OPEX startup as an alternative to the lean startup method

OPEX startup as an alternative to the lean startup method

ISE Magazine October 2020 Volume: 52 Number: 10

By Jiju Antony, Alexandre Fonseca Torres, Marcelo Machado Fernandes and Willem Salentijn



Traditional management is still widely adopted throughout organizations today despite of their nature and size. In this kind of management, a great deal of resources in the form of time and cash are spent in the planning phase of a product or service before the first launch.

This method has provided significant results for companies under stable scenarios – where the market presents a constant and predictable behavior with time in terms of prices, de-mands and competitors – and when there is a great amount of historical data. Under unstable circumstances and new markets, however, traditional management does not present satisfactory results. In fact, it can create a great amount of waste.

The lean startup method was created by Eric Ries in his book, The Lean Startup 2011 as an alternative to traditional management. In his own words, lean startup consists of “the application of lean thinking to the process of innovation,” or a method “characterized by an extremely fast cycle time, a focus on what customers want (without asking them), and a scientific approach to making decisions.” The idea of lean startup is to perform simpler and faster experiments by creating a minimal viable product (MVP) instead of asking customers by conducting surveys. In fact, customers usually are not aware of their true needs and desires, especially when the product or service is an innovation. The lean startup favors experimentation over detailed or elaborate planning, customer feedback over intuition and itlerative design over traditional “big design up front” development (“Why the Lean Start-Up Changes Everything,” Steve Blank, 2013) with the promise of accelerating development processes and new businesses. The experiments provide in-sights on the product that could not be obtained via survey or by talking to customers (Ries).

The origins of lean startup are based not only on the lean manufacturing principles of Taiichi Ohno’s Toyota Production System (1988), but also on the customer development concepts (The Startup Owner’s Manual: The Step-By-Step Guide for Building a Great Company, Steve Blank and Bob Dorf, 2012). A historical literature review on lean startup and on other alternative business model validation methods is found in “Lean Startup: A Comprehensive Historical Review” by Rafael Fazzi Bortolini, Marcelo Nogueira Cortimiglia and Antonio Ghezzi (2018).

The five principles of lean startup include:

  1. Entrepreneurs are everywhere.
  2. Entrepreneurship is management.
  3. Validated learning.
  4. Build-measure-learn.
  5. Innovation accounting.

Although lean startup is primarily focused on startup businesses, this method can be applied in different kinds of enterprises, including large companies (“Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors,” Henry Edison, Nina M. Smørsgård, Xiaofeng Wang and Pekka Abrahamsson, 2018). Even though the lean startup has been gaining widespread popularity over the past few years (“The Influence of the Lean Startup Methodology on Entrepreneur-Coach Relationships in the Context of a Startup Accelerator,” Yashar Mansoori, Tomas Karlsson and Mats Lundqvist, 2019), this methodology still suffers from limited theoretical bases and operational issues that hinder its adoption (“Digital Startups and the Adoption and Implementation of Lean Startup Approaches,” Antonio Ghezzi, 2019).

Within this context, this article aims to start an analysis about the pros and cons of the lean startup method and also to propose an alternative to this method called operational excellence startup, or OPEXS.

Some pros and cons of lean startup

Although the lean startup is a relatively new methodology, it has emerged in a short time due to Ries’ popular books that provide an easy-to-follow approach for entrepreneurs to create radically successful businesses by using continuous innovation. However, Ries also states in his book that, “those who look to adopt the lean startup as a defined set of steps or tactic will not succeed … ultimately, the lean startup is a framework, not a blueprint of steps to follow.”

In fact, lean startup clearly presents some pros and cons mainly due to the fact that it is not a complete framework, as presented by its very creator. The main pros and cons, which were gathered by startup practitioners and researchers, are presented in.

Although there is a general understanding that there is a direct relationship between entrepreneurship, innovation and successful companies (Innovation and Entrepreneurship, Peter Drucker, 2006), the question is whether this also applies for startups. Research on 1,165 Finnish startups surveyed shortly after their entry into the market, Ari Hyytinen, Mika Paja rinen and Petri Rouvinen (2015) found that an innovative approach is negatively associated with startups’ subsequent survival. This effect is magnified by entrepreneurs’ greater ap-petite for risk.

A core principle of the lean startup is the minimum viable product as a means to collect validated data by introducing a new version of a product (Ries, 2011). The concept behind this is beta testing, a technique to release software that is not finished in order to identify missing and erroneous requirements (“Online Experimentation at Microsoft,” Ron Kohavi, Thomas Crook, Roger Longbotham, Brian Frasca, Randy Henne, Luan L. Ferres and Tamir Melamed, 2009). Although companies like Facebook and Microsoft use this technique, for a startup there is the risk of imitation by a competitor (“Experimentation, Learning and Appropriability in Early-Stage Ventures, Andrea Contigiani,” 2019) due to its scale. What works for companies like Facebook and Microsoft does not necessarily have to work for startups.

Lean startups use a “get out of the building” approach called customer development to test their hypotheses (Blank, 2013). However we know that new products have to mature and diffuse over time to get a momentum to spread through a specific group or social system (“Diffusion of Innovations,” E.M. Rogers, 1962). Novelty is even often disliked by customers (“Disruptive Innovation for Social Change,” Clay-ton M. Christensen, Heiner Baumann, Rudy Ruggles and Thomas M. Sadtler, 2006).

Based on research on 250 teams that participated in an American clean-tech accelerator program over 10 years, it was found that having a strong strategy is more important than conducting a tremendous number of market tests (“The Lim-its of the Lean Startup Method,” Ted Ladd, 2016). Instead of direct targeting customers, it could be more useful to use big data in combination with the lean startup (“Combining Big Data and Lean Startup Methods for Business Model Evolu-tion, Steven H. Seggie, Emre Soyer and Koen H. Pauwels, 2017).

While the first step in lean is to identify what is value for the customer (Lean Thinking – Banish Waste and Create Wealth in Your Corporation, James P. Womack and Daniel T. Jones, 1997), in innovation the customer needs time to get used to a new product. Seeking validation for breakthrough ideas can be hard when using customers.

In 2019, authors Arnaldo Camuffo, Alessandro Cordova, Alfonso Gambardella and Chiara Spina (“A Scientific Approach to Entrepreneurial Decision Making: Evidence From a Randomized Control Trial,”) conducted an experiment on 116 Italian startups, with one group being trained in conducting rigorous hypothesis testing and the other group following their intuitions on how to assess their ideas. The group that conducted the scientific approach had the better results. But could an entrepreneur also be a scientist?

Entrepreneurs can be differentiated from non-entrepreneurs on the basis of intention and they are more intuitive in their cognitive style than the general population (“Intuition and Entrepreneurial Behavior,” Christopher W. Allinson, Elizabeth and John Hayes, 2000). Scientists however are data-driven and fact-based. This seems to be a contradiction to the natural intuitive decision-making of the entrepreneur.

Another contradiction in the experimentation of the lean startup are the lean practices which are applied. Lean is about asking the customer, validating in the design and working closely together. One of the key concepts in lean management is kaizen, or continuous improvement. Kaizen is about incremental change. Radical change however from the Japanese perspective is not about kaizen, but about kaikaku (“Kaikaku-Radical Improvement in Production,” Daniel Gåsvaer and Jens von Axelson, 2012). Understanding Toyota and its success is not only about the search for the better way by continuous improvement but also about understanding the contradictions in incremental change and radical change (Extreme Toyota: Radical Contradictions That Drive Success at the World’s Best Manufacturer, Emi Osono, Norihiko Shimizu and Hirotaka Takeuchi, 2008).

The theoretical grounding for the lean startup is thin and mostly based on lean best practices and the customer development methodology. In a comparative study on the impact of the lean startup approach versus a traditional business plan on mobile startups performance, it was clear that the startups were much quicker than the ones with the traditional business approach. However, the question is not whether who was capable of introducing a product first. The question will be if the product will turn from a question mark to a star in the growth-share matrix (“The Product Portfolio: Growth Share Matrix of the Boston Consulting Group,” Bruce Henderson, 1979).

Alternative to lean startup

As an alternative to the lean startup method, we propose the operational excellence startup method. Developed further from the lean startup, the OPEX startup method includes some key tools and concepts from other operational excellence methodologies to address some of its limitations. One refers to the lack of scientific knowledge regarding the experimentation, which includes the hypothesis formulation, the design of the experiments and the confirmation of hypothesis. The authors would also suggest some additional elements to the build-measure-learn cycle proposed by Ries can be considered, including:

Build: Lean startup is more focused on collecting a preliminary voice of the customer in order to build an MVP in the shortest cycle time possible and after presenting to customers. Depending on the nature of the product or service, using a “good-enough-to-move-on” approach can be extremely dangerous. In the automotive sector, for example, robust design is vastly used in order to identify up front the best ranges of operation for the design parameters to minimize the impact of noise parameters that could impact the output performance of the product, especially in the hands of customers. Ries apparently did not consider these scenarios when talking about minimum viable product.

Measure: Design for manufacturability, design for reliability, design for assembly, design for manufacturing, design for environment, etc., (DFX) can be applied in order to avoid high cost on corrective and containment actions when a product or service is presented to the customer even as a pilot or a preliminary version. The closer to the customers, the higher the cost-to-fix a quality problem.

W. Edwards Deming stated in one of his seminal keynote talks that it is more expensive to fix a problem when it is in the customer’s hands. At the same time, it is least costly if we can design an integrated management system that can prevent problems in the first place. This requires long-term strategic thinking and a commitment of leadership for quality and designing quality into products right the first time. Ries did not talk about these tools addressed above when talking about MVP.

Learn:  Well-recognized techniques such as failure mode and effects analysis (FMEA) can provide a more accurate diagnosis in terms of potential risks associated with the product or service that came out of an innovation or continuous improvement journey. Moreover, research has shown that design FMEA is more effective and produces superior results rather than process FMEA. The severity of an engine problem on an airplane is different from a code that did not run properly on a mobile app. FMEA can stratify those scenarios and propose different approaches for each of them.

Finally, there was no mention of organizational learning in Ries’ work, which is necessary to support the implementation of continuous improvement. Organizations cannot build a culture of continuous improvement unless they incorporate organizational learning as a core concept around it.

References: IISE Magazine October 2020 (https://www.iise.org/iemagazine/2020-10/html/antony/antony.html)