to moving fast and scaling effectively. Building and maintaining a robust ecosystem of partners demands dedicated resources.
·         Fifth, establish the right go-to-market capabilities. Selling tech-enabled products is nothing like selling traditional hardware. It requires knowledge of consultative selling, software bundling, and unfamiliar sales cycles and solution architectures. Expecting your traditional sales channels to convert customers quickly or bolting a digital sales group onto a traditional organization could spell disaster. Instead, develop a clear customer interaction model and overhaul your sales structure, processes, enablement strategies, and incentives.

Tech-enabled innovation and product development has the potential to deliver enormous and much-needed revenue growth in the industrial sector. Companies that take a rigorous approach to finding, quantifying, and capturing value—and then move quickly—can expect to see the greatest impact
By Venkat Atluri, Jeremy Eaton, Mithun Kamat, Satya Rao, and Saloni Sahni
https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/tech-enabled-disruption-of-products-and-services?cid=other-eml-alt-mip-mck-oth-1811&hlkid=618679184bf8401282d097408c405f04&hctky=1627601&hdpid=40950bab-bdef-4ff9-9eb4-9ea21456999b

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