Unit III Scholarly Activity
Malkta
Theimpactofsmallbuss.pdf
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201944
The Impact of Training on Small and Growing Businesses
© 2019 IUP. All Rights Reserved.
Suncan Pavlovic*, Jermaine Coelho** and John Olukuru***
* Visiting Professor, Strathmore Institute for Mathematical Sciences, Strathmore University, Ole Sangale Road, Madaraka, Nairobi, Kenya. E-mail: [email protected]
* * Project Manager, Institute for Small Business Initiatives, Strathmore University, Ole Sangale Road, Madaraka, Nairobi, Kenya; and is the corresponding author. E-mail: [email protected]
* * * Head of Data Science and Analytics, Strathmore University, Ole Sangale Road, Madaraka, Nairobi, Kenya. E-mail: [email protected]
Introduction The Micro, Small and Medium Enterprises (MSME) sector has garnered increasing attention
from across the globe due to its contribution to the economy and society as a whole, often
being cited as the ‘backbone of the economy’ (Robu, 2013). This holds true in various parts
of the world from regions such as across Europe, where they represent 99% of all businesses;
It is widely believed that Small and Growing Businesses (SGBs) have the potential to be global engines of shared prosperity: to drive growth, promote sustainability, and support equality around the world. This study looks at the effect of providing training to SGBs on their growth, profitability and employment creation. Data was collected from participants of the advanced entrepreneurship program at the Institute for Small Business Initiatives in Kenya. The study features the introduction of a new metric—Effective Cash at Owner’s Disposal (ECOD)—which is critical in evaluating SGBs, especially in developing economies. The data was then compared as at the intake date, 1 year and 2 years after. The findings of the study show that the program has a significant positive effect on the businesses that went through it with average revenue increasing by 63%, average EBITDA increasing by 106% and 2.2 net new jobs created by each enterprise within a year of enrolment. The study also finds that the program year is characterized by strong revenue and profit margin growth, as well as relatively moderate employment growth due to the optimization effect. In the year after the program year, the positive trend continues (at a notably lower rate), but once the streamlining process is completed, the employment growth booms (doubling the growth rate from the first year). The study also reveals that remarkable improvement in understanding of finance is not matched by an equivalent improvement in cost optimization and record keeping. The introduction of a user- friendly IT tool for financial analysis and cost optimization is likely to greatly increase the effectiveness of such entrepreneurship programs and create longer lasting impact.
The Impact of Training on Small and Growing Businesses 45
they have created over 85% of jobs (Commission, 2019) in Southeast Asia, where they again
represent over 90% of enterprises, and generate a majority of the employment (Pratama, 2019) in
China, Japan and the USA (Robu, 2013). It is the same case in Kenya, with over 80% contribution
to employment creation and contributing one-third to the economy’s GDP (KNBS, 2016). Given
the critical role they evidently play in the economy, the high rate of business failure is alarming
with over 60% of businesses closing within the first two years (KNBS, 2016). A study carried out
by Njoroge and Gathungu (2013) on Small and Medium Enterprises (SMEs) in a Kenyan district
revealed the urgent need for training on financial and strategic management for SMEs to grow
beyond the first stage of enterprise development and survive beyond five years.
Small and Growing Businesses (SGBs) differ from the more traditional characterization of
SMEs in two fundamental ways. Firstly, SGBs differ from livelihood-sustaining small
businesses, which start small and are destined to stay that way. Secondly, unlike many
medium-sized companies, SGBs often lack access to the financial and knowledge resources
required for growth (ANDE, 2019). SGBs have the potential to be global engines of shared
prosperity: to drive growth, promote sustainability, and support equality around the world
(ANDE, 2016). The Institute for Small Business Initiatives (ISBI) was founded by an Austrian
NGO ICEP and Strathmore Educational Trust (SET) with the goal to promote business and
financial skills amongst these SGBs in Kenya.
ISBI offers comprehensive innovative business programs for entrepreneurs who wish to
streamline their business operations, expand their business and graduate from micro stage to formal
or higher levels of scale enterprises. The focus of the programs is on the immediate practical value
for entrepreneurs and best practices from each industry involved. All business cases were
developed based on real-life Kenyan examples. Furthermore, the class framework also provides an
excellent opportunity to network and exchange ideas with the like-minded entrepreneurs.
The Advanced Entrepreneurship Program (AEP) is ISBI’s flagship program; it is composed
of 13 half-day sessions held once a week over 3 months. Contrary to most training programs
where participants are either fully sponsored or pay only a small symbolic fee, AEP
participants pay on average US$1,000 which cater for all the direct costs associated with
running the program. This ensures sustainability of the program independent of future
donations, since clients are willing to pay the full cost of the program. This serves as a double-
edged sword as it forms part of the selection criteria in filtering the entrepreneurs who are
serious and dedicated to improving their businesses while, on the other hand, it ensures that
the program is constantly improving in attempt to deliver value for money to the clients.
Comparing the performance of these entrepreneurs who pay for training to those who take part
in sponsored programs will reveal critical insights which can be used by other training
institutions and NGOs as well as contribute to policy making regarding SGB training.
AEP focuses on five main areas: strategy and marketing, finance and cost management,
leadership and organization, tax and law, and personal development. As a value add-on,
participants enjoy the benefit of a choice (depending on their individual priorities) of one of
the following individual services: consulting, coaching or business plan mentoring, typically
between 1-3 months after completion of the class sessions.
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201946
As shown in Figure 1, these modules form the foundation of the business and when this
foundation is strong, it transforms into the pillars of growth of the business. After the
entrepreneurs gain personal skills that help them develop personally, they gain business skills,
what together results in effective and transformative change within the businesses.
The program is designed for business owners or key decision makers in licensed companies
meeting any three of the following criteria:
• Annual turnover of US$100,000 (KES10 mn) or more
• Credit capacity of US$50,000 (KES5 mn) or more
• Two years at the least in the same business
• Five full-time employees or more
• Undergraduate degree or higher of the participant entrepreneur
By using this selection process, ISBI is able to select businesses that meet ANDE’s
definition of SGBs of having between 5-250 employees and significant potential, and
ambition for growth (ANDE, 2019).
Figure 1: AEP Course Structure S
tr at
eg y
a n
d M
ar k
et in
g
F in
an ce
a n
d C
o st
M an
ag em
en t
L ea
d er
sh ip
a n
d O
rg an
iz at
io n
Personal Development
Individual Sessions
(Time Management, Decision Making, Negotiation)
(Consulting, Business Plan Mentoring, Coaching)
Advanced Entrepreneurship Program
The Impact of Training on Small and Growing Businesses 47
The existing research shows that there is a gap in the efficiency of providing support when
it comes to selecting which firms to support (Woodruff, 2018). Differences in firm performance
after going through training based on ISBI’s selection criteria will provide valuable insights
into developing an optimal selection process for other similar programs.
This paper, in form of a benchmarking report aims to estimate the impact, both financially
and qualitatively, of the program by comparing performance data for the year before the
participant joined the program, one year after and, where applicable, two years after intake
in the program.
Literature Review Studies reveal that education and training rank highly among the critical factors leading to
the success of entrepreneurs and their businesses (Mehralizadeh and Sajady, 2006). It is also
widely regarded amongst practitioners, researchers and policy makers that entrepreneurship
education results in measurable outcomes (Kozlinska, 2012). There is the increased need and
desire amongst both business schools and firms in measuring the impact of executive and entrepreneurial education, though it is often difficult to accurately measure due to lack of
baseline data as well as inaccurate or misleading data (Murray, 2019). The diverse content
of various programs combined with differences in duration and intensity makes it difficult to
determine the extent to which such programs can be compared (Ismail, 2018). Generally, the
impact of entrepreneurial education can be measured across two spheres: educational and
socioeconomic (Kozlinska, 2012) where educational learning outcomes are put forward as knowledge, attitude and skills (Heinonen and Poikkijoki, 2006; and Batarelo et al., 2013).
Other sources refer to the ‘impact’ of entrepreneurial education moving from the purely
educational dimension to the socioeconomic level which includes increased income, growth
and job creation (Blenker et al., 2006).
Studies throughout the literature reveal conflicting results with some scholars discovering
that there is little to no significant effect on businesses in terms of revenue, profits and
employment amongst Peruvian female entrepreneurs who received training (Karlan and
Valdivia, 2011). Most studies find that business owners implement some of the practices
taught during training, though the magnitude of improvement to practices is often modest at
best (McKenzie and Woodruff, 2013). Despite one of the main aims of entrepreneurship training programs being the promotion of self-employment through business creation,
evidence from programs in Sri Lanka and Chile find that in the long term (2 years), self-
employment declined significantly (Mel et al., 2014; and Martínez et al., 2016). Another
meta-analysis of 37 programs also found that there was no impact on income after training
(Cho and Honorati, 2014).
There are some studies that reveal some positive effects of business training albeit under
certain conditions. For instance, there is a statistically significant positive effect on
entrepreneurs who had access to higher education (Cho and Honorati, 2014). In Chile, the
Micro-Enterprise Support Program (MESP) resulted in an increase in total income of US$70 which decreased to US$34 over the long term (Martínez et al., 2016). A study in Pakistan finds
that entrepreneurship training reduced the rate of business failure among men by 6.1% though
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201948
there was no effect on women (Giné and Mansuri, 2014). Another study using data from seven
countries shows that standard training programs with focus on business practices are highly
correlated with differences in firm performance both in the cross section and panel data
(McKenzie and Woodruff, 2017).
The discovery that standard mass-delivered trainings are mostly ineffective led to the
experimentation of new approaches, for instance, an initiative in Togo providing ‘personal
initiative’ psychological training to small business owners is more effective in improving sales
and profitability than standard training programs (Campos et al., 2017). Anderson et al. (2018)
find that connecting small-scale entrepreneurs in Uganda with mentors across the world
through online meetings over Skype has little impact on business practices, highlighting the
importance of local knowledge or personal contact.
There are also a number of self-published reports from various organizations involved in
business training that show improvements after participation, for instance, Goldman Sachs’
10,000 small businesses program in the US where 68% of participants increased revenue after
six months (Sachs, 2016) and in the UK where one year after the program, average revenue
increased by 45% (Sachs, 2018). Technoserve has recently launched a program for training
micro-retailers in Kenya and the results of the program indicate that average revenue increased
by 44% and average profits increased by 56% (Waweru, 2019). A study done on female
entrepreneurs in Kenya who underwent business training shows that they increased revenues,
profits and the owners’ well-being without any negative effects on non-treated businesses,
meaning that business growth in underdeveloped markets is possible without taking sales
away from non-treated businesses (McKenzie and Puerto, 2017).
While there is very limited evidence on the effectiveness of business training for SMEs,
the available evidence suggests that individualized consulting programs for bigger entities,
though largely more expensive, has significant effects on performance with costs being
recouped in less than a year (Bloom et al., 2012). ISBI’s unique approach of blending in-class
training with individual consulting sessions after they learn the core concepts significantly
reduces the traditionally large cost of individualized consulting services. There is an
increasing number of incubators and accelerators in lower-income countries, however, there
is limited evidence of their effectiveness (Woodruff, 2018). A majority of the studies focus
on either programs that provide technical skills through lectures in a classroom setting, or
mentoring projects or individualized consulting. ISBI provides services to its clients mainly
through lectures but also offers additional value-add on services of consulting, mentoring or
business plan development depending on the entrepreneur’s concrete needs and priorities.
Studying the differences between entrepreneurs’ performance based on their choice of value-
added will provide key insights into the most effective method of support for SGBs. The study
will also contribute significantly towards understanding more about which specific
components of accelerators are the most important in the context of the Kenyan SME sector.
Research shows that some interventions have different effects on males and females
(Woodruff, 2018). ISBI has approximately 50% male and 50% female alumni entrepreneurs
across various sectors, thereby providing the opportunity to discern differences in effects of
The Impact of Training on Small and Growing Businesses 49
training on these businesses. This will greatly contribute to the much-needed body of literature to assist in development of the most effective interventions for both female and male owners.
Data and Methodology
Population and Sampling The entire population under study includes 163 entrepreneurs who undertook the AEP from the commencement of this study in May 2019. For the purpose of this study, it was determined that 32 of the entrepreneurs who had gone through the program not long before would be unable to provide sufficient data at that point, leaving a net population of 131 entrepreneurs. According to Krejcie and Morgan (1970), a population of 131 corresponds to a sample size of 98. From this target sample size, there was a response rate of 80% (number of usable responses/target sample size) (Fincham, 2008) which is significantly above the generally accepted minimum response rate of 60% and in some cases even 50% (Draugalis et al., 2008).
As shown in Figure 2, 47 participants were able to provide all the required data for 2 years. 31 participants were able to provide all the required data for 3 years. 32 participants took part in the program during 2019 and it was determined that it was too early for conclusive information at the time of data collection. 23 participants cancelled set appointments on more than one occasion. 11 participants were uncomfortable sharing financial information. 8 participants refused to take part in the impact assessment. 7 participants responded to only a part of the questionnaire. 4 participants could not be reached after calling on 5 separate occasions as well as sending 2 emails with no response.
Figure 2: Population Breakdown
47
31
1 1
32
7
23
8
Cancelled appointment
twice
Too early for conclusive information
Uncomfortable to share financial information
Did not want to take part in research
Could not be reached
Incomplete data
Provided full data for 3 years
Provided data for 2 years
4
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201950
Complete datasets were obtained from 78 entrepreneurs: 43 were recorded at the clients’
sites, 22 were recorded in ISBI premises and 13 were recorded over the phone. As shown in
Figure 3, 50% of participants are female and 50% are male. 50% held an undergraduate
degree, while 26% held a higher degree and 24% had a lower qualification than an
undergraduate degree. Regarding how long the participants have been in the same business,
32% had over 10 years of experience, 36% had 6-10 years experience, 10% had 3-5 years
experience and 22% had less than 2 years of experience. 61% were in the service sector, 24%
in production and 15% in retail. In terms of industry, 19% were in professional services, 19%
in building technologies, 13% in food and beverages, 12% in ICT, 9% in tourism and leisure,
8% in environmental technologies, 8% in education, and 12% in others. In terms of size 17%
had revenues below US$20K, 10% had revenues between US$20-50K, 14% between US$50-
100K, 13% between US$100-200K, 22% between US$200-500K, 13% between US$500K to
1 mn and 12% had revenues greater than US$1 mn.
Data Collection
Since the data to be collected is of complex nature and can be interpreted in various ways,
it was necessary to train the data collectors beforehand in how to collect the data to ensure
accuracy and uniformity (Schindler, 2019).
Figure 3: Participants’ Background
Gender Education Experience
Female, 50%
Male, 50%
Above UG, 26%
Undergraduate
50%
Below UG, 24%
More than 10 years, 32%
6-10 years, 36%
3-5 years, 10%
Less than 2 years, 22%
The Impact of Training on Small and Growing Businesses 51
The data collected is both quantitative and qualitative.1 The quantitative data collected
relates to three distinct periods: the year before the program—12 months before the intake
date, the year during the program—12 months after intake date, and the year after the
program—13 to 24 months after intake date (where applicable).
The qualitative data was collected by asking participants to rate various characteristics of
the program and their experiences on a scale of 1-5 where 1 = No impact and 5 = Major
Transformation.
Data was collected through three main ways: interview in person at the clients’ sites (in
55% cases), interview in person at ISBI offices in Strathmore University Business School (in
28% cases) and phone interview (in 17% cases).
Companies were categorized by industry sector according to the 10 clusters used by the
UK Department of Trade and Investment since 2001 (Midlands, 2012).
Data collected and used in evaluating impact include:
Employment
As employees are recognized as all people who work full-time for a concrete SGB and it
represents their main source of income, irrespective of legal status and formality of
employment. In some cases, especially in construction and agriculture sectors, the SGBs
employ quite a few seasonal workers. In such cases, the number of workers and working
months are annualized. For instance, six full-time workers engaged for four months are
reported as two full-time employees.
Revenue
Reported revenue represents total revenue from all business activities of an entrepreneur,
irrespective of formal, semi-formal or even completely informal nature of a concrete business
activity.
EBITDA (Earnings Before Interest, Tax, Depreciation and Amortization)
EBITDA is used as a measure of profitability increase because of lack of proper accounting
records and unfeasibility to collect precise data, especially on depreciation and total credit
costs. The change in EBITDA is used as the most relevant benchmark for measuring
increased market value of the SGBs (Damodaran, 2012). The measurement of this aspect is
very important as many SGBs strive for external equity capital, and the higher the initial
value of the enterprise, the stronger the entrepreneur’s negotiation position, i.e., they
sacrifice a smaller percentage of ownership for the same amount of investment.
EBITDA = Revenue – COGS – SGA
1 The data was collected using the model questionnaire of Aston Business School (ISBI-Strathmore University). A comprehensive explanation as to how each data item in the questionnaire was collected is available at www.isbi-kenya.org
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201952
ECOD (Effective Cash at Owner’s Disposal)
For the purpose of this study we introduced a new metric: ECOD, i.e., Effective Cash at Owner’s Disposal. It is similar to Owner’s Discretionary Cash Flow (ODCF), but net of credit installments and effectively paid tax in the concrete year.
ECOD = EBITDA + Owners Salary + Owner’s Drawings – Interest Expense – Credit
Principal Repayment – Tax Paid
ODCF (Kenton, 2018) is commonly used as one of the most important multiples for estimating SME value in case of merger and/or acquisition of small businesses (Schmerler, 2016). Since ODCF is used mainly for the purpose of valuation, current capital structure is irrelevant to the new owners. Therefore, ODCF gives valuable information to the acquirers about the cash SMEs can generate, irrespective of decision on how they are going to finance the acquired company.
The relevance of measuring the effective cash the owners have at their disposal is extremely important for MSMEs in emerging countries being an indicator of their sustainability (i.e., ability to generate cash from operation over and above credit and tax obligations) as well as of the potential to sustainably grow their business (i.e., without increasing leverage).
In Kenya, many MSMEs, especially the micro- and very small enterprises, rely on different kinds of MFIs, less-regulated SACCOs and even informal Chamas. Moreover, even the licensed banks often provide their financing products in a less transparent way as compared to the common practice in developed countries. For instance, overdraft is typically given at a fixed rate for three months, but the interest rate is applied flat to the highest amount exposed during this period and not calculated per day pro rata. Such practices are combined with high flat fees and other upfront charges, which (due to the short crediting period) have serious effects on the actual costs of borrowing.
A majority of credits provided by MFIs and other, less regulated institutions are for very short periods, typically up to one year. It makes the servicing monthly (or often weekly) installments a real challenge and a serious threat to the MSME survival.
Due to all this and our primary interest lies not in enterprise valuation for the purpose of sale, but in the increase of its sustainability, and we found that measuring ECOD is much more suitable for our purpose. Additionally, by measuring changes in CROE (Cash Return on Equity) we used changes in ECOD/Equity as significantly more informative in our case. Finally, in our measurement of the Gross Value Added (GVA) we use the change in ECOD in combination with the change in total amount of salaries paid.
After collection, the data was then entered into the database by the researchers. The data was then prepared for analysis by ensuring that it was complete, accurate and appropriately
coded (Schindler, 2019).
Data Analysis
The report seeks to estimate the GVA to the participants’ businesses using methodology
borrowed from similar impact assessments carried out by Aston Business School (Butler and
Wilson, 2015) and Advantage West Midlands (Midlands, 2012).
The Impact of Training on Small and Growing Businesses 53
This study measures GVA using three of the recognized approaches which center on
business (turnover), employment (change in number of employees), and business (salaries and
profits). The above approaches were calculated for the sample size and then extrapolated over
the entire population in order to estimate the total impact of the program.
Results
Business (Turnover)
After participation in the program, average revenue increased by 63% (US$285,000) from
US$437,000 to US$733,000. There was a total increase in revenue across all participants by
US$48.3 mn from US$73.9 to 120.3 mn, thereby contributing to the growth of the economy.
This growth was fueled by 71% of participants who increased their revenue, while 25%
reduced their revenue and 4% did not experience any change. The increase in revenue among
the smaller-sized entrepreneurs who fall within the first quartile (Q1), was 56% which is similar
to the average revenue increase of 63%. This implies that the average is not skewed upwards
by some big companies and growth is similar across all sizes of businesses. This average
increase in revenue one year after the intake is roughly 1.5 times higher than similar, fully
sponsored programs in developed economies such as the UK (Sachs, 2018). Furthermore, when
looking at growth, 40% of participants were able to grow into the next category, testifying
to the effectiveness of the program.
The GVA is US$13.9 mn as shown in the Figure 4 and is calculated as 30% of the total
increase in revenue for all participants translating to a 63% increase (Midlands, 2012; and
Butler and Wilson, 2015).
Figure 4: Gross Value Added (Turnover) According to the Revenue Method
40
35
30
25
20
15
10
5
0
22.2
36.1
N = 163
AfterBefore
Value Added
US$ + 13.9 mn (63%)
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201954
Job Creation After participation in the program, there were on average 3 new jobs created per SGB, especially among the smaller businesses. As shown in Figure 5, 42 SGBs (54%) with 14 employees on average increased their staff by 5, creating 235 jobs. There was no reported difference in the number of employees for 22 SGBs (28%). There was also a reduction in the number of employees, particularly in the larger companies that were overstaffed and underwent optimization processes. 14 SGBs (18%) with 34 employees on average reduced their staff by 5, i.e., 64 in total. In combination, these two effects (growth of the smaller and optimization of the larger SGBs) resulted in a net creation of 2.2 jobs per SGB which translates to 357 net new jobs.
Figure 5: Increase Versus Decrease of Jobs
Before After
Increased Same Decreased
14 10
34
19
10
29
Business (Salaries and Profits) Within a year of participating in the program, average EBITDA increased by 106% (US$72,000) from US$67,000 to US$139,000. There was a total increase in EBITDA by US$12 mn from US$11 mn to US$23 mn. This growth was fuelled by 81% of participants who increased their EBITDA, while 13% reduced their EBITDA and 6% did not experience any change. Increase in EBITDA after going through the program is remarkably strong in the lower segment (Q1) with EBITDA increasing by 320% (US$14,000). Specifically of interest is the fact that 8% of businesses reduced their turnover by 20% on average, but tripled their EBITDA (increased by 193%), which is one of the AEP’s key messages: “optimization before growth”.
Within 1 year of participating in the program, average ECOD increased by 92% (US$56,000) from US$60,000 to US$116,000. There was total increase in ECOD by US$9.1 mn from US$9.9 mn to US$19 mn as shown in Figure 6. This growth was fuelled by
The Impact of Training on Small and Growing Businesses 55
81% of participants who increased their ECOD, while 17% reduced ECOD and 2% did not
experience any change. The average increase in ECOD is equally strong in the lower segment
with increase in ECOD of 94% (US$10,000).
Net employment increased by 357 (491 gross) and in combination with average salary
increase of +US$287 per employee per annum amounts to US$2.26 mn increase in salaries.
Total amount of salaries and profits changed from US$20.22 mn to 31.57 mn, i.e., increase
of US$11.35 mn.
Statistical Significance
Two-sample t-tests were carried out on the samples for each category of revenue, EBITDA,
ECOD and employment to determine the statistical significance of the changes attributed to
going through the program on these variables, at 5% significant level. The results reveal that
the changes in the businesses can indeed be attributed to their participation in the program
as shown in Table 1.
Client Satisfaction
After each class session, participants fill in a feedback form where they rate the session
and provide suggestions for improvement. The ratings are made on a scale of 1 to 5, where
the answers are summarized in three thematic groups and represented as average for each
group:
Figure 6: Gross Value Added According to Cash and Salaries
35
30
25
20
15
10
5
0
N = 163
Salaries
10.4
ECOD
9.9
Salaries
12.6
ECOD
19.0
Before After
Value Added
US$ + 11.4 mn (56%)
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201956
Table 1: Descriptive Analysis of the Tangible Measures of Business Growth
Mean 453,225 737,999 67,487 139,071 60,476 116,279 16.3 18.4
Standard Error 111,779 232,330 12,288 25,597 9,869 21,011 2. 8 2. 8
Median 150,000 187,500 32,900 55,520 31,595 48,216 6. 0 8. 0
SD 987,203 2,051,880 108,523 226,065 87,158 185,564 24.7 24.9
Sample Variance 9.75E+11 4.21E+12 1.18E+10 5.11E+10 7.60E+09 3.44E+10 6.10E+02 6.20E+02
Kurtosis 45.19 42.48 3.04 17.04 2.59 18.77 13.91 8.30
Skewness 6.12 6.17 1.12 3.55 1.29 3.75 3.36 2.70
Count 7 8 7 8 7 8 7 8 7 8 7 8 7 8 7 8
Confidence Level 222,580 462,627 24,468 50,970 19,651 41,838 5. 6 5. 6
(95.0%)
t-Test: Paired Two Sample Revenue EBITDA ECOD Employees
Mean Before 453,225 67,487 60,476 1 6
Mean After 737,999 139,071 116,279 1 8
Observations 7 8 7 8 7 8 7 8
Pearson Correlation 0.91 0.52 0.59 0.94
df 7 7 7 7 7 7 7 7
t-Stat. –2.07 –3.27 –3.26 –2.29
P (T<=t) one-tail* 0.02104 0.00081 0.00084 0.01249
t Critical one-tail 1.66488 1.66488 1.66488 1.66488
P (T<=t) two-tail 0.04209 0.00161 0.00168 0.02498
t Critical two-tail 1.99125 1.99125 1.99125 1.99125
Descriptive
Statistics
Revenue
After
EBITDA
After
ECOD Employees
* p-Values at Alpha 5%
97.9%
99.9%
99.9%
98.8%
2.1%
0.1%
0.1%
1.2%
AfterAfterBefore Before Before Before
The Impact of Training on Small and Growing Businesses 57
• Relevance and applicability, ranging from (1) Not at all … to (5) Very much. • Teaching method and provided materials, ranging from (1) Poor … to (5) Excellent • Program organization, venue, etc. in the range from (1) Poor … to (5) Excellent Continuous and meticulous study of clients’ feedbacks for each subject and lecturer is the
only way to keep quality at the desired level and to improve instead to degrade the effectiveness of the program with the time.
The soaring reviews received from AEP participants of over 90% rating across all modules and aspects, shown in Figure 7, testify to the quality of the program and the value that they derive from it.
Personal Development Over 80% of alumni reported significant positive impact on their leadership confidence and capability, what translates into concrete organizational improvements. About 75% of participants reported improvements in delegation of duties, thus freeing up time for strategic thinking and planning.
Over 75% of participants reported major transformation or significant improvement in their understanding of finance, especially in relation to their business. However, this improved understanding of finance by the entrepreneurs is not matched by an equivalent improvement in record keeping and cost optimization where only about half of the participants reported major transformation or significant improvement.
Figure 7: Client Satisfaction
Feedback Collected from AEP Participants after Class Sessions
Total No. of Feedback Forms = 781
Relevance and
Applicability
Teaching and
Materials
Program
Organization 4.74 4.66 4.61
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0 Strategy and
Marketing
Finance and
Cost
Management
Leadership
and
Organization
Business Law
and Taxation
Personal
Development
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201958
Discussion Investor Desirability
Analysis of the data collected shows that Return on Assets as a measurement of management efficiency increased by 81% within a year of participating in the program [Due to lack of precise information about interest costs explained above, (EBITDA/Assets) is used as much more reliable metrics for comparison over time than typically calculated (Net Income/Assets)] This can be attributed to participants’ better understanding of finance and how thereby to better utilize the assets at their disposal to generate greater returns.
Cash return on equity (ECOD/Equity) as a measure of SGB attractiveness for investors went up by 62%. As a result of the participants’ increased understanding and awareness regarding their business, they are able to generate greater returns on their investments through a combination of deleveraging, streamlining operations and precisely focused investing.
These significantly higher ratios make SGBs more attractive to potential investors as it is an indication of the effectiveness of the management as well as the ability of the company to generate cash. This makes it easier for the SGB owners to raise capital, if they decide to
seek investment for further growth and expansion.
Risk Reduction Debt coverage ratio as an indication of SGB’s ability to service its credit obligations increased by 55%. This is brought about by the improved profitability and cash generation of the firm and represents one of the most important achievements of the AEP: reduction of risk of falling into illiquidity (most common bankruptcy cause, especially among very small SGBs). Furthermore, lending institutions are more willing to extend additional credit to these SGBs.
These findings are in line with earlier studies carried out by Karlan and Valdivia (2006), who found that through entrepreneur training, microfinance institutions also had direct benefits in terms of higher repayment and client retention rates.
Debt/Equity (D/E) ratio, as a measure of financial risk SGBs are exposed to, was reduced by 19% within one year. This is also an extremely important achievement of AEP as it makes SGBs much more robust against changes in their very volatile market conditions—resulting
in significantly reduced likelihood of falling into insolvency.
Insights
Gender
We have not identified any statistically relevant differences between men- and women-owned
SGBs. This implies that both men and women benefit similarly from the training provided.
Experience
We attribute the differences based on the entrepreneurial experience much more to the
difference in the SGB size than to the actual owner’s experience. Profit has more than doubled
in each segment, but the profit drivers are different:
The Impact of Training on Small and Growing Businesses 59
• Improvement in SGBs with owners having fewer than 10 years of experience (actually smaller SGBs with revenue of US$300K on average) was driven mainly
by increased turnover (87%) and less by profit-margin increase (15%).
• On the contrary, in SGBs with more experienced owners (in fact, bigger SGBs with revenue of US$779K on average) the change was achieved by the turnover increase
of 43% (half the rate of smaller SGBs) and profit-margin increase of 34% (double
the rate compared to smaller SGBs).
Education
Differences based on educational background support the assumption that better educated participants benefit much more from the program:
• The participants with a degree above undergraduate – tripled EBITDA (+221%) • The participants with undergraduate degree – doubled EBITDA (+108%) • The participants with educational level below undergraduate – increased EBITDA
‘only’ by half (+49%)
Cost Recovery
A majority of participants recovered the cost of the program already during the program itself through increased profits and operations, with 80% recovering their costs within three months. Only 10% of participants required more than 6 months to recover their costs. Next to ensuring sustainability of entrepreneurship programs, this finding reinforces ISBI’s founding presumption that such training must be perceived by MSMEs not as a personal owner’s
expense, but as investment into their business and as such must bear return.
Comparative Impact
Comparing the performance of the AEP alumni to the performance of participants in other programs as well as the larger economy as a whole helps to put things into perspective. The Global Accelerator Learning Initiative (GALI), which draws data from the Entrepreneur Database Program at Emory University, provides a benchmark using 12 acceleration programs in developing countries with the focus on creating impact on for-profit micro and small enterprises across all sectors (ANDE, 2019), similarly to AEP. This benchmark compares the 78 AEP alumni to 86 accelerated ventures with the following results:
• Average revenue of accelerated ventures increased by 8% versus AEP 63%; • Average new jobs created by accelerated ventures was 1.2 versus AEP 2.2; • Asset turnover change of accelerated ventures was 12% versus AEP 43%; • Average productivity of accelerated ventures decreased by 2% versus AEP increase
of 43%; and finally
• Accelerated ventures receive philanthropic support of US$4,000 on average, whereas AEP alumni pay US$1,000 for the program.
Comparing the performances with other comparable programs is challenging, as most programs
generally do not report their impact, lest of all to such an extent. The Goldman Sachs 10,000 Small
Businesses (10KSB) program in the UK was selected as a suitable benchmark due to the similarities
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201960
in the program as well as the comprehensiveness of their impact reporting. Similarities between
AEP and GS 10KSB are in the target market (small businesses), program goals and duration of
the program (Sachs, 2018). Most significant differences are in the economic environment (UK
versus Kenya) and average enterprise size (5 times: US$2,160K versus 453K).
Significant differences are in revenue (albeit AEP’s superior percentual increase in revenue can
be partially explained by much smaller turnover in the case of AEP participants) and productivity
increase. GVA measured in absolute numbers is much higher in the UK, but considering the
number of alumni (8x) and average size of enterprise (5x), both programs yield practically the same
results in terms of turnover percentage: +12%. Similar situation is with employment growth: +13%.
GS 10KSB does not report several indicators that play a critical role in developing
markets. Especially important are increase in capital efficiency (by 81%) due to very high
financing costs in Kenya (as well as in other developing countries), and increase in SME
market value (+106%) as shown in Figure 8. Moreover, due to the high rate of SME
bankruptcies caused by illiquidity and insolvency, reduction in financial and liquidity risks
(–19% and –55% respectively) play a crucial role in the case of Kenyan enterprises.
Relating the performance of the AEP alumni to the overall prevailing economic conditions
in the same period also highlights the impressive contribution of AEP. The AEP alumni grew
5.6 times more than the average GDP growth rate (Bank, 2019) and created 4.2 times more
jobs than the economy in general in the same period (KNBS, 2019).
Figure 8: Benchmark Comparison
SME Growth ( Revenue)
Productivity Increase (Revenue/No. of
Employees)
Employment Increase
Gross Value Added/SME Size
Understanding Finance/More Using
Financial Data
Leadership Confidence
Leadership Capability
63%
45%
43%
28%
13%
13%
12%
95%
84%
96%
94%
99%
97%
12%
SME Value Increase EBITDA)
Operating Cash Increase ODC)
Capital Efficiency Increase EBITDA/Assets)
Investment Attractiveness ODC/EQUITY)
Debt Coverage Increase
Profit Margin Increase ( REV/
EBITDA)
Equity Increase
Assets Growth
Debt/Equity Ratio Decrease
106%
92%
81%
62%
55%
27%
27%
21%
19%
95%
Financial Indicators not Reported by Goldman Sachs 10KSB Program
(UK)
ISBI’s AEP (Advanced Entrepreneurship Program
Goldman Sachs 10KSB Program (UK)
The Impact of Training on Small and Growing Businesses 61
Conclusion
AEP Effectiveness
Increasing Value
Increase in revenue of 63% in combination with 27% increase in profit margin results in more
than doubling EBITDA (+106%), which is used as proxy for establishing change in SGB
value. ROA dramatically improved from 21% to 38% and ROE from 30% to 48% testify to
extensive improvement in operational management and significant increase in attractiveness
of SGBs for future investors.
Improving Liquidity
Two factors contributed to substantial improvement in SGB liquidity (illiquidity is the most
common cause of SGB bankruptcy): Free Cash Flow almost doubled (+92%) and debt-
coverage ratio increased by 55%.
Creating Employment
Employment growth (mainly driven by service sector) averages to 3 new employees per SGB.
Due to strategic streamlining (i.e., cutting off unproductive activities and focusing on core
competence) 18% of SGBs reduced their staff, which resulted in 2.2 net jobs per SGB in the
program year. However, in the year following the program-year this optimization effect was more
than compensated; but now by the growth of more profitable and less risk-exposed SGBs.
Comparing these results with the US$1,000 cost of the program (paid by clients
themselves) suggests a cost per job of around US$450, what compares quite favorably with
other programs aimed at creating jobs in developing countries, such as US$2,000 in Mexico
(Bruhn et al., 2018), and US$9,600 through the YouWin! Competition in Nigeria (McKenzie
and Sansone, 2017).
Facilitating Sustainable Growth
40% of participants were able to grow into the next category within a year of completing the
program. Asset growth (14% on average), especially remarkable in the production sector
(31%), is in big part financed by equity from retained earnings—19% on average (60% in
production sector). This trend of healthy organic growth is evident not only during the
program year but also continues (at a slower rate) in the following year, which results in
substantial reduction of debt/equity ratio from 1.04 to 0.77 in two years as shown in
Figure 9, and consequent reduction of financial risk.
Social Impact
GVA according to revenue method is US$13.9 mn. GVA of US$11.4 mn according to profits-
and-salaries method consisted of: increase in effective cash at owner’s disposal by US$9.1 mn
(US$56K on average) and increase in total salaries paid (number of employees x average
salary) amounting to US$2.3 mn. This brings the average GVA to US$12.7 mn. Development
costs were donor-sponsored and amounted to US$630K over the 3 years. Therefore, every $1
invested in program development resulted in $20 of social value addition.
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201962
Assuming continuing annual growth in the number of participants of only 10% and after adjustment for execution risk (–20%), it is quite realistic to expect that at least US$26.9 mn extra of social impact will be created during the next five years. Consequently, terminal value results in additional $43 of social impact per $1 invested (Addy et al., 2019).
Recommendations
Social Impact
As revealed from the study, the impact of programs such as AEP where clients pay in full for delivery costs is greater than other programs that are fully sponsored or clients pay only small symbolic fees. Charging entrepreneurs to participate in the program has three immediate apparent benefits:
• Firstly, it serves as an excellent filter to select only those entrepreneurs who are serious about improving their businesses and will be dedicated to completing the program and getting the most out of it.
• Secondly, it encourages the lecturers and delivery team to provide value for the clients’ money, thereby ensuring that the program maintains top quality throughout.
• Finally, since clients cover running costs of the program in full, it facilitates continuity of the program beyond the donations required for program development. It is therefore recommended that NGOs change their traditional model of providing fully-sponsored programs to charging a substantial amount in order to create deeper impact and facilitate sustainability.
Figure 9: Asset Growth and Capital Structure
1.04 D/E Ratio
0.77
n = 31
Assets 362
Assets 438 Assets 489
Year Before AEP Year Following Year
Equity
177
Equity
224
Equity
277
0.95
The Impact of Training on Small and Growing Businesses 63
Optimization Before Growth
The study finds that the program year is characterized by strong revenue and profit margin
growth, as well as employment growth (at a moderate rate due to the optimization effect).
In the year after the program-year, the positive trend of increasing revenue and profit
continues, albeit at a lower rate; but once the optimization and business streamlining are
completed, the employment growth booms (doubling the growth rate from the first year),
thus more than compensating for earlier rationalization. It is recommended that SGB support
programs follow this approach of prioritizing optimization and streamlining existing
business activities over simply providing funds or other means of expanding existing
activities in order to prevent the growth of unproductive activities which could be
detrimental to the business as a whole.
Improvement Potential
The study reveals that remarkable improvement in understanding of finance is not matched by
an equivalent improvement in cost optimization. The problem lies in the lack of a user-friendly
IT solution for record-keeping that should be accompanied by a tailor-made software for
financial analysis and cost optimization. The need for an IT solution is propagated by several
challenges of manual record keeping. It is difficult to collect all relevant information manually:
there is too much information to collect, too many calculations to do manually, and too many
mistakes are possible. It is also difficult to analyze collected information without software:
participants require a long and specialized training in order to internalize relevant financial and
cost-management concepts and quantitative methods. Without tangible benefit, sooner or later,
SGBs lose patience. Without clear insights, it is not possible to draw proper conclusions about
crucial improvement potential. Onsite monitoring and impact measurement are very expensive
and prone to inaccuracy. The introduction of such a tool is likely to greatly increase the
effectiveness of such entrepreneurship programs and create longer lasting impact.
Challenges Faced
Some of the entrepreneurs who had gone through the program since then changed some of
their contact details such as email addresses and telephone numbers, thus making it difficult
to track them down.
Often the entrepreneurs would cancel meetings at the last minute, sometimes even after
the researcher departed to the agreed upon destination. This proved to be costly and
demoralizing for the data collectors. In 23 cases, the entrepreneurs cancelled meetings on two
or more occasions, after which we stopped insisting on interviewing them.
Limitations: Despite careful and rigorous approach by the researchers, some numbers could not be considered 100% accurate because they were not automatically recorded (by a
sophisticated record-keeping software, for instance), but mainly self-reported. Also, due to
the lack of proper financial records and due to the prevalently semi-informal nature of doing
business among the population under study, in some cases it was necessary to make—
always jointly with the interviewed entrepreneur—estimations of various costs and
expenses.
The IUP Journal of Entrepreneurship Development, Vol. XVI, No. 4, 201964
However, considering the specifics of the researched market and the fact that most of the studies
of SGB markets in developing countries rely purely on self-reported data, we can consider the data
from this study precise enough to understand trends in the studied population and estimate the
effectiveness of the AEP on targeted SGBs, as well as to compare with others.
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