Creating a Winning R&D Strategy: Assumptions
Most startups promising advanced tech must invest in research and development early in the company lifecycle, and continuously. Those who do see better growth, as McKinsey reports that a 6% increase in overall R&D spending results in 4% faster growth in comparison to close competitors, leading to improved market penetration. Founders recognize that, while the associated costs here are quite high from the onset, the potential to capture a market with a potentially industry-leading product is worth exploring, which helps explain the 30% increase in overall US R&D spending in the last five years alone.
As R&D is at the forefront of operations for deep tech startups, the difference in execution depends on preparation. There are few approaches to R&D that are exactly alike, but there are plenty of overlaps today when it comes to the underlying strategies. Below are a few assumptions that founders can observe to best formulate their approach.
R&D Strategy Assumptions
1. Innovation Cycles Evolve Quickly
The ability for companies to innovate quickly and more continuously is largely due to improvements in computing power. The emergence of cloud computing helps to improve performance and accessibility while also eliminating costs related to the purchase of equipment or the development of in-house software infrastructure. Most advanced technologies require experimentation, which is a cost sink. But, with the strides made towards process automation, design optimization and product simulations, those costs come down significantly, met with proportional increases in throughput. Also, there is a growing interest in the There is a growing interest in the ‘democratization’ of difficult to imitate technologies only available to large, well-capitalized enterprises, which can result in more stiff competition from lean SMEs.
2. Maintain a Customer-First Approach
Though R&D drives innovation, founders need to connect the product in development to its potential customers, regardless of the length it takes to fully commercialize. Too often, the prospect of creating something that solves a supposed problem takes precedence over actually determining if it fits a market, which results in products that aren’t appealing to potential customers. According to a report by McKinsey, only 25% of deep tech startups actually get a product to market, suggesting an obvious gap between what is being developed and what is needed in the market.
A few founders try to avoid the customer early-on, instead focusing on feedback received from intermediaries, which include advisors, consultants or investors. The insights provided might be useful to an extent, but are based on past experience and aren’t a reflection of the exact customer needs today.
By involving the customer in the research and development process, a startup can more accurately define market shortcomings, refine the full capabilities of the product to differentiate from others, and achieve product-market fit more quickly by incorporating customer feedback and testing. The results of a customer-focused approach to R&D are positive, as Deloitte reports that integrating customer feedback into the R&D process results in a 1.6x increase in customer lifetime value.
3. Favor the Bold
Most advanced tech startups run multiple projects simultaneously, be it a biotech company with more than one drug candidate available for clinical trials, or a semiconductor startup with different approaches to chip assembly. Though plenty of organizations favor ‘safe’ projects that lead to nearer-term returns, aggressively allocating resources towards more disruptive bets has the tendency to deliver high rates of success. This often means holding off on commercializing a product, but the extra time available means the company can refine its innovative project to best satisfy a large unmet need in the market.
For example, in 2019, Amazon launched its first set of smart glass, the Echo Frames. This new product represented a bet on a completely new market for the company. Though Amazon isn’t exposed to near as much risk as a startup with only a few products in development, it nonetheless invested significantly into R&D to develop a completely new product category, resulting in the absorption of market share in quickly evolving AR/VR market.
McKinsey found that only 6% of executives today reported being highly successful in generating ‘disruptive innovation’, suggesting there are plenty of opportunities for new startups to prioritize more ambitious projects that result in high returns.
4. Measure Progress Constantly
Lots of research and development projects lack effective mechanisms to measure progress, where early failures or setbacks are explained away as experimentation, or success is in securing rights to intellectual property and not determining its potential to generate lasting revenue. There are a large suite of KPIs to implement for short-term monitoring and long-term forecasts, with a few listed below.
First, immediate measures of performance include:
Productivity. Being able to measure output is important. To get a handle on productivity, founders can track projects by listing them as not started, in-progress and completed, and as a ratio between R&D spending to-date and what has been allocated to each project, then assessing the priority of completing each project.
Time-to-Prototype; Is a measure of how long it takes to create a functional prototype of a given product, which can help a startup identify development shortcomings or process bottlenecks.
Quality Control; A few different KPIs exist to assess the quality of a product in development, which include defect rates, the amount of provisions in place for testing and quality analysis, and test feedback scores from independent researchers or potential customers.
Technology Readiness Level, TRL; This captures the maturity of a technology, and ranges from early concept stage (TRL 1), to finished product ready for commercialization (TRL 9). A startup can use TRL to set appropriate project timelines and communicate this progress internally and with investors and potential customers.
Collaboration; These provide a window into the effectiveness of collaboration between those engaged in R&D and a variety of other stakeholders, which include sales and marketing. Determining how many cross-functional projects exist, patents are filed jointly with external partners, and the percentage of the R&D budget being spent on external collaborations helps with overall communication of progress and deliverables.
Innovation Velocity; This tracks the speed and volume of innovation within a company, accounting for numbers of patents filed, prototypes developed and new projects and products launched. This metric is all-encompassing, and allows an advanced technology startup to see if it’s continuously generating tangible results.
A few KPIs are also worth identifying early but best reflect long-term projections, which then slowly come to fruition in later years, but serve as important benchmarks to adhere to immediately.
Time-to-Market; Tracks the time taken for a product to go from concept to commercialization, which is crucial as innovation happens quickly in deep tech, so being able to stay ahead of relevant competition is a must.
R&D Spending; Founders usually have a good understanding of the costs associated with R&D, but the totals are always subject to change, and investors want to see discipline with every budget.
Payback Period; For each product released to the market, founders and investors each benefit from knowledge of how fast the project can recapture its costs.