Developing complex products typically requires integrated data sets and end-to-end processes to collaborate across internal teams and supply chains — safely and effectively. Having the right enterprise solutions to manage data creation, access, and change control is essential to driving effective operations and product-development delivery. Enterprise solutions range from advanced, holistic digital platforms (PLM, ERP, MES, SCM) to self-contained specialised apps and integrated toolsets that provide built-in business logic and configurable processes.
For start-ups, the question is less about "which platforms" and more about "when, to what depth, and in what order." Enterprise capabilities that serve start-ups well share a few characteristics:
- Focusing on business capabilities — and driving scalability, flexibility, and analytics from the start.
- Providing automation, simplification, and speed when it comes to finding the relevant information and making informed decisions.
- Low entry barriers. Start-ups don't have the time or budget to launch multi-year enterprise projects — they need cost and adaptive entry (and transition or exit) criteria.
- Pragmatic short-term solutions that can be deployed in weeks or months. A 12-month rollout might feel long-term to a new business.
- An iterative approach to requirements. Start-ups don't have to define everything at once — they can build and mature requirements over time, in a true agile sense.
- A way to learn from operating templates, lessons learned, and the digitalisation experience of established OEMs. Many of the people start-ups bring in carry cross-industry expertise, including return-on-experience and contextual good-practice examples.
Putting together and maintaining the enterprise development strategy and digitalisation roadmap is an ongoing duty — one complex engineering start-ups need to take seriously from day one. It's a means to an end: understanding how business functions and suppliers collaborate, anticipating and mapping data flows across operations and systems, from strategic digital platforms down to niche best-of-breed technical solutions.
Start-ups have the double challenge of building a new business, new product concepts, new operations, new manufacturing facilities, in parallel to developing and implementing new digital strategies. They make rapid decisions to get started, decisions which they [might] have to adjust or undo later as they transition to the next stage of their business lifecycle.Grealou, 2020
Building that roadmap isn't about "engaging in months of planning and research" — it's about summarising and validating "hypotheses in a framework called a business model canvas. Essentially, this is a diagram of how a company creates value for itself and its customers" — focusing on iterative, successive minimum viable products in "quick, responsive development" cycles, as Blank (2013) described.
Business agility without losing sight of the big picture
Start-ups shouldn't settle on half-house solutions. They have the opportunity to start from scratch with the best right-sized option, the more suited niche tools — based on what they can afford — and build on those as they mature. Making the most of digitalisation budgets, investing in the right prototypes to find their marks, and learning and adjusting to nurture product development and production operations is the job.
Funnelling and managing new ideas, innovation, performance, and continuous improvement come hand in hand. Being innovative refers to the "systematic capacity of organisations to successfully exploit new ideas in a commercial context" (Grealou, 2015). Start-ups aim to innovate with their products and services — and with their operating model — by leveraging "a broader variety of sources of knowledge" from their founders and networks, building a people-centric ecosystem (Gruber et al., 2013). Rapid digital and enabling process implementation can make or break product development roadmaps.
Robust enterprise architecture for effective business models
Enterprise architecture is about connecting the dots across business, technology, process, data, and — most importantly — people. Business models matter for both established organisations and start-ups. Ultimately, business models exist for one thing: making a profit. They contribute to how new organisations attract investment, talent, and customers — and to demonstrating that new ideas are viable, that products and services have the potential to create value, and that the start-up can make it happen.
Enterprise solutions are the processes, applications, and technologies organisations use to support their operations across functions, disciplines, product lines, and the development, production, and commercialisation phases. Assumptions and decisions made in a start-up's early days shape how it operates and how it achieves meaningful results. Early manual process definition contributes to building the best-fit solution going forward — requirements captured now can be the basis for future automation or integration. That is: the operating model matures as the business matures.
Assumptions that shape any organisation's behaviour dictate its decisions about what to do and what not to do, and define what the organisation considers meaningful results. These assumptions are about markets. They are about identifying customers and competitors, their values and behaviour. They are about technology and its dynamics, about a company's strengths and weaknesses. These assumptions are about what a company gets paid for.Drucker, Theory of the Business, 1994
Enterprise architecture brings Drucker's "business architecture" idea to the next level of detail. It reaches into all the underlying data, platforms, tools, and integration-related assumptions that concern how decisions are made — and how data creates value across the organisation.
What are your thoughts?
References
Grealou L (2020); Greenfield vs Brownfield PLM Implementations; engineering.com.
Grealou L (2015); Framework to Successfully 'Exploit' New Ideas; virtual+digital.
Blank S (2013); Why the Lean Start-Up Changes Everything; Harvard Business Review.
Gruber M, MacMillan IC, Thompson JD (2013); Escaping the Prior Knowledge Corridor: What Shapes the Number and Variety of Market Opportunities Identified before Market Entry of Technology Start-Ups? Organization Science, 24(1), 280-300.
Drucker P (1994); Theory of the Business; Harvard Business Review, September/October, pp. 95-106.
