Dragon's Den UK: a comparative analysis of the growth of featured firms

Dragon's Den UK: a comparative analysis of the growth of featured firms by Nuno Filipe Costa Lopes Internship Report for Master in Management Faculdade de Economia, Universidade do Porto Supervised by: Miguel Augusto Gomes Sousa September, 2015 i Biographic note I am Nuno Filipe Costa Lopes, born on the 19th of January 1990, in Braga, Portugal. I have concluded a bachelor in Economics at Faculdade de Economia da Universidade do Porto in 2013, the same year I later enrolled in the Masters in Management program in the same university. During my studies there, I was in most years part of the Handball team of the faculty, competing in the regional and national university championships. During the second academic year of the Masters’ program, from September to December 2014, I joined Ernst & Young for a curricular internship in their Transaction Advisory Services department. This internship served as the motto for the work hereby presented. Recently, in May 2015, I moved to Amsterdam in the Netherlands to join Atradius, a trade insurance global company, where I started working as a Financial Controller for the IT department. ii Acknowledgments Before proceeding to the actual content of this study, I'd like to acknowledge everyone who, in any way, has helped me to complete this important stage of my life. First, for everything they have ever done for me, all the support provided, whether academic related or just on a personal level, I'd like to thank my family and friends. But most of all, to my parents, for all the sacrifices they made for me to be able to be where I am today, whether they were financial sacrifices, time sacrifices or just emotional sacrifices, for all the education they themselves provided me with from a young age, always encouraging me to go further and push myself to constantly improve and learn. Secondly, I'd like to thank Ernst & Young for the opportunity they gave me to have a first work experience, to join their team and learn from their business and activities, as well as for their availability to help me get what I needed to successfully complete this journey. I grew a lot in those three months, I gained skills and knowledge on the industry I couldn't have otherwise, and I met some extraordinary people who worked for the company. I'd like to specifically thank my counselor, José Torres, who was always very helpful with my questions, doubts and requests. At last, I'd like to thank to everyone in the University who has helped throughout this academic path I have taken the last 7 years of my life. To my colleagues which I have learned together with, often helping each other, to my teachers who not only taught me the knowledge I have gained, but also shared with me their personal experiences and took my education to the next level. And especially, to Professor Miguel Augusto Gomes Sousa, my supervisor for this work, for all the support, guidance, discussion and critics that he provided me with throughout these months, without whom this work would not be the same. To all, my humble thank you, you are all in some way present in this work. iii Abstract Reality shows in television featuring business angels, such as Shark Tank and Dragon's Den, have gained a lot of popularity in recent years. They bring to the invited companies not only the possibility to raise capital for their company next to business angels, but also everything that 10 minutes of publicity on national TV can bring. Although business angels have been a widely studied topic, this specific subject of TV shows featuring them has been so far ignored in research, with no studies regarding the effects this kind of show has, either on the featured companies or the economy of the country in which it airs. This particular study tries to analyze the effects that a TV show like this can have on the featured firms, by analyzing their growth before and after the show airing, alongside the growth of similar companies, and making comparisons based on the different decisions they take on and after the show. While addressing several issues along the way, the main question to answer is if whether or not striking a deal in the show is the best outcome for the future growth of the company. The gathered data and further analysis curiously shows no statistical evidence to support such claim, while also providing some other insights. JEL-codes: D92, O12 Key-words: Business Angels, Dragon's Den, Total Assets, Investment, Firm Growth iv Contents Biographic note .................................................................................................................................. i Acknowledgments ........................................................................................................................... ii Abstract .............................................................................................................................................. iii List of tables ........................................................................................................................................ v List of figures ..................................................................................................................................... vi List of annexes ................................................................................................................................. vii 1. Introduction ............................................................................................................................ 8 2. Literature Review .............................................................................................................. 11 2.1 Business angels and the equity market ..................................................................... 11 2.2 Business related reality TV shows .............................................................................. 16 2.3 Total assets growth rate as proxy for growth ......................................................... 17 2.4 Similar studies ..................................................................................................................... 18 2.5 Critical review of literature ............................................................................................ 19 3. Methodology and data ...................................................................................................... 21 3.1 Data collection ..................................................................................................................... 21 3.2 Comparable groups ........................................................................................................... 24 4. Results and discussion ..................................................................................................... 27 4.1 Overview of all data .......................................................................................................... 27 4.2 Firms without offers ......................................................................................................... 29 4.3 Firms who accepted offers vs. Firms who rejected offers .................................. 30 4.4 Firms with final deals vs. Firms with rejected/failed deals .............................. 33 4.5 Other results ........................................................................................................................ 35 5. Conclusions .......................................................................................................................... 37 6. Limitations and critics ..................................................................................................... 39 References ........................................................................................................................................ 40 Annexes ....................................................................................................................... 44 v List of tables Table 1 - Overview of the companies' data..................................................................... 23 Table 2 - Growth of all firms .......................................................................................... 27 Table 3 - Accumulated growth of all firms ..................................................................... 28 Table 4 - Growth of firms without offers ....................................................................... 29 Table 5 - Accumulated growth of firms without offers .................................................. 30 Table 6 - Growth of firms who rejected offers ............................................................... 30 Table 7 - Growth of firms who accepted offers .............................................................. 31 Table 8 - Accumulated growth of firms who rejected offers .......................................... 32 Table 9 - Accumulated growth of firms who accepted offers ........................................ 32 Table 10 - Growth of firms with rejected/failed deals .................................................... 33 Table 11 - Growth of firms with concluded deals .......................................................... 33 Table 12 - Accumulated growth of firms with rejected/failed deals .............................. 34 Table 13 - Accumulated growth of firms with concluded deals ..................................... 34 Table 14 - Averages of all proposals and offers ............................................................. 35 vi List of figures Figure 1 - Breakdown of groups by stage and their sample size .................................... 25 Figure 2 - First comparison ............................................................................................. 26 Figure 3 - Second comparison ........................................................................................ 26 vii List of annexes Annex 1 – Similar studies table ...................................................................................... 44 Annex 2 - Database of firms receiving offers ................................................................. 45 Annex 3 - Database of firms without offers ................................................................... 47 8 1. Introduction For the past few years, all over the world we have seen reality TV shows in a business environment prosper and gain recognition (Edwards, 2006; Lee, 2014). Shows such has Shark Tank, Dragon's Den or The Apprentice have been broadcasted and franchised in a large number of countries, as we see an entrepreneurship wave rising seemingly everywhere. Shark Tank or Dragon's Den, title depending on the country where it is aired, consists of a TV Show featuring 5 business angels from the country, who listen to different pitches from entrepreneurs who have started their own business and are looking for capital to grow them. These business angels consist in individuals with vast wealth who use it to invest in private companies and help them grow, with hopes of future return on their investment (Deakins and Freel, 2003; Gregson et al., 2013; Shane, 2012). In Portugal, the first season of a Portuguese version of the show, named after the American version (Shark Tank), was aired during the period this dissertation was carried on. The Portuguese version of the show is produced with the main sponsorship of Ernst & Young (EY), the same company in which, for the last three months of 2014, I did an internship while integrated in the Transaction Advisory Services department, a department focused mainly on due diligences of potential M&A deals. When Shark Tank was announced, and I found that EY was the main sponsor, I knew I had found the subject for my internship report. The subject is highly relevant when we take in look the current situation of the country itself. The economic outlook of Portugal has suffered in the recent years, as the latest crisis was heavily felt and condemned Portugal to an intervention by the Troika for financial rescue, the tripartite committee led by the European Commission with the European Central Bank and the International Monetary Fund, with the economic growth of the country being held back as austerity measures were put in place. Recent economic indicators for the recent year and forecasts for the next years by such institutions as the IMF itself start to paint a brighter future, and the push for entrepreneurship made in the country has undoubtedly played his part. This push made 15 financial aspect, overcoming the funding problems of the firm, active angels also provide the investee firm with their own management expertise, their experience and knowledge in the business world, they provide them with access to their own network of contacts, opening up new opportunities for the firm, they can give the firm some technological stimulation by arming it with new tools, while also making the firm more credible in a financial point of view, leveraging it for further funding from other sources such as banks or venture capital firms, as the risk of the firm is reduced by their investment (Harding and Cowling, 2006; Macht and Robinson, 2010; Mason, 2006). Prowse (1998) also points out that angel investors can also help the investee firm by hiring top management personnel with deep knowledge on the industry, recruit valuable members for the board, or help on more specific aspects of the business such as solving major operational problems, evaluating capital expenditures or helping with the definition of the firm's long term strategy. Even the entrepreneurs themselves often recognize that the experience of the business angels, their knowledge and expertise are more valuable to them than the actual financial input (Lindstrom and Olofsson, 2001). Hence, due to the high mortality rate of start-up firms, with more than 50% of start-ups in Europe closing their businesses within 5 years of their birth (European Commission, 2003), the angels become a critical factor in the hopes of dodging this end, a help that any young firm would be grateful in having. In the light of this information, it is good news that the number of business angels, as well as the number of actual deals that they agree on, are on the rise (Brzozowska, 2008). This is probably due also to an increase in the interest on Entrepreneurship, as more and more people dream with their own business, as we can observe in the USA with the general population's past dream of owning their own a house shifting nowadays towards owning a their own business, a trend seen in Europe too. This creates more opportunities for the angels to invest as more companies are "investable". In a timeframe perspective, most angels have an investment horizon of five years (Prowse, 1998), meaning they hope to get a return on their investment within that time, since studies have shown that the most value added by investors actually happens within the first few years of the investment, when the impact of their presence and 16 added benefits is really felt (Bertoni et al., 2011). Therefore, in a way, it is within that timeframe that they will have the best return on their investment. 2.2 Business related reality TV shows The business world has been present in television for many years, but up until very close to the turn of the millennium, it was seen in very different eyes than it is seen today. Up until then, no real TV shows were made with the purpose of deeply exploring or focusing on the business aspects and particularities of any person, situation or subject. Business television was far away from popular culture, and was reserved for targeted programs to business people. Usually in popular culture, business men in fictional TV shows tended to be represented has bad, sneaky and fraudulent, always leaving a bad impression and misrepresenting the people involved in such an important area of our life. This was due to a vision from the executives that 'money was boring' for television, that predominated for many years (Edwards, 2006). In the UK, this changed in the 1990's with the appearance of shows in the business entertainment format such as the Troubleshooter, and has continued since in the new millennium with shows as Dragon's Den and The Apprentice. With these changes in the TV environment, airing shows that reflected the values of entrepreneurship, the TV industry even learned some of its values for itself and started its own mini-revolution, leading to changes in its culture and also starting the rise of independent TV stations, while inciting the same entrepreneurship values to their audience (Lee, 2014). These changes were also reflected in the popular view of what is an employee. The public conscious was saturated with the image of a "loyal company man", the only image that was projected and promoted towards them (Sampson, 1995). This also changed as the image of the risk taking entrepreneur started to be projected too, after being away for so long, along with their failures and successes. While showing this, their journeys, their ups and downs, their good and bad sides, shows such as the Dragon's Den, as suggested by Down (2010), act as a guide for 17 the viewer, providing them with a list of do's and don'ts in order to succeed, what are the behaviors that a successful entrepreneur should have. Nolan (2012) argues that a show like Dragon's Den "relies upon and extends its audiences' literacy in the language of business", providing them with not only quality entertainment, but also giving them the chance to learn and get a few key points on how to achieve success in business. A similar point is made by Kiersey (2014), who argues that this kind of shows give the viewers a feeling that by taking their message seriously and following their advices, a business can succeed even during a bad recession. The show has been featured in many countries from all over the world, with all types of backgrounds, while its format has also been widely spread and useful, particularly in developing countries (Jubraj, 2015). The United Bank of Africa even introduced a similar TV show in 2008, stating that "Dragon's Den is unique and different from other business reality shows and will further the bank's aim to promote entrepreneurship and innovation in Africa." 2.3 Total assets growth rate as proxy for growth Since the purpose of this paper is to evaluate the growth of the companies that were participants in the UK version of Dragon's Den, whether or not they successfully completed a deal, it becomes quite important to discuss how will this be made, what kind of data and framework will be used, because available data regarding entrepreneurial firms is rather slim and rare (Brav, 2009). Garnsey et al. (2003) analyzed growth measures for young companies, and classified them into three different types: measuring in terms of inputs (such as investment or number of employees), in terms of value (such as own assets or market capitalization) or in terms of outputs (such as sales or profits). A review of the studies made on growth was also done by Delmar (1997), who concluded that overall the measures of growth most often used are growth of sales, employees, assets and market share. 18 Due to the scarcity of reliable information on data, for the purposes of this work we will focus on the measures in terms of value as per Garnsey et al. (2003), most specifically the value of assets. This is because the data available for this analysis lead to the conclusion that data regarding inputs or outputs is even more scarce and rare, while information on assets is more easily available in databases such as Amadeus, at least regarding firms based in the UK, which is the scope of this work. As in other studies such as Alarape (2007), Glancey (1998), the total assets growth rate of firms will be used as proxy for their actual growth rate. Revest and Sapio (2013) actually make a comparison between private companies and listed companies utilizing, among other data, the total assets growth rate, with the purpose of studying the relevance of what they call the Alternative Investment Market towards the growth of a firm. Hence, the total assets growth rate will be calculated in accordance to Weinzimmer et al.(1998): 𝑔= (𝑇𝐴1− 𝑇𝐴0) 𝑇𝐴0 where g represents the total assets growth rate for the period between 0 and 1; TA1 is the total assets value at time 1; TA0 is the total assets value at time 0. We shall also keep in mind that the relative growth of a company has a negative relationship with not only that said company's age, but also with its size (Evans, 1987). 2.4 Similar studies Despite not yet having been made studies that analyze the performance of companies who have participated in TV shows such as Dragon's Den before and after the show, there have naturally been studies who have analyzed the growth of companies 19 in different situations and circumstances throughout a period of time, which in all fairness is the exact goal of this study. Different methods have been used, and a compilation of a few studies taking a similar approach for an analysis on other unrelated subjects can be found in the Annexes. Most of them use the total assets growth rate as a unit of analysis for firm growth, even if not as the only unit of analysis in their study, but just one of several. The methods for analysis used vary from Correlation and Regression to try to establish deltas between the featured groups of each study. The method applied in the present study, however, will not be one of those, as available information for this topic is not enough to make a proper regression or correlation analysis with a specific purpose. Solomon (1997) on the other hand uses stock prices as unit of analysis, which essentially represent a market evaluation of the company's assets. He evaluates the value added by consultants to their client firms, using an approach of setting a timeframe of a certain time before and after the consulting engagement. This is also important since for the purposes of this work there is the need to set a timeframe around the airing of the show itself, to analyze the growth between it. Hence, despite these studies being on different and unrelated subjects, bits and pieces of their approach can be adapted into this work. 2.5 Critical review of literature When we take a look on what's available as literature on Business Angels, it is obvious that a lot of research has been done on this topic, on their characteristics and features, on the type of benefits that they bring to their investee firms, among other things. However, it seems that a more analytical approach to the benefits is still lacking. This topic has essentially been covered mostly on a theoretical basis, which despite 20 being understandable due to the difficulty of gathering information, leaves the door wide open for other authors to step in and contribute with models and analytic analysis on the subject. Even a subject somewhat easily quantifiable, such as an analytical approach to the difference of performance between VC backed firms and Angel Investors firms, is a subject that only as seen the work of Fairchild (2011), and can still be further developed. This is even more the case when talking about business related television. All literature found is a theoretical approach on the subject, the evolution of the business thematic in television overtime, how it has changed and how it has produced changes. This however is not really backed up with numbers, neither other potential studies have been made addressing any of the numerous questions one could ask in an analytical point of view towards the benefits (or not) of these shows. Hence, this is what this work aims to do, an analytical study in this fields which are, so far, much more based on theory. The goal is to provide with a first analytical analysis on the participants of a show such as this one, gathering data from their performance throughout the years and assessing with numbers the different growths of the firms depending on the outcome of their participation of the show. 21 3. Methodology and data In order to answer the main question of this study (Is striking a deal on the show really the best outcome for the future growth of the firm?), the UK’s Dragon’s Den was chosen as the analyzed program, since not only is the show now on the 12th season, and so has a fairly big enough pool of data to study, but also the geography of the featured firms in the show provides us with the ability to access the Amadeus Bureau Van Dijk database to retrieve their financial information, something not possible with US or Canada companies, the two other biggest versions of the show. 3.1 Data collection In order to collect the data, season 6 until Season 10, aired between 2008 and 2012, were watched. Season 6 was chosen has the point of beginning since it was essentially the borderline, as information on companies from past seasons was less likely to find in Amadeus Bureau Van Dijk. Season 10 was chosen as the end because it was the last one that allowed for an analysis of what has happened at least 2 years since the show itself aired. From a total of 184 companies featuring the episodes, there were 96 companies who received an offer from at least one of the Dragons, with 83 of them being accepted and 13 rejected. There were also 88 companies who had not received any sort of offer. A thorough search was then conducted in the Amadeus Bureau Van Dijk and Duedil databases, accessing those companies balance sheets in order to gather the information related with the total assets of the companies. For comparison purposes, a peer group was selected for each one of the companies, comprising the 10 firms in the same industry (according to the NACE code) and in the same country – with the closest total assets value to each sample company in a given year. After retrieving the same relevant financial data as the one previously 22 retrieved for the analyzed companies, the median for each group of 10 was calculated. The use of the median instead of an average was chosen to lower the possible influence of the existence of outliers in the sample. At this point, the sample was reduced from 96 companies who had received an offer to 80 who also had relevant financial information available. The companies with no offers were also reduced from 88 to 44 with the same sort of information. The next step was to define a timeframe to analyze the companies. Taking for example the work of Solomon (1997), the decision was to focus on the performance of a short time before the show aired, and a longer period after the show aired, to compare the evolution of the growth measures in the different situations. Therefore, knowing the date in which each episode had aired, the period defined starts in the year before an episode was aired, and ends two years following it. This timeframe essentially comprises 3 growth rates, one for each full year of the analysis, which means that the financial data on 4 consecutive years of the company was gathered. The periods will be represented as: • year -1 (the year just before the airing of the show) • year 1 (the first year after the airing of the show) • year 2 (the second year after the airing of the show) This further reduced the sample, since not all of the companies with financial information available actually met all these requirements. Of the 80 companies who had received an offer and had financial data available, only 35 of them had it for the required 4 years. However, 13 more companies had the data for the first three consecutive years and so could be used in partially in our analysis. This means that the third year growth rate, which is related to the second year after the airing of the show, will have a slightly smaller sample. Hence, we got a final sample of 48 companies who had received an offer and met the necessary requirements to be part of the analysis. Moreover, regarding the set of companies receiving no offers in the show, the final sample was further reduced to 16 23 firms meeting the requirements. Table 2 provides a breakdown of these the trimming down of the sample: Table 1 - Overview of the companies' data Total of companies 184 Without offers 88 With all required information 16 With offers 96 Accepted 83 With all required information 41 Rejected 13 With all required information 7 Besides these 3 years of the chosen timeframe, the data (for the companies who had it available) from the year before and after the timeframe, i.e. year -2 and year 3 as they will be referred to from now on, was also retrieved and will be presented, with an even smaller sample. This will not be part of the main analysis, the comparisons among the different groups, but will instead just be used for some general considerations on the sample as a whole. Finally, for all those final sample companies, the total assets growth rate was calculated in accordance to Weinzimmer et al. (1998) as previously mentioned. The same calculation was done to the total assets medians of each of the companies' peer groups. These growth rates were calculated to represent the growth rate performance of similar firms in the same industry. It was also important to find out whether or not the accepted deals on the show had actually gone through or not. As stated before, the deals broadcasted on the show are not final or binding, as due diligences must be conducted afterwards, and further negotiations may occur. 24 After a search for news on these deals was conducted turned out only a few results and clarifications, this was complemented by the work of Tigermobiles 1 , who conducted a research on the developments of companies who featured Dragon's Den UK. To answer this particular question, they accessed a paid website managed by the UK Government that provides information on British firms, Companies House 2 , and searched the Directors, Shareholders and Board Members history of the companies to access if any of the Dragons was ever featured in them. This allowed us to better understand what actually happened after the show for the majority of companies, leaving just one company with no information, who was therefore left outside of the sample. Of the final 48 companies left in the sample receiving an offer from the Dragons, of which 41 had accepted it, only 12 of these deals actually went through, with 29 falling in the due diligence stages. This is actually in line with reported news articles regarding the outcome of such deals in the UK version of Dragon's Den. According to a report by Burn-Callander 3 , over half of the deals made on the show in that country don't actually make it through the due diligence stage, and fall through. 3.2 Comparable groups In Figure 1, we can have a better understanding at the breakdown between groups that the featured firms endured, as well as the number of firms in each group present in the sample, assigning a number to each one of these groups for better identification. 1 Dragons' Den - Where Are They Now? https://www.tigermobiles.com/dragons-den/ 2 Companies House https://www.gov.uk/government/organisations/companies-house 3 "Half of Dragons' Den investments fall through after the show" http://www.telegraph.co.uk/finance/businessclub/money/11425328/Half-of-Dragons-Den-investmentsfall-through-after-the-show.html 31 Table 7 - Growth of firms who accepted offers Accepted n = 16 n = 41 n = 41 n = 30 n = 18 Year -2 Year -1 Year 1 Year 2 Year 3 Featured Firms 89.84% 174.21% 47.98% 35.87% 5.33% Peer Groups 6.22% 13.95% 13.00% 10.96% 8.64% Peer Adjusted Variation 83.63% 160.26% 34.98% 24.91% -3.31% The first conclusion we can take from these results, is that the companies who rejected the offers have a much higher growth versus their peers during the pre-show years than the companies who accepted the offers on the show, being almost the double in percentage terms. We can only speculate whether the rejection was due to greedy entrepreneurs, who felt they would deserve a better deal than the deal offered, or due to greedy investors that were trying to undervalue the deals, leaving no choice to the entrepreneurs but to reject them. Deeb (2013) touched precisely this point in his previously mentioned article for Forbes, making a comparison of the deals made on Shark Tank to the deals made by VC's firms, concluding that the valuation standards on the TV show were much lower than in traditional VC's, and that the dilution levels much higher. This is an observation also supported by Greathouse (2014), who argues the investors in the show usually under-value the companies. Some data regarding this argument will also be presented in the last point of this section. Since these companies rejecting the offers show larger growth differentials, they are possibly more strong on their valuation ambitions and tend to resist more to the under valuations of the investors, showing more confidence and persistence on their beliefs. However, after the airing of the show, the companies who have accepted the offers invert the tendency and have peer adjusted variation almost 10% larger than the companies who rejected. Bertoni et al. (2011) claim that most benefits collected from investments are created in the first years after the injection of capital, and this evidence seems to support that claim. However we should remember that in this particular analysis, these accepted 32 deals include the ones that actually failed to progress past due diligence and so a deep analysis will be needed to assess those claims. Another explanation could lie within the good publicity of actually striking a deal in the show. Good comments and support by the investors in the show, positive attitude and the psychological aspect of a success could possibly induce strongly in the audience the notion that the company provides a good service/product. On the third year after the show we see the abnormal growth for both groups of companies end, supporting these last couple of claims. Looking at the accumulate growth in Tables 8 and 9 the group that accepted the offer presents a higher peer adjusted growth rate than the group of companies that rejected the offer: Table 8 - Accumulated growth of firms who rejected offers Rejected n = 7 n = 5 Acc. To Year 1 Acc. To Year 2 Featured Firms 111.08% 467.83% Peer Groups 18.13% 60.23% Peer Adjusted Variation 92.95% 407.60% Table 9 - Accumulated growth of firms who accepted offers Accepted n = 41 n = 30 Acc. To Year 1 Acc. To Year 2 Featured Firms 307.64% 554.72% Peer Groups 32.75% 44.56% Peer Adjusted Variation 274.88% 510.16% This results suggest once again that accepting an offer in the show can bring good publicity for the firm and enhance the growth, as the stamp of success in the eyes of customers can be powerful. Finally, it is important to notice the small number of firms which rejected the offer, making these results difficult to extrapolate. 33 4.4 Firms with final deals vs. Firms with rejected/failed deals Moving to the last comparative analysis, we look at the stage after due diligence has been performed and the deal outcome is final and definite, featuring the deals that actually took place versus the deals that were rejected or fell through at some point of the process. Tables 10 and 11 show the results for all the deals rejected or failed and for deals that went through, respectively: Table 10 - Growth of firms with rejected/failed deals Rejected/Failed deals n = 18 n = 36 n = 36 n = 27 n = 14 Year -2 Year -1 Year 1 Year 2 Year 3 Featured Firms 101.80% 215.60% 52.00% 57.27% 8.40% Peer Groups 6.76% 17.98% 11.74% 7.62% 5.36% Peer Adjusted Variation 95.04% 197.62% 40.26% 49.65% 3.04% Table 11 - Growth of firms with concluded deals Deal went through n = 3 n = 12 n = 12 n = 8 n = 7 Year -2 Year -1 Year 1 Year 2 Year 3 Featured Firms 151.36% 126.88% 30.29% 61.91% -2.83% Peer Groups 16.12% 1.87% 16.35% 31.28% 19.62% Peer Adjusted Variation 135.24% 125.01% 13.94% 30.63% -22.46% The first results show us that the peer adjusted variation is highly positive in both cases before the companies featured in the show. However, when we analyze the years after the airing of the show, we find that both in year 1 and 2, the companies that didn’t get any deal done have a peer adjusted variation that is the triple of the companies who actually concluded the deal with the Dragons in year 1 and nearly the double in year 2. This is contrary to what was expected, which was that the firms who got the Dragons' financial and entrepreneurial help would outperform the firms who decided to do without it. 34 To what reason(s) can we deem this discovery? One possible explanation can be found in Landström (1993) that states UK angels tend to be more passive than active, not getting much involved and providing the investment and reading reports. Could this be the case, that these particular TV investors actually end up being too passive and don't contribute much to their firms growth, leading to this observations, and would we see different results if the geography of the study was different? The accumulated tables highlight even more these differences, as we can see in Tables 12 and 13: Table 12 - Accumulated growth of firms with rejected/failed deals Rejected/Failed deals n = 36 n = 27 Acc. To Year 1 Acc. To Year 2 Featured Firms 323.10% 655.94% Peer Groups 34.25% 48.17% Peer Adjusted Variation 288.85% 607.77% Table 13 - Accumulated growth of firms with concluded deals Deal that went through n = 12 n = 8 Acc. To Year 1 Acc. To Year 2 Featured Firms 146.57% 158.81% Peer Groups 19.74% 42.18% Peer Adjusted Variation 126.84% 116.63% Here, the difference is even larger, raising more doubts on the actual benefits of an offer on the show. Another important factor that may explain the difference is the fact that not getting any deal with the Dragons, whether the firms rejected their initial offer or their deal fell through for some reason along the due diligence stage, does not mean that they didn't receive an investment from elsewhere. Since they were actually looking for funding, it's possible that in most of the cases they actually ended up getting funds from another investor, being a business angel or not. There is not much information on this, but from research on the companies, we can say that of the 29 companies whose accepted deal fell through in the due diligence 35 stage, 6 was because the entrepreneur refused the offer and found funding elsewhere. For the remaining 23, for most of them the reasons are unknown. We can only speculate that these companies actually found more committed investors, more active angels, or even decided to go to a VC firm, realizing they could get a better deal there. It is also curious to realize that on the third year after the show, the peer adjusted variation on both groups plummets, with the companies with definite deals with the angels actually growing 22% less than their peers. Again, we find evidence to support the claim made by Bertoni et al. (2011) that most value added by investors is shown in the first years after the investment. 4.5 Other results Looking deeply at the possibility defended by both Deeb (2013) and Greathouse (2014), that investors on the show constantly undervalue the companies and which may explain the higher growth of firms who reject the deals, data on the proposals by the investors was analyzed. Table 14 provides the averages of the proposals by the entrepreneurs which received an offer, as well as the final offers from the investors, whether they were accepted or not: Table 14 - Averages of all proposals and offers (GBP) First proposals by Entrepreneurs Final Offers from Dragons Investment 92,900 101,900 Equity percentage 14.9% 36.6% Firm Valuation 771,300 298,900 The fact that the average investment offered is higher that the proposals can be misleading, since one of the rules of the show is that the Entrepreneurs must get a full 36 offer on their asked amount, i.e., the investment offer of the investors can't be lower than what was proposed. However, when we look at the equity percentage, we see that the final offers average is of more of the double than what the entrepreneurs first were aiming to dilute. The firm valuation average from the offers brings the value of the firms down to less than half of what the entrepreneurs were hoping for. This data shows an even more disparity than the one that Deeb (2013) mentions in her article, based on the American version, suggesting that UK investors in the program are even more tough on their demands. This data seem to support the defense of an undervaluation of the companies, especially if we take into account that the median of revenues of the companies is 300,000 GBP, which would essentially mean that the firms are being evaluated at a multiple of one time its revenues by the investors from the show. Finally, we can look at the mortality rate among the featured companies. According to the available information, 17% (16 out of 94) of the companies receiving offers have dissolved by the time this study, a percentage that remains consistent with each different group: 2 out of 13 rejected deals, 8 out of 46 deals that fell through and 6 out of 35 deals that followed through were dissolved. A report by the European Commission (2003) sets the mortality rate for start-ups as over 50% after 5 years of inception, and while the timeframe is not the same, since we are bundling companies with different years of operations, some with more than 5 years and some with less, one could still assume that, according to the available data, the mortality rate among the featured companies is lower, whether they strike a deal or not. However, this could be biased by the fact that the show producers perform a pre-analysis and almost only companies with high growth actually feature the show, so therefore would perhaps be more probable to succeed. 37 5. Conclusions The objectives of this study were to, by analyzing the growth of firms featuring reality shows in television featuring business angels, find any possible trends or deviances in their growth based on the outcome of their participation. By doing this analysis, our hope was to answer the main question supporting this study: Is striking a deal on the show really the best outcome for the future growth of the firm? The first conclusion that we can get from this study is that, even if a company is featuring on this kind of show, success is not granted from any perspective. From the analysis made, it was not found any statistical evidence that supported the common belief that just an appearance on the show can bring benefits and increase the growth of a firm just due to the publicity. However, it's undisputed that featuring in this kind of show may provide an initial hype on the company, while its long term growth key points lie elsewhere. This study did also not found any evidence that achieving a deal with the investors on the show will lead to greater growth performance of the company. Contrarily, the results actually point quite the opposite. As our result showed, the companies who passed on the Dragon's deals tend to show a larger growth than the companies with confirmed deals. This may suggest not only that these entrepreneurs might have got the capital they were looking for from other possible investors, which seems rather likely since they got publicity with both customers and other investors by featuring in the show, but also, this being the case, it allows for speculation on whether by doing so they are likely to find more suitable and/or committed investors, resulting in a higher growth. This can be explored by further studies focusing on what actually happened with the companies who passed on the deals. All in all, an appearance in a show such as Dragon's Den, as well as making a deal within the show, is not, in a general way, necessary linked with superior growth. Obviously, there is much more that needs to be studied in this field. Jobs created by these companies could be strong possibility for another further study. Sohl (2008) estimated that business angels helped create 200,000 new jobs in the USA in 2007 alone. It is then widely accepted that these individuals, in general, help the economy grow by working with high-growth SME's to achieve their full potential. Is this also the 38 case regarding the companies in a show such as this? Does it have a significant impact on the country's economy? It is also worth noting that, with regards of Portugal, the first season of the show has just finished, and according to a report written by Barbosa 1 , the percentage of deals made was much higher than in the analyzed series here in this study. They reviewed 85 firms, and made deals with 60 of them. This represents a success rate of 70%, much higher than in the UK where it sat at 45% (83 companies out of 184). The same report features a comment made by one of the investors, claiming that they expect that 80% of the agreed deals actually follow through to being actual investments. If this ends up being true, again we see a much higher percentage than the one in this sample, which stood at 42% (29 out of 70 companies), and is in accordance to other reports from the UK . This could represent a very different set of data for a possible Portuguese version of this analysis. Where the Portuguese investors much more relaxed with their investments? Another open door for a further study, but it seems as if they weren't as selective and demanding as the British investors in this sample. 1 Tubarões do Shark Tank investiram mais de três milhões de euros em cerca de 60 negócios http://www.dinheirovivo.pt/Buzz/interior.aspx?content_id=4462730 39 6. Limitations and critics The main problems of the sample are related to the lack of available information among entrepreneurial firms (Brav, 2009). This fact made the already not large sample of firms reduced even further as more than half of the featured companies did not have the necessary information for an analysis, and left no choice but to focus the analysis on the total assets growth rate, due to the absence of Profit and Loss accounts. Here, the analysis of revenues or profits would allow for a more accurate view on the actual extent of the impact of featuring in television on sales numbers. There is also the geographical limitation of the sample, as this is based on the UK version of the show. This can be a bias on the sample towards the specific conditions of the country's economy, and also due to the personality traits of the BA's of the country, more passive according to Lindstrom and Olofsson (2001). The behavior of BA's of another country might be different, and lead to different conclusions, as we are already seeing significant differences in just the first season of the Portuguese version. It is also worth to mention that this analysis, while focusing on the available information, leaves out all other possible external factors, as well as some other factors inherent to each firm that can affect their performance. Whether it is the fact that they actually got an investment deal somewhere else, specific business decisions or other conditions that arose, these are all factors that are not taken into account and may distort the analysis. 40 References Alarape, A. A. (2007). Entrepreneurship programs, operational efficiency and growth of small businesses. Journal of Enterprising Communities: People and Places in the Global Economy, 1(3), 222–239. Bertoni, F., Colombo, M. G., and Grilli, L. (2011). Venture capital financing and the growth of high-tech start-ups: disentangling treatment from selection effects. Research Policy, 40, 1028–1043. Brav, O. (2009). Access to capital, capital structure, and the funding of the firm. Journal of Finance, 64, 263–308. Brettel, M. (2003). Business angels in Germany: A research note. Venture Capital, 5, 251–268. Brzozowska, K. (2008). Business Angels in Poland in Comparison to Informal Venture Capital Market in European Union. Engineering Economics, 2(2), 7–15. Davidsson, P., and Honig, B. (2003). The role of social and human capital among nascent entrepreneurs. Journal of Business Venturing, 18(3), 301–331. De Bettignies, J., and Brander, J. A. (2007). Financing entrepreneurship: bank finance versus venture capital. Journal of Business Venturing, 22, 808–832. De Clercq, D., and Sapienza, H. (2006). Effects of relational capital and commitment on venture capitalists’ perception of portfolio company performance. Journal of Business Venturing, 21(3), 326–347. Deakins, D., and Freel, M. (2003). Entrepreneurship and Small Firms. McGraw-Hill Education, Maidenhead. Deeb, G. (2013). "Comparing “Shark Tank” To Venture Capital Reality". Forbes, http://www.forbes.com/sites/georgedeeb/2013/10/09/comparing-shark-tank-toventure-capital-reality/ Delmar, F. (1997). Measuring growth: methodological considerations and empirical results. In Entrepreneurship and SME Research: On its Way to the Next Millenium (Vol. Ashgate, pp. 190–216). Down, S. (2010). Enterprise, Entrepreneurship and small business. SAGE Publications. 47 Annex 3 - Database of Firms without offers Company name Airdate Description Investment Asked Equity Offered Air Oasis 21/07/2008 purifier of water 125 10% Layline 21/07/2008 sheets with a line dividing in the middle 50 20% Saboteur Crime Prevention 28/07/2008 crime prevention housetools 275 10% Carbon 6/ Screen Machine 28/07/2008 device for parents control kids TV time 150 15% Shoes Galore Ltd 04/08/2008 shoe selling franchise 100 30% Very PC 04/08/2008 energy efficient computers 250 5% Fresh Olive Oil Club 11/08/2008 Club that distributes prime olive oil 50 10% FB1Frank Bisson 1 18/08/2008 blade for cutting hair 100 5% Ifoods.tv 18/08/2008 social network about food 100 10% Ladderbox Uk 25/08/2008 Tool tray that multi-fits to the top of all ladder types 100 15% Juliette's Interiors 25/08/2008 site selling french furniture and mirror 106 20% Discrete Heat 01/09/2008 central heating 150 10% TinyDeol.com Ltd 01/09/2008 fat and cholesterol free curry sauces 42 15% prestige pet's products uk 08/09/2008 bowl for dogs 120 15% Apocalypse Ltd 15/07/2009 hardcore horror live entertainments 200 20% The Wholeleaf Co 22/07/2009 natural disposable dinnerware 120 20% Dusty: A Life in Music 29/07/2009 musical 250 25% Oarsome Potential 29/07/2009 protective grip for sports 75 20% Spey Bay Mussel Farm 05/08/2009 mussel farm 100 20% Clever Bins 05/08/2009 trash bins 65 10% Wine Innovations Ltd 12/08/2009 pre filled wine glasses 250 25% Saboteur Crime Prevention 19/08/2009 electric blind closer 120 20% Grillstream 19/08/2009 easy to clean grill tray 120 15% Bound Biographies 26/08/2009 biography productions 75 20% Bee Automobiles 26/08/2009 electric cars 2500 30% Extreme Fliers 02/09/2009 remote control mini helicopter/car 75 15% Butterfly Technology 02/09/2009 product to squeeze all from a tube 75 15% Flow Signals 14/07/2010 21 century traffic signals 50 10% Flex FX Productions 14/07/2010 A Bollywood dance company which provides a wide range of entertainment from arena shows to corporate events 200 30% subeo 21/07/2010 personal submarine 1450 45% EDH Washing Line 21/07/2010 80 25% Tatty Bumpkin 26/07/2010 A children's lifestyle brand that includes clothing, yoga, toys and books. 200 20% Aquatina 26/07/2010 A collapsible, concertina shaped refillable water bottle that aims to reduce bottled water waste 100 10% Rotaball 02/08/2010 An outdoor leisure activity based on football in a similar genre to swingball. 150 10% Blooming High 02/08/2010 A stackable outdoor plant container 50 15% Black Nut Iberian Pig Feed 09/08/2010 A manufactured pig feed that replaces the acorn, the Black Nut Iberian Pig's natural food source. 100 20% Zigo 09/08/2010 Combined bicycle and buggy. 225 6% Angel Cot 16/08/2010 Suitcase combined infant cot and baby changing station 150 40% Advanced Building Designs 16/08/2010 Various products for the building and plumbing industries, the RadClamp, Radwrench, pump nut removal tool and tap splitter 89 15% Gift Card Converter 24/08/2010 Website to buy/exchange gift cards 50 25% Citidogs 24/08/2010 dogs creche 75 20% yum yums 31/08/2010 Books for children to encourage healthy eating. 100 20% Odourbuster 31/08/2010 A product that can be fitted to toilets and draws the smell out and down the flushpipe when people are using the bathroom. 75 15% Abiie Buggy (My Babiie ltd) 13/09/2010 Buggy that incorporates a changing table 100 10% GaBoom 13/09/2010 Website to exchange computer games 65 11% 48 Company name Airdate Description Investment Asked Equity Offered Miruji Health 31/07/2011 chair to help people lose weight 100 10% The British DJ and MC Academy 07/08/2011 name speaks 150 20% UV body sculpture 07/08/2011 50 20% Rascal Dog Litter Box 14/08/2011 a fresh take on dog litter trays 75 20% My Sea Safe 21/08/2011 detachable safe for sun loungers 150 5% Rico Mexican Kitchen 21/08/2011 mexican food 75 20% Myburgh Designs 28/08/2011 design company 70 20% Aqua Sheko Fish Spa 04/09/2011 fish spa experience with modern Japanese bars 150 30% Brat & Suzie 04/09/2011 hand drawn, illustrated animal t-shirts and jumpers 65 20% Opus Innovations 12/09/2011 baby accessories 50 10% Health Swing 12/09/2011 indoor, progressive, whole-body mobiliser and rehabilitation swing 50 40% Wingz 19/09/2011 Sleeves for women 50 30% Realtor Network Ltd 19/09/2011 real estate agency 50 20% Savvy Lash 26/09/2011 cosmetic tool to safely separate eyelashes 50 20% The Nuttery 26/09/2011 bird feeders 100 15% Romeo Products/ Romeo Shell 26/09/2011 an outdoor shelving system for drinks 50 25% Culicka Ltd 03/10/2011 game toy in a cube 80 10% Redfoot 03/10/2011 folding shoes 300 10% Sendmybag 09/09/2012 service to ship bags 100 5% Abspak 09/09/2012 device for abs while seating 50 25% Third Door Workhub and Nursery 16/09/2012 day care nursery for babies and offices for parents 120 20% Dirty Beach 16/09/2012 Beach bar 100 10% 13 horror ltd 09/09/2012 horror experience books 50 20% Mamka 09/09/2012 e-commerce website 200 10% Lost For Words 30/09/2012 Game show 80 25% Hunting Foot 30/09/2012 products for older people 80 30% The Wheelbarrow Booster 30/09/2012 bag to double volume of barrow 50 10% Camping Bugs 07/10/2012 Glamping 250 30% Sticker Make-up 07/10/2012 eyeliner 50 20% topline dance frame 14/10/2012 dance frame 97,5 15% Queue For You 21/10/2012 app to not wait in line in callcenters 150 1% Fellas 21/10/2012 intimate cleaning wipes for men 60 20% Drumchasers 28/10/2012 percussion-based musical 60 20% Nebo 11/11/2012 raised toilet for back pain 85 15% Purepotions Skincare 11/11/2012 ointments and cream for dry skin 90 15% Caterquip 18/11/2012 refurbished catering equipment supplier 100 10% Dayfame Luxury VIP experiences 18/11/2012 celebrity treatment for a night out on the tiles 100 30% Synagi Intelligence 18/11/2012 hand tool with interchangeable heads for housejobs 95 20% It-soles 25/11/2012 soles for dancing for women in high heels 50 15% Carkoon 02/12/2012 baby seat with air bag 100 20% Boatbox Ltd 02/12/2012 box for top of car that turns into boat 100 16% Melbry Events 27/12/2012 Christmas experience event 100 20% Pucket 27/12/2012 wooden game 50 10%