Partnerships between digital start-ups and large corporations are an effective way to fast-track digital transformation. For corporations, it expedites entry into new technologies and markets, for start-ups, it provides an opportunity to scale faster than ever before. During this process it is important that technology does not become a proxy for people, and that data is not siloed. What worked for technology partnerships in the past is not a framework for the future.
The growing dominance of digitally native companies and the realities of competing in a digital environment have major implications for traditional companies. Firstly, corporates must re-imagine their core offerings and end-to-end operations, addressing new online markets and reducing costs.
Secondly, there has been a fundamental shift towards the adoption of advanced technologies as core capabilities. If organisations are unable to effectively identify, assess, and harness bleeding edge technology, their competitiveness will be limited in a post-digital environment.
How corporates can innovate effectively by partnering with startups
A recent report by BCG illustrates the critical role of technology in achieving business goals, finding that 80% of companies now deem the acceleration of digital transformation to be a strategic necessity.
Historically, enterprises accelerated their growth by performing the same activities at a larger scale and with increased efficiency. This approach traditionally served organizations well, providing industry boundaries that offered stability for incumbents. Now with the threat of global recession looming, the ability to adapt rapidly and in an agile way to an uncertain future is more important than ever.
As innovation cycles become smaller, traditional models of value identification, experimentation, and digital innovation have increasingly come under pressure. This situation has resulted in scattergun investments, waste, increasing complexity and technical debt.
In response to this growing pressure, companies are leveraging leading-edge third-party products to facilitate rapid innovation at scale, and are looking to start-up technology as a way to make a quantum digital leap. By partnering with start-ups, corporates have the opportunity to supercharge innovation and gain a competitive edge.
For example, Facebook’s recent acquisition of synthetic data start-up, Reverie.ai, may enable it to improve its image recognition and advertising algorithms. However, the technology could also be leveraged to further develop its suite of AI tools, including computer vision, augmented reality, and neuro-linguistic programming (NLP).
At BCG, we believe that the company of the future is bionic, with humans and technology working together. To achieve its full potential, technology must be combined with the flexibility, adaptability, and comprehensive experience of humans. With a next-generation technology stack and tailored strategies, bionic companies can increase innovation and reduce time to market.
Start-ups have a critical role to play in helping companies become bionic while accelerating innovation at scale. Trying to accelerate enterprise innovation at scale while using established technology can solve some challenges, but its success is limited by the fact that they are commodity based. Conversely, start-ups are innovative and disruptive by nature, and can provide corporates with a route to lasting strategic differentiation.
The Perfect Match?
Effective corporate-start-up collaboration is not easy to achieve. Cumbersome processes, the lack of a clear strategy, and poor methodologies for experimentation mean corporates are failing to effectively harness start-up technology. This reality is causing many to miss out on opportunities to create the critical competitive advantage they need.
Large corporates often face compatibility problems when it comes to partnering with start-ups, but this can be addressed by applying the characteristics of a bionic company from the outset. This includes leveraging human talent, modular technology, data, and AI to build personalized customer experiences. Taking this approach also improves the efficiency of operations and increases innovation tempo.
Technology has a big role to play in the realisation of a bionic company, and a key attribute of the bionic company is advanced Data and Digital Platforms (DDP).
BCG’s DDP approach enables organizations to liberate data and accelerate critical business capabilities. It also unlocks data stored in disparate silos and legacy systems by decoupling the data layer from core transactional systems.
Watch Now : What Is a Digital Platform?
In the below image, we outline five impediments to the perfect corporate-start-up relationship, and the bionic solutions that combine technology and people in ways that bring out the best of each:
1. Difficulty experimenting with new technology
Legacy systems impede an organization’s ability to innovate because they lack modern integration architectures and frameworks like SOA. Legacy systems are often not interoperable with start-up technology built on contemporary open stacks, making experimentation difficult and costly. Adding to the challenge, the specific skillset required to maintain legacy systems is different from the expertise required to work with start-up technology, which is built on the latest frameworks and programming languages. The result of this is a technology skills gap between large corporates and start-ups.
Finally, proofs of concept are disruptive to the modus-operandi of IT teams and business units because they demand focus, time, and effort, detracting from other BAU priorities. As such, it may not be feasible or sustainable to conduct the many POCs required to test multiple start-up solutions rapidly and continuously.
When leveraging a modern DDP, data is decoupled and “liberated” from core systems, eliminating the need to integrate with legacy applications that may have challenging technology stacks or esoteric integration patterns. Integration and experimentation with start-up technology can be performed easily using APIs, leveraging the liberated data stored in the DDP data layer. Teams can then focus on testing start-up technologies and products faster, with greater ease and significantly reduced costs that are conducive to rapid experimentation at scale.
Taking this approach also means that there is no need to modify core systems or disrupt BAU IT priorities, because integration occurs within a modular architecture designed for composability. The DDP approach also bridges challenging skills gaps because APIs are standardized. Therefore, knowledge of a niche technology is not locked into a closed group of individuals, and a greater proportion of developers and business personnel can experiment with start-up collaboration.
2. Failure to link new technology to the right use case
Unless there is a sound business case, new technology is often nothing more than a Venus flytrap. This is because companies commonly lack the operational governance to ensure that an investment is effectively exploited across all business units. According to the International Data Corporation (IDC), worldwide cloud spending is anticipated to reach $1.3 trillion by 2025, based on the continued compound annual growth rate (CAGR) of over 21.0% witnessed in recent years.
Despite this stratospheric trajectory, cloud software remains underutilized in many cases.
A recent 2022 report from Flexera indicates that organisations are wasting 32% of their cloud spend annually, up from 30% last year, although the true figures are likely to be even higher. Data provides a clearer picture of this wastage, with desktop software accounting for 31%, data centre software for 29%, and SaaS software for a further 29%.
By reducing the cost and effort associated with integrating bleeding edge start-up technology, businesses can test out potential applications for new tech across multiple business units and use cases. This provides the chance to explore possible opportunities for value creation, enabling the testing of different scenarios until the most impactful applications are identified.
3. Structure, processes and ways of working don’t support start-up engagement
Traditional procurement is not suited to start-up engagement. Common sourcing processes favour large, established tech firms with extensive reference accounts, an army of sales engineers, and well-defined use cases. Meanwhile, start-up technology is commonly filtered for a variety of reasons. For example, there is little to no presence on market research reports, and limited reference accounts or case studies. Additionally, start-ups simply do not have enough staff to compete effectively, and too few personnel to credibly deliver a large-scale enterprise solution.
With a DDP approach, start-up sourcing is accelerated and more agile. Small teams can experiment with new technology to power digital products and services, using modern practices such as Human-Centred Design (HCD). This approach simultaneously reduces risk and time to value from a start-up collaboration, delivering value early and incrementally.
4. Inability to identify and assess value
A key point of failure in corporate-start-up engagement is the scattergun investment in POCs. Just as start-ups must work hard to continually evolve and update their platform, the value generated by a new technology also emerges over time through trial and error. Unfortunately, many companies commonly only attempt a single-scope proof-of-concept, or focus too heavily on testing technical interoperability. As a result, it is very difficult to validate a business hypothesis or prove a business case in a limited, short-term POC.
With a DDP approach, innovation teams can experiment with start-up technologies in multiple composable sub-systems over time, exposing key pockets of value. This approach drives innovation while portfolios of start-up technologies are arranged in sub-systems to create new offers, services, and business models, helping to stave off disruption.
5. Making sense of the technology landscape
This is where a composable start-up engagement platform and modular architecture, powered by a DDP, can address the most pressing challenges of corporate-start-up engagement. Composability describes a system where sub-components can be arranged in multiple combinations to create new systems in response to changing requirements.
Composability is not a new concept, but evolving technology and the start-up ecosystem has made adoption of composability a lot more feasible. Primary examples include APIs, containerisation, and deployment orchestration (Kubernetes and cloud adoption). The result is a shift away from big monoliths to a more global start-up ecosystem.
Today, composability is a foundational characteristic that businesses must develop if they are to efficiently integrate with start-ups. It removes the friction from the corporate-start-up relationship by allowing organizations to introduce or replace technological components, facilitating easy integration and experimentation with early start-up technology.
A combination of bionic and DDP methods is clearly the way forward for digital acceleration. Scaling with third-party products is an excellent way to rapidly innovate, but there is still a way to go for corporations when integrating with start-ups and building growth-stage ecosystems.
By adapting faster than ever to market conditions and major global challenges, companies will increasingly find that integrating start-up technology is critical, especially when it comes to boosting innovation in the pursuit of sustainable value-creation.