How to harness automation in the grant advisor sector : a recommendation for UGOO

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How to harness automation

in the grant advisor sector

A recommendation for UGOO

Writer: Zinzi van der Aar. Supervisor: Stephan von Delft.

Contact: zinzivanderaar@gmail.com

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Executive Summary

This study discusses the grant advisor UGOO that operates in the Dutch grant advisor industry. This industry has not been subjected to disruption by automation since its creation thirty years ago. However, the conclusion of this study is that the threat of disruption through automation is one to seriously consider. New developments in the artificial intelligence and machine learning field imply that activities of UGOO are computerizable.

Instead of being disrupted by an upstart competitor, this study recommends self-disruption according to the Step Aside strategy. In this strategy both computers and humans do what they do best. The computers take on the ‘cognitive heavy lifting’, and the human focuses on the activities that are deemed unlikely to be automated soon. In UGOO case, this would mean the consultants would use their creativity and social skills to defend cases for the more challenging WBSO-beneficiaries. For the more clear-cut proposals that only require factual expertise, UGOO could employ computers. In that way, the ‘jobs to be done’ of UGOO’s customers (for example: running a healthy business) will still be fulfilled for all customers, yet UGOO would operate more efficiently.

To convince UGOO to invest in automation now, before a Big Bang Disrupter takes over the market, this study relates the futuristic concept of automation to the concrete challenges UGOO is currently facing.

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I. II. Introduction

The main focus of this study is UGOO, a medium-sized grant consultancy firm. In ten years, UGOO has grown into a company of approximately 25 employees in Amsterdam and Eindhoven, with nearly 400 customers. UGOO operates in the grant advisor sector. This industry has not been subjected to disruption by automation since its creation thirty years ago. In this day and age, where the possibilities of information technology can perform cognitive tasks (from self-driving cars to machines that beat humans at chess) this seems an untenable situation.

In this study, the author investigates if and how UGOO can be disrupted by the introduction of new automation technologies in the grant advisor sector and how to harness future disruptive developments.

Firstly, this study investigates current automation developments and how these can be applied to UGOO activities, assessing the risk of disruption in the grant advisor sector. This subject has not been researched before, yet authors have written about disruption in similar sectors like management consultancy and the legal industry. In these industries disruption has happened, and they can form a relevant parallel to the grant advisor sector.

Furthermore, this study will be the first study that combines a Customer Value Proposition with research on the bottlenecks of current technology to determine the level of which a sector can be disrupted through technology. This will be done by linking tasks that cannot be done by computers to jobs that customers hire a consultant to do.

Then, the study focuses on how to harness possible future disruptive developments. With the results that derive from the first section, a substantiated choice can be made for a strategy on how technology and humans work together. This research first maps the human skills required to fulfill your customer’s ‘jobs to be done’ before deciding what role technology will play in your service.

The outcomes of this research show how the possible future disruptive events in the grant advisor sector, and how UGOO can harness theses, in a way that is both future-proof and pragmatic – preparing UGOO for a bright future.

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III. The Grant Advisor Sector – A Competitive Environment

A. Background

The Dutch government makes available approximately yearly € 2,855,447,500 for innovative

companies in Dutch grant schemes.1

The largest and broadest innovation grant in the Netherlands is the Wet Bevordering Speur &

Ontwikkelingswerk (WBSO) 2. The WBSO provides a fiscal facility that reduces wage costs

for research and development (R&D) employees by lowering their wage taxes and social insurance contributions. In terms of its scope and budget, the WBSO has grown into the most significant Dutch measure encouraging corporate R&D activities (Poot, den Hartog, Grosfeld & Brouwer, 2003). Almost 23,000 Dutch companies in 18 disaggregated sectors benefit from it3.

82% of these companies4 use a grant consultant when they apply for the WBSO. The reasons

companies hire a consultant are the:

- complexity of the application process,

- lack of experience with applying for grants and

- lack of knowledge about the grant possibilities (Bouwer, den Hartog, Poot & Segers, 2002).

Grant consultants specialize in grants to gain the experience and knowledge that companies lack. Therefore they act as an intermediary between an innovative company and the Netherlands Enterprise Agency (NEA), the executive body of the Ministry of Economics responsible for allocating the WBSO.

In exchange, most grant consultants ask a fee over the grant benefits, generally ‘no cure, no pay’. The fees range from 5% to 15%, depending on the level of service and quality the grant

1 See appendix 1. 2_{http://wetten.overheid.nl/BWBR0007746/2016-01-01} 3_{http://www.NEA.nl/sites/default/files/2016/06/Focus_op_speur_en_ontwikkelingswerk_WBSO_RDA_2015.pdf} 4_{http://michielvanveen.vvd.nl/nieuws/12549/antwoord-minister-op-vragen-over-de-mit-regeling-en-wbso}

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consultant can provide5. The sector consists of four large grant-consulting firms. They have specialties in different grant areas and themes6. Because these firms have in-house expertise related to most grant schemes, they can offer customers a “one stop shop” solution. Other advisors in the sector are medium- to small-sized companies and sole traders. These players predominantly have expertise regarding a few grants. The main focus of this study is UGOO, a medium-sized grant consultancy firm, which focuses on the WBSO grant.

B. Trends in the industry

The trends in the industry imply that it will become more difficult to establish the same revenue yearly, yet the costs will remain the same or even rise. The profit margins will therefore stagnate or decline.

Firstly, there are two trends implying revenue will be more difficult to generate:

1. New legislation by NEA results in less potential customers.

The awarded benefits to companies from the WBSO grow every year, from 287

million euro in 1998 to 860 million euro in 20107. The Netherlands Enterprise Agency

(NEA), the executive body of the Ministry of Economics responsible for allocating the WBSO, is under constant pressure to ensure that the tax money meets its purpose:

stimulating new innovation8. NEA therefore creates new legislation to reject less

innovative companies. With the added legislation, the NEA demarcates the WBSO’s boundaries, by excluding certain programming languages, collaborations, and activities. This lowers the number of companies that are eligible for the WBSO, which also limits UGOO’s (potential) market.

2. Saturation in the market stifles premium price

UGOO must deal with strong competition. The low entry barriers and attractive market (the WBSO alone generates a market of 312 million euro) attracts plentiful entrepreneurs. The market is therefore nearly saturated. In particular, UGOO belongs

5 https://www.ondernemersplein.nl/ondernemen/geldzaken/subsidies/info-en-advies/tips-voor-het-selecteren-van-een-subsidieadviseur/ 6 http://www.ondernemersplein.nl/ondernemen/geldzaken/subsidies/info-en-advies/tips-voor-het-selecteren-van-een-subsidieadviseur/ 7_{http://beleidsonderzoekonline.tijdschriften.budh.nl/tijdschrift/bso/2013/06/BELEIDSONDERZOEK-D-12-00027} 8_{https://www.elseviernextens.nl/wp-content/uploads/2016/02/cpb-boek-20-kansrijk-innovatiebeleid.pdf}

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to the higher segment in the market with a success fee of 15%. UGOO’s full-service approach and 95% success-rate explain this premium price. However, competitors are increasingly promising similar services to those provided by UGOO. As the distinctions between UGOO and other competitors become less apparent, UGOO is having a more difficult time justifying its premium price.

Meanwhile, the cost per succeeded application might rise:

1. More hours are needed for a succeeding grant application

Advisors at UGOO currently face a challenging situation. The demarcation of the WBSO means they have to go through extra lengths to secure grants for their customers; more letters of appeal must be written, more trials must be attended, and etc. Simultaneously, to compensate for the lost revenues from the WBSO, the advisors must familiarize themselves with other grant schemes, and have begun to write unexplored applications that require a higher degree of precision, and thus more time, than their regular work.

2. Less applications will succeed

To overcome the WBSO’s demarcation, UGOO has adopted the strategy of introducing new schemes into their services. While UGOO has experimented with this approach, it has not yet been successful. The most notable difference between the WBSO and other innovation grants is that companies that meet the WBSO’s conditions will always receive a grant. For other innovation grants schemes, the government calls for tenders, which rank the companies according to eligibility, and only those with top rankings receive the grant. Naturally, achieving a high ranking for one’s proposal requires different skills than ensuring that one’s company meets static conditions. UGOO does not yet have these skills.

C. Disrupt or be disrupted

Thus far, the picture painted gives the impression of a company with certain inefficiencies: UGOO must put forth more effort and funds to achieve the same - or even less – revenue. Rapid business growth seems unlikely in this phase. This raises the

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business model, eliminating the demand for legacy grant consultants like UGOO?

If these new entrants displace the existing industry they will disrupt the grant consulting sector. This disruption of a current industry is happening in a similar industry as grant consulting: the legal industry. Similar to the grant consulting, this industry is characterized with a lack of knowledge on the customer side resulting in high opacity in the industry. The legal industry, as Christensen, Wang, and van Bever’s (2013) describe, is now filled with upstart competitors that take away business from white-shoe firms. The writers describe how fast such entrants can change an industry. In three years the opinions of partners changed rapidly; in 2009 42% of the partners expected price competition, in 2012 this percentage climbed to 92%. This fits with the standard pattern of industry disruption: New competitors with new business models arrive; incumbents choose to ignore the new players or to flee to higher-margin activities; a disrupter whose product was once barely good enough achieves a level of quality acceptable to the broad middle of the market, undermining the position of longtime leaders and often causing the “flip” to a new basis of competition (Christensen, Wang, and van Bever’s (2013).

Technology can automate tasks, services and even complete jobs; called ‘automation’ in this thesis. If automation results in a transformation of the business model into a new, more efficient one, and if that new business model displaces the old business model, the automation was disruptive.

The fastest disruption occurs if a new entrant uses technology to establish a more

efficient business model. These disruptors can offer a dramatically better value

proposition through use of new technologies. Downes & Nunes (2013) describe the Big Bang disruptors-trend, in which products hit the market that are not only cheaper than established offerings, they are also more inventive.

As an example: advanced algorithms are ‘open-source’ and thus ready to use for every developer, where in the past a labour- and knowledge-intensive process was needed to develop these in-house. Now, state-of the-art technologies and products can be developed

quickly against low cost. The result is a more efficient business model mixed with

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D. Scope of the research

In this thesis I answer the following questions: Can the grant consulting industry, in particular UGOO, be disrupted through automation? And how can UGOO self-disrupt, to prevent disruption from new entrants?

Disruption in this thesis means that the demand for the traditional service with the ‘no cure, no pay’- business model will be replaced for a new service that reaches the same result (grant benefits), more efficiently (less effort, lower price, etc.).

This thesis recommends self-disruption as a strategy to prevent a disruption from an upstart competitor. Self-disruption for UGOO means that the innovation of their services (with new technologies) will replace the need for their legacy services completely. An example is the traditional consultant McKinsey who is disrupting its own consultancy services via offering technology-based analytics and tools: “McKinsey solutions” (Christensen, Wang and van Bever, 2013).

The structure of the thesis is as follows. Firstly, this study examines the probability of automation disrupting grant consultants’ work, as not all jobs as susceptible for computerization. (Frey & Osborne, 2013). The insights from this research answer the question of whether automation could disrupt the grant consulting industry, and thus whether UGOO should adopt technology if they want to self-disrupt.

Then, the study examines the possible completeness of this disruption. As stated in the article “Surviving Disruption” (Wessel & Christensen, 2012), not all disruptions are total. Perhaps UGOO’s customers would still need certain tasks completed for which a computerized solution would not be applicable. To map these jobs, the author created UGOO’s customer value proposition. This framework highlights UGOO’s services and – more importantly – the gains it creates and the pains it resolves as it executes jobs for customers.

Next, the paper employs the Five Paths Towards Employability framework to examine the best strategy for UGOO to harness the possible disruption. This framework provides strategies that companies can utilize to embrace automation. Taken together, the two frameworks could provide UGOO with substantive recommendations on how to join

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forces with computers to gain a competitive advantage, i.e. how to self-disrupt through automation.

Lastly, this thesis aims to motivate UGOO to self-disrupt according to the proposed strategy. The need for innovation is not felt in the industry, because players other than

grant consultants have not entered the market since the start of the industry thirty years

ago. Automation, which has disrupted so many other sectors, has not become a component of UGOO’s practices, or of the sector in general. The components of the service (meeting, interview, writing and submitting) remain human-executed work. Therefore at the end of the thesis, the benefits of technology are linked to the problems UGOO is currently facing because of the abovementioned industry trends. The assumption is that this approach would motivate managers more than a ‘Big Bang disruption’, for which they have seen no signs yet.

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IV. Literature

A. History of Automation

Automation is the technique of controlling a process by automatic means, as by information technology or devices, reducing human intervention to a minimum. Over the course of time more and more human task have been automated. The complexity of the tasks that can be automated increases, as the technology gets more sophisticated and intelligent.

The first era of automation occurred in the 19th century. In that century, machines in factories released people from certain tasks that had previously forced them to labor by hand. This disruption had a massive impact on the textile industry and the car industry. Factories rose in prominence, and workers’ tasks changed, as they either became handlers of machines or moved to offices for clerical work.

In the 20th century, machines automated even these tasks, especially with the arrival of personal computers. According Davenport and Kirby (2015), automation in the 20th century targeted routine services, transactions, and clerical chores. Or, Frey and Osborne (2013, p. 15) noted, “Computerisation has largely been confined to manual and cognitive routine tasks involving explicit rule-based activities.” These tasks are described as ‘routine tasks’.

In the 21st century, automation is focusing on intelligent machines, capable of independently making decisions, without human input. In fact, these new machines can make better decisions than humans, thanks to their capacity to analyze tremendous amounts of data, quickly detect patterns, and optimize calculations. Because of these capabilities, seemingly unpredictable and ‘non-routine tasks’ (e.g., driving a car) can be automated (Frey & Osborne, 2013).

B. Automation of the tasks in the Grant Advisor Sector

The activities of UGOO can be divided into routine tasks and non-routine tasks. Almost all of the tasks involved in submitting a grant (monitoring deadlines, providing business information, meeting administration requirements, etc.) are routine. These duties do not

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change, and they follow explicit rules. As submitting grant proposals is routine clerical work, current technologies could automate the process.

The non-routine component of grant consultants’ work is mainly related to writing grant proposals. Companies create a broad range of innovations, and establishing a link between these innovations and the grant’s requirements demands profound knowledge of those requirements. Moreover, the terms of the grant are subject to change. As noted above, civil servants create new legislation as they award grants. Therefore, UGOO’s advisors are continuously learning and adapting. Such non-routine tasks were not - until recently – sufficiently understood to allow for automation (Frey & Osborne, 2013).

However, technology is advancing rapidly. Tasks that were non-routine and not computerizable a decade ago have now become well-defined problems that can be programmed into machines. The rise of big data played a particularly significant role in this transition. To define the right problems in algorithms, it helps to have relevant data for analysis and testing. Big data means that massive amounts of data can be analyzed to detect patterns, find parameters, and validate relationships. Thus, the rise of big data has boosted developments in the machine learning area. Machine learning (including data mining, machine vision, computational statistics, and other sub-fields of artificial Intelligence [AI]) is explicitly dedicated to the development of algorithms that allow cognitive, non-routine tasks to be automated (Frey & Osborne, 2013).

The WBSO was founded in 1994. From 1994 to 2010, 120,900 companies have applied for it9. In 2015, NEA awarded 38,310 WBSO applications10. Since the success rate of the WBSO is not 100%, the number of total applications was in fact much higher (NEA does not release data on the number of applications). It is therefore reasonable to say that the static questions in the grant applications were answered hundreds of thousand times. This increasingly large and complex dataset is an example of big data. By analyzing patterns in millions line of text in both awarded and non-awarded applications, this data can be used to make a computer understand subtle dos and don’ts in writing grant applications. In other words, it can turn UGOO’s main asset, its human capital and expertise, into a software product. Christensen, Wang, and van Bever (2013) call this productizing. They claim that, as artificial intelligence and big data capabilities improve, the pace of productization in the consulting sector will increase. In “The Future of Employment,”

9_{http://tijdschriften.boombestuurskunde.nl/tijdschrift/bso/2013/06/Beleidsonderzoek-D-12-00027}

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Frey and Osborne (2013) give an example of productization, called Future Advisor. This is a service that uses AI to offer personalized financial advice at a larger scale and lower cost. This productization is one of the major disruptions Christensen, Wang and van Bever (2013 p. 12) predict for the consulting industry: “The steady invasion of hard analytics and technology (big data) is a certainty in consulting, as it has been in so many other industries.”

In conclusion, an information technology company could develop technology based on abovementioned principles to automate a large part of the current tasks in the grant consultants industry, thus productizing the job of a grant consultant. Once this technology has been developed, it could potentially serve unlimited clients without an (high) increase in costs. Therefore the business model is much more efficient. If the expertise of an artificial intelligent system delivers the same success rate as traditional grant consultants, it is likely companies will replace UGOO and similar companies for this cheaper system. Thus the market will be disrupted.

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V. Frameworks

The first framework, the ‘Customer Value Proposition’, is used to explore the jobs UGOO fulfills for its customers as well as how UGOO fulfills these jobs. Based on the knowledge from the literature these components are examined for their likelihood to be automated. That leads to the second framework: ‘Five Paths Towards Employability’. The second framework explores the strategic options UGOO has in self-disruption through automation. This framework is used to determine the most plausible solution of the strategic options.

A. Customer Value Proposition

When considering innovation and disruption, it is essential to realize that companies do not hire UGOO because they want a grant advisor. They do not even want a grant, for its own sake. Rather, business owners have certain jobs to fulfill, their “jobs to be done.” In other words, they must make progress in given circumstances, and they “hire” a product to help them (Christensen, et. al, 2016). If innovators are not clear on the customers’ “jobs to be done”, they risk solving the wrong problem via their products’ innovations.

In fact, UGOO could significantly improve its service in ways that would not help customers complete their jobs more successfully. For example, in the famous case of the quarter-inch drill that people purchase to drill quarter-inch holes, offering the drill new colors would not make the hole (the job) any deeper, nor would it speed or simplify the drilling process (Christensen, Cook & Hall, 2015). In UGOO’s case, new AI technology could improve the efficiency of UGOO’s business model. But perhaps that does not help customers to carry out their jobs more successfully. Therefore, before deciding on a self-disruption strategy that does not alienate customers, it is necessary to identify the required jobs to be done of UGOO’s customers.

For the determination of the jobs to be done in relation to UGOO’s services, this thesis uses the book of Osterwalder called: ‘Value Proposition Design’. Osterwalder builds on the work of Christensen on jobs. He proposed mapping customers’ functional, emotional, and social jobs in the “Customer Profile (of the Value Proposition),” and stressed the

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importance of taking into account the pains and gains that customers encounter in attempting to fulfill these job. After that, Osterwalder proposes to design the “Value Map (of the Value Proposition)”. The value map charts services and products, as well as, more importantly, the gain creators and the pain relievers of these products. If the pain relievers mitigate the stress that customers experiences as they complete a task, and if the gain creators lead to those achievements for which customers strive throughout the process, there is a fit. Then, the company’s product and the customer’s desires match, generating a demand from the customer (Osterwalder, 2014).

This study designs a Customer Profile and Value Map of UGOO’s current services, to gain insight in what value UGOO current adds to the customer’s jobs to be done. The goal of the exercise is to assess which jobs UGOO’s customers want the organization to complete for them, as well as which of these jobs a possible (self-) disruptor could perform more successfully. When UGOO self-disrupts, the jobs of customers must still be fulfilled by the new, replacing service. As discussed above, the disruption source under consideration here is automation

The Customer Value Proposition this study designed for UGOO is seen in Figure 1. The right part of the Customer Value Proposition describes the Customer Profile. This segment describes the customer in a business model.

Firstly, the jobs of the customers describe what customers are trying to get done in their work and in their lives. The customers of UGOO are entrepreneurs running innovative companies. Their jobs are: manage a healthy business, which means keeping costs low, selling products, remaining innovative, maintaining a competitive advantage and managing the company.

The gains describe the outcome UGOO’s customers want to achieve or the concrete benefits they are seeking. The biggest reason entrepreneurs involve themselves with the WBSO is the obvious benefit of ‘free money’ (on average, 25,000 euro per developer in 2016). With that extra money, entrepreneurs can achieve other benefits, for example hire an extra developer or better margins.

The pains describe bad outcomes, risks and other obstacles related to UGOO’s customer jobs. An obstacle companies dread the WBSO is the bureaucratic process, which takes time to understand. This results in a risk that an entrepreneur does not get other important things done. The worst pain involved in the application process, however, is emotional.

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The information asymmetry in the relationship between the government and the companies, caused by the entrepreneurs’ inexperience, is the major reason companies employ an advisor. The complexity of the law and legislation in combination with the amount of money involved, causes anxiety.

Value Map Customer Profile

Figure 1: Value Proposition, Osterwalder (2014).

Analysis of the jobs to be done can explain the decision making process that leads a company to hire an intermediary like UGOO instead of applying for the grant without help. The latter one is of course free of charge. Apparently, ‘getting a grant as cheap as possible’ is subservient to getting the most out of the grants and reducing the stress and anxiety involved. This is backed by research that shows that only 1% of the companies that hired a grant advisor do it because they think it is cheaper. (Bouwer, den Hartog, Poot & Segers, 2002). That is in line with Christensen’s theory about jobs to be done: customers care less about product characteristics (in this case: price), then about the job they have to fulfill.

The left part of the Customer Value Proposition describes the Value Map. The Value Map describes a list of all the Services and Products a value proposition is built around.

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The service UGOO offers is ‘full service’; UGOO takes over the complete grant application process, from detecting an opportunity to defending the application in court if necessary.

The gain creators describe how UGOO’s service creates customer gains. In fact, UGOO creates and optimizes the primary gain, the grant benefit, thanks to its great expertise and creativity.

The pain relievers describe how UGOO’s services alleviate customer pains. The full-service approach of UGOO lessens the sting of stress, anxiety, and lost time, as it takes over the complete process of writing and submitting a grant proposal, including fighting for proposals that NEA intends to reject. If UGOO fulfills the whole process, the lack of expertise of the customer is not an issue.

The customer value proposition UGOO pitches to their prospects fit to that job seamlessly: “With UGOO you’ll get maximum reward and spend minimal effort.” The firms’ full-service approach delivers on this promise. In most cases, UGOO’s tactics and expertise result in applications that maximizes grant benefits for companies, within the limits of what is allowed. Furthermore, UGOO manages the largest part of the application process. Based on the interviews with customers, in which they were asked about their main reason for working with UGOO, the fact that UGOO has expertise and can unburden them is mentioned most often. Therefore, it does appear that UGOO’s value proposition is based on favorable points of difference. UGOO pitches in a way that differs them from ‘doing it yourself’ and from the cheaper grant advisors in the industry. (Anderson, Narus & van Rossum, 2006).

The act of designing the customer value proposition made clear that there is a fit between what UGOO offers and what customers’ desire. This is not surprising, as UGOO has been running a profitable business for ten years. However, the goal of this exercise was to assess which jobs UGOO’s current customers want the organization to complete for them, to determine if automating tasks is possible without losing relevance in fulfilling the customers jobs to be done. Especially is UGOO aims to self-disrupt, i.e. replacing the present service for a new, more efficient service, it is vital the new service still helps customers with the jobs in their life.

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Framework application

The following question arises: For which of these activities that create gains or relieve pains could a machine substitute? To answer these questions, the study makes use of “the bottlenecks to computerization,” which Frey and Osborne (2013) currently view as the reason that not every task can be automated. These bottlenecks prevent the following tasks from computerization:

1. Perception and manipulation tasks: Since robots are still unable to match the depth and breadth of human perception, they are less suited for unstructured work environments or for handling irregular objects (Frey & Osborne, 2013).

2. Creative intelligence tasks: It is difficult to state (dynamic) humans’ creative values in a sufficiently clear manner to encode them in a program, and this is the primary reason that the first robot able to compete with humans in terms of creativity has yet to be developed (Frey & Osborne, 2013).

3. Social intelligence tasks: Computerization of such tasks is challenging, largely because engineers have so far failed to articulate and code all of the “common sense” information that humans possess. Without algorithms providing this information, robots cannot function in human social settings (Frey & Osborne, 2013).

Which of UGOO’s gain creators or pain relievers require perception, creative intelligence or social intelligence?

First, perception and manipulation (task 1) is irrelevant, because the UGOO consultants barely have to perceive objects. The main analysis consultants have to perform is of spoken word (interviews, conversations) and written word.

Second, creativity (task 2) is not a word that many people would immediately associate with the grant advisor sector. However, this is a misconception. Consultants at UGOO need to identify creative ways to enhance grant benefits. One of their current grant optimizing methods is to design “umbrella projects.” In these typical UGOO endeavors, consultants incorporate all innovative activities in one project. For some companies, this is straightforward. If all of the developers work on a single app, of all the activities related to this app become one project: developing app X. However, other companies have multiple products. If these products have different innovative components and face unrelated development challenges, it takes creativity to write one project that connects all

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of the activities and still makes sense.

Furthermore, creativity is needed to determine the way in which a company is eligible for a grant when it is not immediately apparent in its activities. For example, UGOO also serves companies that are not frontrunners in innovation. If their tasks were described very factually, their grant application would probably fail. The tactics required for success in such instances require an original approach. As described in an article by Frey and Osborne (2013), it is impossible to define and codify all of the ways that humans can be creative.

Finally, the consultants at UGOO all possess social intelligence (task 3); a prerequisite for success in that role. Sales require social intelligence; consultants must be able to identify the meaning behind words and play into that meaning to convince companies to choose UGOO. Furthermore, empathy is key in the grant application process. Consultants must persuade developers that their approach to writing proposals is superior to what developers would write. Empathy helps consultants with questions, such as: What is the real reason NEA wants to reject a project? When to fight and when to collaborate in negotiations with NEA? These questions require the ability to understand another person’s feelings. A computer does not have the social perceptiveness to comprehend human reactions, in the way that UGOO consultants do. Additionally, consultants create a human connection with their customers. In the author’s discussions with customers, most of them expressed positive emotions when talking about UGOO.

Taking the aforementioned into account, the gain-creating and pain-relieving tasks with which UGOO can assist, and for which computers cannot substitute, are:

- Creativity, being inventive.

o Designing “umbrella projects” for companies with divergent activities. o Finding the innovation in seemingly mediocre activities.

- Social intelligence, having empathy.

o Defending grant proposals to NEA and persuading them of the innovation.

o Being a counselor to customers, forming connections with the customer, and positive emotions about the collaboration.

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future are:

- Full-service approach

o Submitting and monitoring grant applications, and writing grant applications for obviously innovative companies that merely develop one product.

- Expertise

o Technical know-how.

o Proactively matching grant opportunities to activities.

In conclusion, not all of the tasks within UGOO’s service can be computerized.

Figure 2: Computerizable gain creators and pain relievers.

The sensible follow-up question should be: How do these tasks relate to the jobs that UGOO’s customers need to complete? As noted previously, the service is not the issue per se. Rather, the chief concern is the jobs that those services help to fulfill. In jobs that customers are legitimately trying to accomplish, do the aforementioned human-required tasks create a gain or relieve a pain or are they merely irrelevant product characteristics?

As already mentioned, the main job of UGOO’s customers is to “run a healthy business.”

The two computerizable tasks (‘full-service’ and ‘expertise’) seem to help all of UGOO’s customers accomplish their required jobs. To run a healthy, commercial business, the margin and competitive advantage is important. Thus, generally speaking, success in the WBSO grant application is of interest to all of UGOO’s customers. Also, all of the firm’s current customers are willing to relinquish a part of the grant, rather than applying for the grant on their own. The expertise in properly writing and submitting succeeding grant applications should therefore matter to all of UGOO’s customers. This is substantiated

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with the interviews executed with the customers.

The same reasoning accounts for UGOO’s full-service approach; the companies already made a deliberate choice to minimize the pains related to writing and submitting grant applications. A quote from business owner 5 during interviews on why he works with UGOO: “I choose to focus my energy on my business and hire a specialist for the stuff outside my core business.” The expertise and the skill of UGOO to translate a company’s story into a succeeding grant application is applauded in the interviews often.

Those tasks that require ‘creativity’ are not necessary for all customers. Two particular situations require UGOO to be creative: (1) when the customer is seemingly ineligible for the WBSO grant, and (2) when they need to combine divergent activities into a single, logical “umbrella project.” However, these conditions do not apply to all customers. Some companies are obviously innovative. For instance, if a company were to develop a new generation of wind turbines without blades, the application process would not demand creativity. Consultants could simply pen down the exact story of the business owner in the application, and the entrepreneur would receive the grant. For a company that created an Enterprise Resource Planning system for social service agencies, the innovation is less self-evident. That does not mean that the company is not renewing themselves, only that UGOO needs more resourcefulness to find and present the innovation to the government.

Likewise, some companies only work on a single product, and they do not need UGOO’s creativity to establish an “umbrella project.” Hence, the human skill of creativity only applies to companies whose eligibility is not clear-cut at first sight, as well as to companies that develop multiple products (but still prefer a single grant project). In other words, creativity aids companies whose activities do not fit the WBSO requirements like a glove. They need the creativity of an expert, in order to achieve their goal of running a healthy business by lowering costs.

‘Social intelligence’ has two main functions, from the customer’s perspective. Firstly, it fulfills the emotional component of the job. On the one hand, establishing a strong connection is a gain-creator. On the other hand, conveying trust reduces anxiety, and is thus a pain-reliever. Secondly, social intelligence is needed to convince; and persuasion is necessary when the government intends to reject an application. Again, not all companies

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need this emotional skill to complete their required job. For companies with cutting-edge innovative technologies, consultants’ social intelligence skills are less essential. If a company is unambiguously eligible, the need for persuasive skills is limited. The importance of human connection depends on the customer strongly. It does not seem related to the company’s level of innovation. In the interviews with ten companies, six preferred a relationship-oriented consultant. Amongst of which a very innovative, multiple award-winning Dutch startup.

However, we can say that even if cutting edge companies value the relationship skills of a consultant as much as ill-fitting companies do, social intelligence is more relevant to fulfill the ‘job to be done’ (i.e. run a healthy business) for companies that do not fit perfectly into the WBSO requirements.

In conclusion, it seems imprudent for UGOO to automate all their tasks, since there still are human-required tasks that are important to fulfill their customers main job to be done: run a healthy business. However, the extent to which the abovementioned tasks are vital to accomplishing this job strongly depends on the company.

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B. Five Paths Toward Employability

The customer value proposition provided insight into the aspects of UGOO’s service to which humans still add value. The discussion also linked the service to required customers’ jobs to be done and examined the skills that different customers need to fulfill these jobs. The conclusion: tasks related to UGOO’s full-service approach and expertise could be automated. This study also shows that fulfilling customers’ job to be done still required tasks only humans do well, namely tasks related to creativity and social intelligence.

Armed with this information, the next step is to consider which strategy UGOO should adopt. If UGOO decides to disrupt their current business model through automation of (certain) tasks, what tasks should new technology take over? To answer this question, this study uses the Five Paths Toward Employability, designed by Kirby and Davenport (2015). In “Beyond Automation,” the writers recommend five possible steps (discussed below) for humans to remain relevant in the AI age while working together with machines.

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Framework application

Step Up: being better at seeing the bigger picture than any computer

To start with the first strategy, ‘Step Up’, UGOO’s capacity to alternate between factual descriptions of activities and a more abstract, creative description seems to match with this strategy. As the writers stated, “There will always be jobs for people who are capable of more big-picture thinking and a higher level of abstraction than computers are.” (Kirby & Davenport, 2015).

If UGOO would adopt this strategy, it should utilize computers to do the cognitive work that is “beneath” the consultants (e.g., simply writing down a company’s pioneering innovative product or practice). The human consultants would use that opportunity to focus on higher-order concerns and to take on the more challenging cases. For example, human consultants could concentrate on creating an “umbrella project” for a customer that develops innovative metal products, from a sieve to a sausage rack. To be successful in this Step Up strategy, a key objective is to “stay broadly informed.” In this case, consultants must be well-versed on the grant industry, possible new grant schemes, and new legislation.

Step Aside: being better at skills that are not about purely rational, codifiable cognition

The ability of UGOO’s consultants to display empathy, form connections with customers, and convince humans, seems to fit the second strategy, Step Aside. Here, UGOO consultants would “focus more on the ‘interpersonal’ and ‘intrapersonal’ intelligences— knowing how to work well with other people and understanding your own interests, goals, and strengths” (Kirby & Davenport, 2015 p. 6). Under this strategy, consultants could devote their energy to winning new work and to counseling customers, while machines take over the grunt work. In this scenario, UGOO’s consultants would need to exploit their intelligences beyond their intelligent quotient (IQs). Emotional intelligence would be particularly important. Gardner (the discoverer of multiple intelligences) believes that sales persons and counselors have above-averages skills in the emotional intelligence regard (Gardner, 2002).

Step In: monitoring and modifying computers by understanding how it makes decisions

With 10 years of experience in grant advising, UGOO has a head start over computers. This could provide the backbone for the third strategy, Step In. Here, UGOO’s

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consultants would save their customers from computers’ incorrect decisions (e.g., decisions that are rationally correct but do not display ‘common sense’). Consultants would monitor and modify computers’ grant applications, searching for mistakes and correcting them. In this strategy, UGOO consultants would have to develop their powers of observation, translation, and human connection (Kirby & Davenport, 2015).

The last two steps do not seem to be relevant. Step Narrowly is about accumulated knowledge about a topic that is so niche, the business case to automate it is non-existent. Yet, the WBSO, a 312 million euro market, is a lucrative business opportunity with significant size. The last step, Step Forward, would require UGOO consultants to become deep knowledgeable regarding current techniques and to gain expertise in writing algorithms, developing machines, and writing codes. This retraining of the work force would be excessive, as well as prohibitively expensive.

In conclusion, three strategies remain to be considered: Step Up, Step Aside, and Step In. In the next chapter recommendation these options will be evaluated.

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VI. Recommendations

Three strategies remain: Step Up, Step Aside, and Step In. Two questions can help to clarify the most fitting strategy:

1. What strategy is most feasible?

2. What strategy is most appropriate for harnessing the company’s resources for the future?

Regarding the first question, Step Aside is the most feasible. Of the current work force of 20 consultants, only two consultants expressed interest in the details and content of the trade. The remaining consultants are more driven by sales targets and relationship management (interpersonal) or by the prospect of individual growth. Removing the scholarly work of researching innovations and regulations in order to write grant proposals would therefore benefit most of the employees, with only minimal retraining. In contrast, the other steps would necessitate retraining, either learning about more grants (Step Up) or learning how to work with, observe, and modify machines (Step In). The work force that thrives in personal situations would most likely not flourish if their primary task were to inspect computers’ production level. Step Aside would also mean that UGOO could retain its cutting edge customers as well as their ill-fitting customers. The new machines could serve those customers that seamlessly fit the WBSO requirements, leaving more time for consultants to serve the more difficult customers.

Regarding the second question, Step Aside is also the most appropriate for the future. As stated in “Future of Employment”, interpersonal and intrapersonal abilities are the skills least likely to be computerized in the near future. In contrast, computers could theoretically execute the tasks that the other two steps would require UGOO consultants to shoulder. Technological developments in AI, mainly activities in the (deep) machine learning field will ensure that future computers could learn independently without human input. The official term for this ability is unsupervised learning, and would render the Step In consultants obsolete. Furthermore, AI developers are increasingly employing

Graphic Processing Unit (rather than Central Processing Unit) processing capabilities.11

This implies that the computational workload could be divided among several processors simultaneously. By grouping data-processing tasks into smaller pieces, computers can

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distribute the workload across their processing units, thus drastically increasing their performance. As their data-processing capacities increases, computers can learn at an exceedingly faster pace than humans. The “broader” knowledge of humans will then be surpassed, and computers will know everything (deep knowledge like the humans in the Step In strategy) about anything (broad knowledge like the humans in the Step Up strategy).

Taking aforementioned into consideration, the Step Aside strategy is most advisable for UGOO. With this strategy, UGOO will not only choose the strategy that is most seamlessly implemented, but also the strategy that is most robust for future developments in automation.

A. Implementation

In this chapter, this study recommends a roadmap for implementing the Step Aside strategy in the organization. This study proposes a roadmap, in which the level of the technology that UGOO purchases, uses, or hires developers to create, becomes increasingly advanced. In Phase 1 of the roadmap, the technology will automate non-routine matters. More intelligence will be gradually added to this technology until UGOO’s machines are cognitively superior to UGOO’s consultants in most tasks (Phase 3). During the evaluation of the technology, UGOO’s cutting-edge customers could gradually shift from human service to service by machines. Humans will still serve those customers that require UGOO’s human skills to complete their jobs. This would preserve the consultants’ positions, because Step Aside capabilities are least likely to be computerized soon.

While designing the strategy, this study takes into account that the market in which UGOO operates has not ever been subject to disruption. As in other industries where opacity is high, new competitors of UGOO enter the market by emulating incumbents’ business models rather than by disrupting them (Christensen, Wang and van Bever, 2013). In result, UGOO consultants are currently still performing the majority of their work manually, as the firm has never needed to invest in technologies to automate these tasks. If there are no competitors with a more efficient business model because of

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technology, it is not urgent for UGOO to invest in technology their selves. Only since 2014 has UGOO begun to build its own Customer Relationship Management (CRM) system. Unfortunately, this system is still completely dependent on the input from consultants. Without feeding the system with deadlines, business information, and other data, it is useless. Moreover, it currently only puts extra pressure on consultants, rather than lightening their workloads.

Furthermore, the non-existent innovation in the industry implies that disruption in the market through automation is a futuristic concept seemingly unrelated to the everyday business of competing in a highly aggressive market. While describing the roadmap this study therefore relates the benefits of automation in each phase to the current challenges that arise from the business trends described in the Introduction. The next section explores how these machines can help UGOO with those concrete challenges in each phase.

Phase 1: Automate Routine Tasks.

In Phase 1, UGOO should make a significant investment in their CRM system or in a new system. The goal should be for computers to completely automate routine tasks (i.e., without depending on human input). As previously stated, consultants’ activities can be divided into routine and non-routine tasks. Routine tasks consist of sending reminders to customers, monitoring deadlines, retyping standard business information, and keeping track of all customers. These tasks follow well-defined procedures that can easily be performed by sophisticated algorithms (Frey & Osborne, 2013), and they are consistent and identical for each grant application. More specifically, these activities have the characteristics of tasks that have already been automated in the 20th century.

By translating the standard procedures into sophisticated algorithms, machines will be able to independently manage the procedures, and will not need constant confirmation from consultants. This would appreciably free the consultants from mundane and time-consuming tasks (i.e. decrease their workloads). The system could support the consultants by taking over tasks, but also by reminding them if human-required tasks are on the horizon. The realization that a smart system is backing them will reduce mental stress on the consultants.

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Consultants will have more time on their hands. This will help them to deal with the WBSO’s demarcation, as they can concentrate on learning from NEA feedback, gaining new knowledge, and sharing it with the team through meetings and workshops. This will help all the consultants to respond more quickly and adequately to new government legislation, (i.e. writing successful grant applications without having to answer multiple questions and letters of appeal). This will further decrease consultants’ workload. Lastly, automation could help UGOO realize its ambition to expand its services to other grants. With more time, UGOO could turn its grant applications into the high quality proposals needed to receive grants awarded through tenders. Overall, the increased available time - if spent on more research and immersion – will improve the quality of UGOO’s service, thus protecting the premium price.

Besides the effect on the quality of UGOO’s services, customers will not directly notice this innovation, and UGOO will still service both cutting-edge and more difficult customers in the same way. However, the unburdening of the consultants could result in a sales boost, as consultants are free to spend more time in sales, thus resulting in more customers of both types (cutting-edge as well as ill-fitting).

Phase 2: Automate Non-routine Tasks.

In the second phase, the funds gained from serving more customers should be invested in developing the intelligence of the technology. Big data analysis can detect patterns in grant applications. Based on this analysis, all of the factors can be identified that an experienced consultant takes into account when making decisions. In this way, an apparently non-routine task can be brought back to standard rules. These guidelines can be translated into algorithms within a framework of a “successful grant application.”

This system will be able to recognize whether a grant application could succeed, by comparing it with patterns defined in the framework. This expertise would be on par with that of a starting grant consultant, who learns the dos and don’ts in the beginning of his or her career. The system could detect if a grant application fit the governments’ requirements, if all boxes are ticked, and if the right activities are emphasized.

In practice, this means that grant applications could be uploaded in this system, scanned, and provided with feedback. Examples of such feedback include, “this word is mostly

seen in rejected applications,” and “questions were asked about texts with a similar build up.”

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After extensive testing, UGOO could offer the program to a selection of its customers. Instead of having an interview with UGOO about its proposal’s development, the company will write down the necessary information and submit it to the program. After processing the feedback, the application would be submitted automatically. Here, UGOO must be delicate in selecting customers. The program will not be creative and will therefore not be suited for customers that are not a clear fit with the WBSO. Furthermore, for cutting-edge customers, the business owners’ personalities must also be taken into account to determine if they would miss the human contact.

In this phase, consultants’ workloads will be further reduced. When the number of customers using the system rises, consultants can Step Aside. They can allow the computer to do the cognitive heavy lifting and focus on those aspects at which humans still excel (e.g. using their creativity for more challenging customers). Moreover, UGOO will also be able to acquire new customers, as the program will be exceedingly more scalable than a human consultant.

Phase 3: AI Machines.

As the number of customers utilizing this program increase, so will its intelligence, due to machine learning algorithms. Machine learning algorithms can teach the program to learn from data and to make predictions. In other words, the system will be able to improve itself without being explicitly programmed to do so. After being fed with so many grant proposals, the machine will gain an incredible understanding of the grants. One day, this knowledge will exceed that of the consultants. Then, decisions will be made automatically, without human reflection. UGOO’s consultants must focus even more powerfully on their emotional and creative skills.

The question is whether this is a tenable situation. A possible scenario is that government eventually realizes that application that were submitted by a human grant consultant consist of more creative liberties. As government has a preference to an exact representation of a company’s activities, they might differentiate between companies that submit machine-written proposals versus human-written proposals. The government might be prone to rejecting these latter proposals, because of their unwanted creative presentation. Thus, all companies would have to use machines or else not submit an application at all. In that case, the industry would have been truly disrupted. But at least, UGOO – and not a new competitor – would be the one responsible.

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Figure 5: The three phases

VII. Limitations

The conclusion of this study is that the threat of disruption through automation is serious. Firstly, the technology is already in state that a large part of UGOO’s tasks could be automated to create a more efficient business model. New developments in the artificial intelligence and machine learning field imply that activities of UGOO are computerizable. Furthermore, this study shows that it is an interesting business case as the size of the market is large.

This study therefore recommends self-disruption according to the Step Aside strategy, in which both computers and humans do what they do best. The computers take on the ‘cognitive heavy lifting’, and the human focuses on the activities that are deemed unlikely to be automated soon (Kirby & Davenport, 2015, Frey & Osborne, 2013). In UGOO case, this would mean the consultants would use their creativity and social skills to defend the case of the ‘ill-fitting’ WBSO-beneficiary. UGOO would also employ computers who can (artificially) write the more clear-cut grant proposals.

This conclusion is based on fieldwork (the researcher was a grant consultant at UGOO for two years), literature research and interviews with clientele of UGOO, mainly business owners. This research gives ground for the reached conclusion, however the

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methods were not perfect. Consequently, the results have some limitations. In further research on the topic of automation in the grant advisor industry, the researcher should try to resolve these limitations and thus prove or debunk my conclusion.

The first limitation is that the interviews with the business owners were held before the topic of the research was definitive. Therefore, the business owners were not asked the obvious question: ‘Would you accept grant advice from a computer, and if so, under which conditions?’. The interviews were included in the research nevertheless, because they give insight in the jobs the business owners hired UGOO to do for them. The theory says that if a product or services fulfills the job to be done, the characteristics of a product or service is a side issue. Further research should show if this is also the case if the characteristics change so fundamentally as they would in this case (human versus robotic advisor).

This research does not consist of concrete technological knowledge on how the proposed system of UGOO would work, other then the general technical terms with which the developments could be labeled. Here lies a task for a Big Data student or Computer Science student, who could really dive into the algorithmic choices that have to be made in the development of a ‘grant advisor system’. This student could also make a substantiated cost estimation related to the development of this system.

This brings forth the last limitation: this research does not consist of a recommendation about the business model UGOO should have after their business changed so drastically. For this, the next researcher could design a Business Model Canvas, also based on Osterwalder’s book. The Customer Value Proposition is only a part of this extensive Business Model Canvas. In the rest of the Canvas, the revenue streams, cost structures, partners, resources, activities, relationships and channels are mapped. This will give a more complete picture of the possibilities and downfalls of the proposed self-disruption.

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VIII. Resources

Anderson, J.C., Narus, J.A. & van Rossum, W. (2006). “Customer Value Propositions in Business Markets”. Harvard Business Review, March 2006.

Bouwer, E., den Hartog, P., Poot, T. & Segers, J. (2002). “WBSO nader beschouwd: onderzoek naar de effectiviteit van de WBSO”. Dialogic, June 2002.

Christensen, C.M., Hall, T., Dillon, K. & Duncan, D.S. (2016), “Know Your Customers’ “Jobs to Be Done””, Harvard Business Review, September 2016.

Christensen, C.M., Wang, D. & van Bever, D. (2013), “Consulting on the Cusp of Disruption”. Harvard Business Review, October 2013.

Davenport, T.G. & Kirby, J. (2015), “Beyond Automation”. Harvard Business Review, June 2015.

Downes, L. & Nunes, P. (2013), “Strategy in the Age of Devastating Innovation: Big Bang Disruption”. Accenture Institute for High Performance.

Frey, C.B. & Osborne, M.A. (2013), “The Future of Employment: How Susceptible are Jobs to Computerisation?”. Oxford Martin Programme on Technology and Employment, September 17th 2013.

Gardner, H. (2002). "Interpersonal Communication amongst Multiple Subjects: A Study in Redundancy". Experimental Psychology.

Porter, M. E. (1991). “Towards a Dynamic Theory of Strategy”. Strategic Management Journal, 12( Special Issue, Winter), 95-117.

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Poot, T, den Hartog, P., Grosfeld, T & Brouwer, E. (2003). “Evaluation of a major Dutch Tax Credit Scheme (WBSO) aimed at promoting R&D”. TU Delft.

Wessel, M. & Christensen, C.M. (2012), “Surviving Disruption”. Harvard Business Review, December 2012.

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IX. Appendix

1. Grant ceilings published by the Ministry of Economics in the Netherlands.12

Instrument Open Ceiling

Innovatieprestatiecontracten 01-02-2016 - 26-02-2016 € 2.785.000 Eurostarsprojecten 01-01-2016 - 12-01-2016 € 9.162.500 Internationaal innoveren 14-03-2016 - 08-04-2016 € 10.000.000 Innovatiekredieten 01-01-2016 - 31-12-2016 € 20.000.000 Innovatiekredieten 01-01-2016 - 31-12-2016 € 40.000.000 Seed capital technostarters 01-01-2016 - 31-03-2016 € 24.000.000 Borgstelling MKB-kredieten 01-01-2016 - 31-12-2016 € 505.000.000 Borgstelling MKB-kredieten 01-01-2016 - 31-12-2016 € 25.000.000 Groeifaciliteit 01-01-2016 - 31-12-2016 € 50.000.000 Garantie ondernemingsfinanciering 01-01-2016 - 31-12-2016 € 200.000.000 Garantieregeling scheepsnieuwbouwfinanciering 01-01-2016 - 31-12-2016 € 400.000.000 Vroege fasefinanciering 01-01-2016 - 31-12-2016 € 7.000.000 Vroege fasefinanciering 11-01-2016 - 29-02-2016 € 2.500.000 Topsector energie-projecten 01-04-2015 - 31-03-2016 € 50.000.000

Wet Bevordering Speur en

Ontwikkelingswerk (WBSO)

01-01-2016 - 31-12-2016 € 1.510.000.000

Totaal € 2.855.447.500

2. Interviews with customers of UGOO

Business owner 1

1. Why do you work with UGOO?

We needed the WBSO grant and Robbert 13approached me. The collaboration with Robbert goes smoothly. He is very good in translating our explanation into the language the government understands.

2. If, starting from tomorrow, you are the managing director of UGOO, what is the first thing you will change?

I couldn’t think of a thing.

3. What is your image of UGOO?

12_{https://zoek.officielebekendmakingen.nl/stcrt-2015-44610.html} 13_{Robbert is a former consultant at UGOO.}

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No fuss. Fast and efficient workers. UGOO’s competitors approach me daily, but I am happy with the service of UGOO. And we have a good personal relationship.

4. How would you describe your business relationship with UGOO?

Personal.

5. I want complete transparency in the process or I am only interested in the end result.

I want complete transparency in the process.

6. I like to take risks or I avoid risks.

I like to take risks.

7. My ideal UGOO consultant does more for me than just grant consulting or I only need UGOO to help me get grants.

My ideal UGOO consultant does more for me than just grant consulting

8. My ideal consultant: relationship oriented or task oriented?

Relationship oriented

I already work with UGOO for a long time, even when they were still DFM Consult.14 They have the knowledge I need in a grant consultant, especially since the landscape is changing all the time. I am still content. I get personal attention from Roland. They are flexible with their billing. I also appreciate that.

Even though I appreciate my good relationship with Roland15, I would like to know the other people behind the organization. Who else is involved with my grant application?

14_{DFM Consult is UGOO’s previous name.} 15_{Roland is one of the two founders of UGOO.}

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A stable and growing organization. They care about the personal relationship. Its an open organization, you are allowed to say something, give feedback. Roland is very dynamic.

Good relationship.

I am only interested in the end result.

6. I like to take risks or I avoid risks

I avoid risks

I only need UGOO to help me get grants.

8. My ideal consultant: relationship oriented or task oriented?

Relationship oriented

It grew historically. We understand each other. That is important.

That’s difficult. I believe in ‘schoenmaker blijf bij je leest’16, so wouldn’t want anything else from UGOO then what they are doing now.

Young organization with young people working there, but never the less well educated. They listen well. And they understand the skill of translating my technical story to an application.

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Like I said, we understand each other.

I want complete transparency in the process

I avoid risks

I only need UGOO to help me get grants

8. My ideal UGOO consultant: relationship oriented or task-oriented?

I work with UGOO for a long time and never had a reason to switch. Robbert was a nice guy to work with, I trusted him. He was capable of making our unstructured story into an application for the government. Robbert is precise. He understands the importance of this grant for us. It’s about money, so it has our priority and UGOO’s expertise helps us to takes care of it.

Now we are the once that have to say: ‘isn’t this a grant that could be interesting for us?’. I want more proactive from UGOO in this. Another thing is: since I became a customer of UGOO eight years ago, nothing in the service has changed. That’s positive and negative: I understand you don’t want to change a winning team, but keep in mind that the environment is active. I would recommend a close watch on what’s happening in the industry

Also I would appreciate a service that takes over the obliged administration.

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I only know Robbert. UGOO is the person you are talking too. I dont know what the organization behind it looks like. But Robbert and Zinzi 17are driven to take of things accurately.

It’s a good relationship that was build over the years.

I want complete transparency in the process

I avoid risks

My ideal UGOO consultant does more for me than just grant consulting

8. My ideal UGOO consultant: relationship oriented or task oriented?

1. Why do you work with UGOO?

I choose to focus my energy on my business and hire specialist for the stuff outside my core business.

I am content with their WBSO-service, but I am interested in other grants. Keep me more up to date about other grants. Also, I don’t like that I have to pay the fee over the amount that is granted while that might not be the amount I will effectuate in the end.

3. What is your image of UGOO?

Really a specialist in the WBSO-area. Writes applications that RVO always awards. They are very successful in that.

How to harness automation in the grant advisor sector : a recommendation for UGOO