The Business of Accelerating the Acceleration of Startups
Business Accelerators dangle the prospect of impact and success to startup company founders, but what is their value-add effect?
The cross-domain and cross-border aspects of the Business Accelerator sector has resulted in an ecosystem that has seen actors in the space jostle for clear and competitive positioning. The evolution of Business Accelerators as a business entity, seeking to supply positive interventions to the journey of start-ups, is common to all growth and innovation orientated ecosystems. The ability for Business Accelerator managers to demonstrably impact their subject accelerate startups positively has been an under-researched area in the Asia-Pacific region, where research to date is largely dominated by descriptive research that limits universal conclusions.
Against this background is the rising volume of capital being channelled into funding startups due to the widespread drive for innovation led growth which is increasingly the cornerstone of industry policy in many countries. With there being over 3,000 Business Accelerator programs existing in conventional markets, an estimated 60,000 startups each year are graduates of startup programs. Whilst this is clearly a material number, by comparison to total estimated startups it is a fraction of the estimated 1.7 million startup companies that were registered in 2017 in G7 countries alone.
The key focus of this article is to thus explore if the success levels of Business Accelerator programs can be clearly demonstrated. The underlying hypothesis is that the outcomes of Business Accelerator programs are superior to non-accelerated startups. With the increasing levels of public and private funding and resources being channeled to startups and thus Business Accelerators, the opportunity for ongoing accountability and optimisation of the allocation of resources is clear.
Business Accelerators: The Current State
Business Accelerators are summarized as 3-to-6-month programs that provide a business service that purports to accelerate strategic execution. The service typically encompasses business pitching, planning, service/product refinement, execution acceleration regarding further refinement and commercialization through customer and potential shareholder engagement. Cohen (2013). The marketing of “business acceleration” is in contrast to the services of an Incubator program, which is generally a program of longer duration, and usually with less of a planned curriculum and less (or no) emphasis on actual commercialization or fund raising.
The proliferation of business accelerator programs and the coveted achievement of being selected into such programs is an accepted element of established innovation ecosystems for aspiring startups. Startup managers are motivated to seek a boost to their prospects through business model refinement and operational execution; and choosing an acceleration program to accelerate the path to success is a common route many founder teams seek. In parallel, accelerator programs are constantly challenged with the need to market their service offering to potential startups in order to win their interest, and to have them apply to the program. That is, Accelerators need to have a developed pipeline of prospective startups that want to join their program.
An added operational challenge for acceleration program managers is that BAs are often startups themselves given the short history of the sector and the recent rise in the launch of BA programs. These multiple challenges are shaped by resource procurement challenges and an increasing need to appeal to a wider range of potential startups, resulting in the need to balance: (i) usually minimal internal resources; (ii) the use of pro-bono external resources and; (iii) a cohort-intake of startup companies which may vary markedly in their industry focus, service or product offering and their relative maturity.
The service provided by Accelerators is usually a commercial bargain, with an exchange of equity participation granted by the startup to the Accelerator for the privilege of participating in the acceleration program as a selected member. The provision of BA services can be seen as a natural experiment, with a conscious choice of a startup seeking an Acceleration program, and the BA management seeking suitable participants to join its program and receive its services. An intervention view of how Accelerators interact with startups, given the stated objective of assisting in commercial success provides a strong cause-and-effect situation for research purposes. The defined period of Accelerator programs, often between three to six months duration with distinct onboarding and off-boarding events further underlines the finite intervention period of such programs and thus provides an opportunity for measuring impact in a temporal sequence. Understanding the independent variables that may (or may not) foster successful outcomes is the basic purpose of this research.
Research Method and Data Analysis:
The research design of this project had in mind the goal of wider universal applicability given the globalising nature of this industry due to the increasingly borderless dimensions of human talent, supply chains, investment capital and intellectual property. As such, the population of sampling is essentially universal in its approach, with a noted focus on Singapore (ASEAN) and Australia
The research followed a mixed-methods research approach to gain insights into the impact of Business Accelerators on startups. A survey of a sample of accelerated and non-accelerated companies was conducted to explore their impact on performance outcomes. The study further explored six dimensions of managerial activities and capabilities to understand if these dimensions could explain observed differences in performance. The analysis concluded no significant differences existed in the performance outcomes of accelerated versus non-accelerated startups.
Phase 1 and 2 Data & Results:
The research had three phases of data collection, following on from an extant review of current industry views and academic research on this topic. The first phase explored initial hypotheses and current accepted practices to corroborate or otherwise the salient features of such programs. This then became a basis for the distillation of the second phase of data collection, being (i) a comprehensive survey that collected objective descriptive data regarding startup company profiles, and performance levels on a temporal basis regarding client traction, revenue and fund raising. Startups that were less than 5 years post incorporation date was one key selection constraint. Additonally, this data phase also collected (ii) behavioural replies to six independent variables which are commonplace in the startup and entrepreneurship literature. These six variables each had detailed behaviours and practices selected and/or adapted from existing robust research to be proxies for these domains of practice. The 40 detailed questions of this aspect of data collection was centred on a Likert scale approach to measurement and then analysed via the SPSS software post data cleaning that ensured the veracity of data collected. The 6 variables researched were: Market-centricity; Execution-orientation; Network-orientation; Business Management Expertise; Entrepreneurial Spirit and; Technical Expertise.
The analysis of the data in turn incorporated a classification of replies into (i) Accelerated vs Non-accelerated and (ii) classified Success vs Non-Success (to-date) dichotomies. The Success vs Non-Success (to-date) was based on an objective assessment of the descriptive performance data collected. This researcher’s classification was done with reference to a combination of practitioner standards and researched papers that studied practitioner assessments. These notably included the Global Accelerator Learning Initiative (“GALI”) criteria out of which ranks Accelerator performance based on the 5 criteria of:
1. Help ventures gain market traction
2. Support leadership development of entrepreneurs
3. Connect ventures to investment opportunities
4. Drive economic growth and job creation
5. Spark innovation in a certain sector
The initial classification of Success vs Non-Success was then moderated against the independent classifications of the same dataset by 3 experts in this domain of startup investing and management.
The analysis of the data set (Population sampled = >1,000; n = 68) saw the following testing conducted: (i) a comparison of means was conducted in analysing the variables between Accelerated vs Non-Accelerated startups and; (ii) a Chi-square test to test if there was any statistical difference between the Success vs Non-Success outcomes, with reference to them being accelerated or not accelerated.
The above mean comparisons, T-tests and Chi-square tests indicate no statistically supported relationship between Success and Non-success companies, when considering the acceleration effect or otherwise. Thus, the sampled data inferred that acceleration has no statistically material effect on if startups get classified as successes or otherwise.
The statistical effect of the 6 independent variables is also concluded as not significant.
A review of the straight means and the independent T-test indicated that Execution-orientation was the closest variable to having statistical significance, given the p-signal of 0.052. If this result is considered conservatively, it would warrant further review given it is on the threshold assuming a 95% confidence interval.
Phase 3 Data & Results:
A further phase of research built upon these findings by selecting two companies that had been through an acceleration program, one being classed as successful and one unsuccessful. Case studies involving interviews of the founders and members of the accelerator program management were then conducted. In addition, a review of other materials including program materials to distil key factors that contrasted the companies and their experiences with acceleration programs was conducted. Whilst the data analysis did not highlight any difference in the success rates of sampled startups between those accelerated and those not subjected to an acceleration program, the association of Business Accelerators with successful startups is a fact. A review of all mature Business Accelerator program marketing materials and websites will attest to the (self-declared) successes that this research has objectively studied. Thus whilst the collected data did not support any higher rate of success for accelerated startups, a case study of a sample of successful and non-successful startups that have been accelerated is a valid third research step that may add to the body of knowledge given the preceding.
The research sought out two companies that had been through a business startup acceleration program as case studies. In selecting potential examples, due regard was given to profiling potential cases that would be representative of companies that participated in a representative acceleration program. For the purpose of enabling a contrast in the cases, the research targeted one case study that profiled a “success” company and another which profiled a “non-success” company. Hakim (2000) outlines the spectrum of possibilities with regard to how case studies may be used to assess the evidence for a particular conclusion. This may involve studies of the “most favorable” illustration of a case that supports claimed knowledge. Alternatively, a focus on a ‘deviant’ case, “which suggests that the exception disproves the rule, or at least proves that the general rule needs to be re-defined as applying only in certain circumstances” (p. 60)
A further consideration in the Phase 3 data collection approach was to ensure the key directional conclusions around: (i) the importance of Execution-orientation in attributing to success (or non-success) of accelerated startups and; (ii) the broad challenge of accelerator programs being able to focus their program interventions through their curricula on topics that confirmed the improved chances of success for their startups.
The approach to these interviews was as guided by Hakim (2000), Creswell (2003) and Yin (2009), where multiple sources of evidence was sought and interviews were crafted around open questioning that explored the Phase 2 conclusions. Emergent themes were identified, coded and linked to theoretical themes to enable a conventional ethnographical approach in analysing such data. These linked theoretical themes (and the underlying transcribed interviews) were in turn highlighted and shared with interviewees to obtain corroboration so as to ensure further veracity.
The summary findings of these case studies suggest that Business Accelerators can have a positive impact on companies by focusing founders on prioritizing a detailed execution-orientation, including regular communication with all stakeholders in the program. Experienced key program resources such as the Entrepreneur-in-Residence and Program Managers, suitable mentors and open relationships with fellow cohort startups were noted as sources of intervention which could impact success. Conversely, a lack of emphasis in these key program resources and processes reflect environmental conditions that challenge effective execution.
Summary Findings:
Business Accelerators are a key part of the startup value chain as their service offer positions them to attract more developed startups that are post the incubation stage. Their blend of educating, mentoring, networking and providing seed capital which may lead to further funding sees accelerators as a common choice for aspiring entrepreneurs. The ability to intervene and impact to help bring success is seen as linked to a strong Execution-orientation. This Execution-Orientation is best adopted by the wider network resources of the Accelerator as well as the startup founders themselves.
The key findings that attribute to the success outcomes included: (i) the discipline of regular and detailed status meetings across a cohort along with one-to-one meetings with accelerator resources helps capability building and execution-orientation; (ii) the extent of Accelerator curricula planning and commitment to a comprehensive program that allows for industry specific expert input may impact success; (iii) mentor matching, commitment and input is a potential factor that may impact success by providing more relevant execution capabilities and orientation; (iv) learning can be from multiple sources from the environment and network established by a startup and its’ accelerator; (v) vicarious or serendipitous learning from other startups in a cohort can be important to a startups’ progress and; (vi) Founders with relevant prior corporate and/or industry experience have wider networks which may help growth efforts.
Implications for Startups and Business Accelerators:
The conclusions of this research highlight the important role of Business Accelerators in the startup ecosystem. With the increased focus of national economic agendas on the positive effect that a vibrant startup ecosystem can have on industrial growth, the importance of Business Accelerators contributing to the level of success in such agendas cannot be understated. The ability to impact the success of a startups’ journey presents a clear value-add opportunity. Applicants to such programs have an implicit regard for the potential benefits that an acceleration program may bring to their venture.
Some key suggestions for BA program managers are as follows with reference to the top two focus areas on GALI criteria, being:
1. Help ventures gain market traction:
2. Support leadership development of entrepreneurs
The results from this research and in particular the issues highlighted in the 2 case studies give strong corroboration of the merits of a focused Execution-orientation. The elements of this dimension of management at startups and through BA programs may include:
(i) ensuring strong market-centric focused articulation of the core product (service). With a detailed focus on the product/service features, the granular elements around execution aspects of the link between product/service benefits and customer value-add helps drive value creation;
(ii) sourcing, producing, implementing, managing and monitoring resources can be channelled to a clear core product (service).
These granular elements encompass an Execution-orientation, and thus reference the preferred focus on understanding, documenting, communicating, monitoring and managing on a continuous basis such detailed execution behaviours. The ability to define, document and track these elements in detail and to have frequent and scheduled communication sessions on the progress are seen as fundamental to instilling a strong execution-orientation.
With regard to the development of the entrepreneurs, BAs can distinguish their programs by having a conscious consideration for ensuring learning effectiveness issues are factored in. The effectiveness of the learning environment should be noted as extending to informal or vicarious learning from program cohort members and new network contacts facilitated by the program, which is learning that is additional to the formally scheduled interactions. The learning needs of startup founders should also be considered and personalized if possible, given experience levels will have an influence on the ability of younger founders to discern less relevant advice from fundamental knowledge that will help their capability development. A focus on striving for excellence in Execution-orientation will compliment Market-centricity and thus optimize efforts towards revenue traction. Achieving revenue traction will as a consequence address the other three criteria highlighted by GALI, which are to: (iii) connect ventures to investment opportunities; (iv) to drive economic growth and job creation and; (v) to spark innovation.
Acknowledgements:
My thanks to Dr. Anne-Valerie Ohlsson-Corboz, Dr. Philip Zerrillo (Singapore Management University) and Dr. Vicente K Fabella (Jose Rizal University) who kindly supervised this research.
Selected References:
Cohen, S. (2013). What do accelerators do? Insights from incubators and angels. Innovations: Technology, Governance, Globalization, 8(3–4), 19–25.
Creswell, J. W. (2014). Research design: qualitative, quantitative, and mixed methods approaches. Sage publications.
Hakim, C. (2012). Research Design: Succesful Designs for Social and Economic Research. Routledge.
Mason, C., & Stark, M. (2004). What do investors look for in a business plan? A comparison of the investment criteria of bankers, venture capitalists and business angels. International small business journal, 22(3), 227–248.
Roberts, P. W., (2017) Accelerating startups in emerging markets. Report by Global Accelerator Learning Initiative www.galidata.org
Stratman, J., & Roth, A. (2002). Enterprise Resource Planning (ERP) Competence Constructs: Two‐Stage Multi‐Item Scale Development and Validation. Decision Sciences, 33(4), 601–628.
Yin, R. K. (2009) Case study research: Design and methods (4th ed.) Thousand Oaks, CA: Sage
Appendix of Selected Data Analysis Outputs:
- Comparison of Means: Successful vs Non-Successful Companies, by 6 variables studied
Comparison of Means: 1.00 = Successful Startups; 2.00 = Non-successful. Execution-orientation variable shows the greatest difference of means
2. Independent Samples T-Test:
Interdependent Samples T-test (Accelerated vs Non-Accelerated startups): The Execution-Orientation “p score” of 0.052 indicates statistical significance
3. Chi-square test of Association:
The Chi-square test summary above indicates there is no-statistical significance of note between the accelerated vs non-accelerated results given the resultant p-score is above 0.05 (being 0.123 for Fisher’s test).
