The Start-Up Data Dilemma

Clifford McDowell
Doorda
Published in
9 min readMay 23, 2018
Photo by Jon Tyson on Unsplash

The Challenge of Getting and Using the Data You Need

Some of the most exciting, innovative and disruptive ideas currently taking the world of business by storm did not come from the boardrooms and discussion sessions of the establishment. These plans were not laid down by the highly-paid, highly-lauded talent found in the upper reaches of the Fortune 500 list. Instead, they came from start-ups.

2016 saw the launch of the TeraRanger Tower, a silent collision detector for drone devices which was considered a significant leap forward in the UAV field. This was the work of a start-up. Elsewhere, some of the most pioneering movements into Internet of Things, or IoT- enabled devices, something which analysts predict will drive the next wave of tech innovation, are being made not by established organisations but by start-ups.

This is precisely what we need; a host of up-and-coming firms ready to throw their innovative hats into the ring and create something really special. But these are just a few examples, what about all the rest?

Unfortunately, many start-up innovations are being stifled before they even get off the ground. The current landscape is not a particularly friendly one to smaller scale organisations, many of which find themselves unable to pursue their innovations through to completion. Often, this is because of data.

Data — the very thing which was supposed to have kickstarted a revolution in business — is holding many modern start-ups back, simply because access to this precious commodity remains restricted.

Legal Constraints on Direct Data

The UK government takes a strong legal stance on the use of data commercially. The legal provisions, laid out in the Freedom of Information Act of 2000 and the Data Protection Act of 1998, restrict what a commercial organisation or other entity can do with the information they gather from customers.

Gathered data must be used for a purpose deemed lawful and fair, and this purpose must be nominated and clearly defined. Any collected data must be accurate, and must not be considered
“excessive” — i.e. data should not be collected if it is irrelevant to the nominated purpose.

Any organisation which collects data is also required to take all measures necessary to protect the data in their charge. This is the legal responsibility of the organisation in question.

Additionally, the organisation holding the data may not transfer this data to any other country unless they have the necessary standard of data protection legislation and structuring already in place.

Individuals also have a right to access and control any information held on them. If an individual submits a data request, you are legally obliged to comply.

Staying on the right side of the law is vital for start-ups. You might have the data you need, but collect it in an irresponsible manner, or behave carelessly with the data, and you will quickly find yourself in trouble and your project derailed. Any business owners concerned about the data issues affecting them can contact the Information Commission Office and request guidance.

General Data Protection Regulations

As of April 2017, start-ups in the UK are also governed by the data protection legislation of the European Union. This means that, depending on the terms and conditions of the United Kingdom’s exit from the EU, UK firms will be required to adhere to the forthcoming General Data Protection Regulations — or GDPR. This set of rights, rules and responsibilities was drawn up in 2016 with the aim of unifying and simplifying data protection across Europe. It is due to be implemented in April of 2018.

So, what will this mean for businesses who must comply?

The idea of the regulations is to update existing protocols to reflect changes in technology. As technological advancements and shifts have altered the playing fields of security, the GDPR provides minimum standards for security and data privacy, including encryption procedures, best practices for data management, and the adoption of clearly designated roles for data security teams.

Whether the UK will be or will not be governed by the EU’s regulations in the future remains to be seen. However, it is certain that start-ups in this country will continue to be bound by data protection red tape and legislation to some degree.

These rules are necessary, as they give the public important protections against malicious use of data. However, they do present certain obstacles to conscientious business owners and start-ups who simply want to apply data understanding and insight to their testing measures and to their business initiatives in general.

Commercially Sensitive Data

Legal constraints are not the only impediments to start-ups in search of data. Much of the most pertinent information — the information which would be of the most value to testing and analysing new products and services — may be classed as commercially sensitive. This sort of information will not be made freely available by other organisations.

This may include;

Demographic information. Which sections of society are being targeted by other companies, for example, or the demographic make-up of key customer bases in a certain market or industry.

Cost information. This may relate to case studies of product launches and other initiatives by businesses in the market, particularly in terms of expenditure and eventual return.

Profit information. How much profit have other companies gained from similar product or service launches? How have they been able to reduce costs and augment profits in the process?

Supplying and sourcing data. Information relating to components, ingredients, suppliers, sourcing locations or protocols.

Partnership information. Information relating to partners or joint ventures, specifically with regard to cost sharing and other numerically specific data.

The data points listed above represent a few examples of potentially commercially sensitive information, but, in effect, the list is far more extensive than this. Basically, any information which may harm an organisation’s profits or business plan will be classed as commercially sensitive and is unlikely to be available to you.

If a start-up does gain access to this information, publishing it can land them in serious legal trouble. Always adopt a careful and considered approach to the use and publication of such data, and remember that any information published must be accurate, particularly if it relates to another organisation.

Competitive Logic

The potential risk of commercially sensitive information is augmented even further when the source of such data is a direct competitor in the market. An organisation is likely to be even more guarded if they feel that you represent a direct rival and that the data they deliver to you may be used against them in some way in their industry.

For example, companies are understandably anxious that a competitor might try to gain traction in their industry by publishing or leveraging certain pieces of commercial information. If this is the case, they are very unlikely to release that information to you.

Even if you are able to sign a non-disclosure agreement, prohibiting publication and ensuring that any data is only used internally, other businesses may still be reluctant to share the most useful datasets with you. This is simply down to competitive logic; why would a competitor wish to aid an up-and-coming rival by delivering hard earned, or expensively purchased, data to them? This data could be used to hone and develop a product or service which directly competes with those of the information donor, and so directly reduces their market share.

This is another example of the obstacles that keep start-ups from the data they need. In this instance, the obstacle is not a legal one, but still represents a dead end in the ongoing search for data.

Machine Learning and other Innovations, Off Limits

We’ve examined the legal and commercial barriers to data collection and usage, so what are the results of this?

In effect, such prohibition makes it incredibly difficult for start-ups to pursue their most innovative, most disruptive ideas, simply because they do not have the data available to them; data which can be used in testing and refining their next steps.

These innovations touch every aspect of a business. Everything, from the products and services a company offers to its customers, to the structure of the business itself, requires ongoing development and enhancement, which can only come through understanding and insight.

To gain this understanding and insight, a company needs to be able to run tests and examine all possible outcomes. This cannot be achieved without data to compare and contrast the results of the tests against. Effectively, avenues to innovation are off-limits to start-ups.

For innovations which directly require data sources, the situation is even more difficult. Machine learning is proving to be one of the driving forces of the business of tomorrow, and companies are falling over themselves to implement this cutting-edge technology into their systems. The applications of machine learning and AI are incredibly wide-ranging — covering fields as disparate as customer interaction, malware prevention, and many areas in between — but this is simply impossible without data.

Unless access to data can be democratised, the business world runs the risk of a schism; a situation in the already established organisations pushes the boundaries of innovation, and the idea-rich/resource-poor members of start-ups are left floundering in the dust.

“A robot named Pepper holding an iPad” by Alex Knight on Unsplash

Expensive DaaS Options

One potential avenue open to start-ups — an avenue which eliminates any concern over legal, professional and ethical wrong-doing — is the DaaS, or Data as a Service, option. This involves an organisation outsourcing some or all of their data strategy to a third party company, including the collection and management of data, the interpretation of data, or the application of the insight derived from data.

On the face of it, this is an attractive option. For starters, it brings an expert view into the equation, helping the business to gain additional leverage that they may not have been able to benefit from themselves. Furthermore, this approach reduces the time and effort that start-ups need to expend on data, giving teams more scope, license and capability to grow the business. As start-ups are often only populated by smaller teams with relatively few members, this is a major advantage.

DaaS certainly represents a set of genuine benefits to businesses, and to start-ups in particular, although it is not without its problems. Some analysts have cited issues with data security and privacy as potential disadvantages, outlining how start-ups need to make sure that their security systems are robust enough to deal with a potential third-party breach. It is also important for start-up owners to shop around as they seek to acquire the most suitable level of support for their business, at the right cost.

Just like in any market, solutions vary in cost, complexity and value. Big names in the industry — such as Experian and Lexus Nexus — provide comprehensive data services which cover a wide range of bases. However, these solutions can be expensive, and if the advantage a start-up receives from data is cancelled out by the prohibitive cost of pursuing it, they will quickly find themselves back at square one.

A Crowded Marketplace

If a start-up owner weighs up the options and decides that his or her business can afford the cost of the DaaS route, the advantages are real. However, take-up levels of Data as a Service products are increasing, which means that more and more businesses are finding themselves wading into testing and strategic planning endeavours armed with the same data as their competitors.

This leads to a crowded marketplace. Businesses are gaining advantages, but these advantages are the same as those enjoyed by the competition. To put it simply, they cancel each other out.

For a start-up, a successful data strategy is something of a balancing act. The business must remain legally and ethically sound, without giving up any ground to the competition; they must also leverage all the advantages they can over this competition, without breaking the bank in the process.

Getting this balance right requires as much innovation and enterprise as launching a winning product into the market.

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