Daily, the world creates an estimated 2.5 quintillion bytes of data, with 90% of it in last two years. When this figure is combined with internet statistics, one can begin to see how much of someone’s life leaves a digital imprint. This data can be used to paint pictures of people, their behaviour and their interactions. The vast quantity of this information is called Big Data and businesses are beginning to use it to their advantage.
What Is Big Data?
The continued and extensive use and development of the internet and interconnected technologies is creating “unfathomably large datasets.” Big Data is a term granted to data that is so expansive or complex, traditional systems of analysis are ineffective or inadequate in unlocking useful information from the data.
However, the challenge of big data is also what makes it so rewarding for business, for if a company can crack big data, they can uncover trends, spot correlations and increase the effectiveness of their decision making by having access to a large amount of information. The rise of Big Data has been brought on by the increased online storage space and an enhanced computing power, capable of dealing with larger quantities of data.
Big Data And Analysis: Purpose
What is the purpose of collecting large quantities of accurate information about consumers, clients and others? Predictions. Simply put, it is about “applying math to huge quantities of data in order to infer probabilities.”
One can see such a purpose in the examples above. For supermarkets, for example, being able to understand previous seasonal trends enables them to stock up on the most sought-after items during seasonal shopping times. The sophistication of Big Data has led some commentators to conclude that, while high-performing systems will not work to the same degree as human professionals, Big Data techniques will often draw conclusions, offer advice and provide guidance at the standard of human experts or higher.
Effects On Business
Big Data can be seen to have three main effects on business, those being that data is being seen as a resource, enhanced knowledge of consumers and companies becoming faster and more reactive to market changes.
First, with data being increasingly seen as a resource rather than a by-product of conducting business, companies are trying to extract more data from their customers. Consumers leave a trail of data “imprints” whenever they use information technology (internet, mobile, social media, etc.), and this imprint will only grow with the internet of things becoming a more realistic prospect.
Simply put, every second, the flow of data presents opportunities for businesses to change their strategy in real time. Even this article is leaving an imprint – how many views it has received, from which browsers, from which locations, how many times the Twitter link has been clicked. From this data, one can paint a picture of what one’s audience looks like and thus one can shape posts to meet new demands, and this is precisely what companies are using Big Data for.
Data As A Resource
Companies such as Facebook and Google have been collecting data for a long time and are now using such data to make guesses, for example, as to what products a consumer is likely to buy, what online content they are likely to browse next and even what activities one will conduct. A large amount of data is collected and used to create targeted advertising. By monitoring users, Google can collect data about their online habits and then feed that information into an algorithm that outputs relevant advertisements on its platform. The model is simple, effective and useful for business.
What’s more, while Big Data has become more complex, businesses have become more sophisticated in using Big Data. More sources of data have been uncovered, and analysis enables firms to cross-reference these sources to produce a realistic profile of any one user. Whereas before, firms would analyse samples of their data and provide a snapshot of the business, new tools such as PwC’s HALO are attempting to analyse 100% of the client’s data to provide a clearer and more precise view of the data.
Such an effect was discussed by Viktor Mayer-Schönberger and Kenneth Cukier in their book Big Data, where they predicted Big Data would cause a move from “some to all.” From here, Susskind and Susskind argue that the only improvement to be made from 100% analysis is “continuous audit” that is, the real-time data analysis for providing a picture of the financial vital signs of a company.
Enhanced Consumer Knowledge
Second, such continuous audit systems exist within the market, albeit for smaller volumes of data. Services and products that offer analytics of a customer’s data which are easy to understand and are digestible can enable the customer to become interested in their “imprints.” Products like FitBit and apps on Apple’s items which enable users to track their movement, exercise and routines can influence the consumer and get them addicted to wanting to better themselves.
Tying into this, such applications can recommend healthy foods, supplementary vitamins and other connected services to boost the consumer’s interaction with the data and the company’s revenues. As soon as a consumer becomes aware of their data and becomes determined to “improve” their results, they will be more likely to remain loyal to the brand. Companies can use Big Data in this way to attract and keep customers, prolonging their operations and increasing profit.
Moreover, Big Data extends beyond simply capturing typical information about customers and then using that analysis to inform decisions. Rather, it extends to creating heightened strategy. For example, Big Data can allow companies to identify the average spend of a customer, their happiness rating, satisfaction and even identify whether one’s target customers are the ones purchasing the products. By understanding Big Data in this way, Companies can manoeuvre into new audiences and expand they product line.
Faster And Nimbler
Ultimately, using Big Data can create reductions in cost, develop faster and better decision-making procedures and lead to the inventions of new products or services. On the cost front, online data requires lower physical storage since the data is often in the cloud. Further, with integrated cloud analytics to organise data, businesses can utilise simplistic search functions and find relevant information quickly, rather than trawling through paper files. This is particularly poignant for law firms. Moreover, Big Data can cut service costs and pass these savings onto clients or the consumer by using networks of computers to provide a single human manager with accurate data to make a decision as compared to a team of employees, collating the data and then reporting it. This feeds into the second factor, better decisions making.
Big Data analytics allows large amounts of data to be analysed quickly, enabling businesses to understand current trends as and when they happen. For example, an online shopping platform can measure the amount of new daily visits and see what products had attracted such attention. Using that data, the platform can then rearrange its layout dynamically, putting hotter items lower down the list of purchasable, making the consumer scroll through related products to get to the one they want.
are created in the world daily
Moreover, with enough data, the platform can recommend new products to customers based on their history of purchases. Further, with historic stores of data from two or three years previous, the platform can predict trends and understand when certain seasonal items are about to become part of a purchasing craze. By understanding the timing, the platform can ensure that such promotions are there earlier to grab customers that would otherwise visit competitors. The possibilities are endless, and all are attainable through understanding how big data is used.
Last, Big Data can act as a catalyst for new products and services, since it allows companies to analyse how customers use their products and analyse what customers want or what is missing. The text mining of thousands of feedback forms can present a clear indication of what customers want from a product. For example, Facebook has taken to allowing users to turn off adverts they do not want to see and then asks them for feedback and the reason why. If the user has already bought the product and that is the reason Facebook receives, then the next ad will be for a different product. By understanding how the consumers act, companies can create new products and thus, in turn, create a competitive advantage.
Effect On Law Firms
Having assessed and analysed, with examples, how Big Data is affecting business and how it will impact companies in the future, this article will now turn specifically to Law Firms. Since Law Firms provide a service to their clients, anything that can speed up the delivery of that service, while maintaining a high level of excellence for a lower cost, will provide the firm with an advantage.
Big Data can be seen as one opportunity for firms to accomplish this, but will it achieve, or help to achieve, change in a profession whose working practices remain largely unaltered since “the time of Charles Dickens”?
First, Big Data can enable law firms to analyse thousands of judgements and create data sets by analysing the outcomes of similar cases to help provide predictions for clients on the outcomes of litigation. With a system that can analyse thousands of cases with similar points of law or facts, lawyers can create resource caches to dip into when needed to bolster a client’s case.
Consequently, this circumvents the need for lengthy research and trapesing through books. Currently, lawyers can use online searches through databases such as LexisNexis and Westlaw to obtain a great starting point from which to expand their field of research. With Big Data, having the ability to search for all cases where Parliamentary Sovereignty has been discussed can provide up to date case lists, often more up to date than the latest book.
However, going one step further, certain systems can be used to analyse judgements with similar facts and create predictions such as the Lex Machina Service (for patent disputes). With this development in mind, such systems can achieve a higher work accuracy, for a lower cost and the system is more consistent than human workers who tire as the working week progresses. Big Data analytics in this light is particularly crucial for the legal industry.
AI And The Legal Industry
A further impact of Big Data is its facilitation of the implementation of Artificial Intelligence (AI) systems into the legal industry. Since Big Data analytics are currently used by lawyers, who input simple commands and use search functions, going one step further and using an AI to conduct the tasks in response to a client’s input can be argued to be the next step. In general, systems which can use Big Data autonomously are game changers for every profession, not merely the legal industry, but that topic deserves its own article.
Second, Big Data can create records of data and, in turn, create industry benchmarking. By using Big Data to analyse the data of clients and the work performances of employees across a global network, for example, this has the indirect effect of creating a more transparent system by effectively implementing industry standards in billing, the time taken to work on a particular issue and amount of cases conducted. The effect of this is to create further competition between firms and in turn develop better business practices by challenging firms to be more efficient while maintaining exceptional production values.
Big Data Helping HR
On this point, Big Data can also help with the management of human resources. With access to a large collection of accurate information about the company, Directors and Managing Partners, with the Board, can manage, to a greater degree of accuracy, existing employees and create benchmarks for performance, enabling a higher standard of goals to be set by highlighting weak points across the company.
Big Data can help accomplish this by providing managers with an overview of employees, from work conducted to time spent providing advice. Ultimately, this increases the visibility of the managers. Data collected to enable Directors to create these goals can include typical casework times, the amount of time spent on call to clients, expenditures on different types of client and the amount of meetings conducted with clients.
From a client-facing point of view, it can include types and amounts of cases, typical case length, client satisfaction, typical client legal costs and client feedback. From this, firms can understand more about client behaviour and, as a result, move to match these behaviours with their legal practice, achieving, or hoping to achieve, better client satisfaction and retention rates. This can be extended to the hiring of new employees because application processes can achieve a higher accuracy at the first stage filtering, such as relevant A level results as well as ensuring training is organised to prepare the future lawyer with particular skills. For example, if clients noted a distinct deficiency in word processing skills, Big Data could allow firms to implement IT workshops since firms are made aware of the lack of competencies by analysing client feedback in large volumes.
Furthermore, with industry benchmarks increasing transparency within the legal sector, clients can use this information to cut their own legal expenditure and choose firms that are better suited to their needs. With such information about billing and costs being widely available, it can provide clients with a stronger negotiating position since they are aware of what a typical case concerning their issue can cost. In this respect, Big Data usage can help mitigate the contemporary challenge of high client costs.
Additionally, as aforementioned, law firms process cases, conduct research, file motions and advise clients with even more intricate services along the way and all that work creates paper files. As a result, Big Data and cloud services can reduce the amount of physical Storage space that is needed. Moreover, client costs are further reduced by the augmentation of work processes. While lawyers are compartmentalising legal work and enabling low-level work to be conducted by lower billing staff, Big Data systems can reduce research times and optimise work processes by delivering hyper-targeted information to lawyers working on cases. In an increasingly saturated global legal industry, any advantage one can gain will assist in obtaining the bigger clients.
The Challenges Of The New Legal World
The benefits of using Big Data and the increased digitisation of the legal industry are accompanied by unique challenges, namely cyber security, analytical capacity and AI.
Primarily, the risk of having large amounts of data in cloud storage and with firms relying more on computerised systems, integrated with the internet, is that a cyber attack can be very costly. Attacks can range from attempts to steal confidential information to damaging internal systems. An attack on a law firm’s network can put the firm’s reputation, digital infrastructure and financial health at risk and with increasing connectivity, the risk is only rising.
For example, if a cyber attack was successful against a firm, the internal network which enabled lawyers to access emails and contact clients could be offline for several days, denying the firm valuable billing time. Further, if confidential information is stolen, such as intellectual property, client information and files relating to government work, that information could pose a great risk to third parties. Big Data contributes to this risk as the data used by the systems is drawn from clouds and thus requires networks to deliver and distribute the data. The more data collected, the bigger the cloud that is needed.
The Norse Corp has a live hack map showing live updates of hack attacks around the world. This map alone shows how virulent cyber crime and cyber attacks are becoming and law firms are a target on the list.
Finding The Right Tools
The second challenge created by Big Data is how to harness it. The analytical capacity of firms limits how they can use Big Data, and it is only useful if the analytical tools exist to deconstruct it and make it palatable.
With the systems becoming more complex, one requires more sophisticated ways to analyse and break down the Big Data to use it. As a result, one is limited by the tools of current times. Due to this, the gradual adoption of Big Data techniques will ultimately require an implementation that can disrupt a firm’s traditional strategy process and learn how to use the systems effectively will require valuable time and resources which may be constrained.
Last, AI poses a risk to the legal profession itself and as aforementioned, Big Data can be seen as a facilitator for a gradual move to more autonomous systems. The advent of artificial intelligence into the legal arena has both disrupted and augmented this services industry.
Such programmes range from doing simple registry searches automatically (RAVN) to reading and analysing clauses in contracts (Kira Systems). The recent news of more law firms implementing low-level processes has brought the question of AI’s relationship with the legal industry to the forefront. This disruption could fundamentally alter the way lawyers conduct business and provide advice and thus is a critical challenge to how lawyers conduct their business globally.
Cutting Out The Routine Work
Low-level legal work relies on a large volume of information coupled with a comparatively small amount of judgment, this type of work is ripe for AI implementation. What’s more, the software can accomplish certain tasks cheaper and with greater accuracy than a human. Simply put, a sophisticated AI challenges the need for paralegals and trainees to conduct such work.
For firms, an AI will effectively increase output by reducing a lawyer’s time on routine tasks. Thus, more time can be spent working on client relationships and bespoke legal challenges. Since law firms rely on clients to generate revenues, anything that can provide a competitive advantage and create value for clients will protect long-term profits. It, therefore, makes business sense to implement AI, but this comes at the price of low-level legal jobs.
Big Data is extremely useful for businesses looking to increase the accuracy of their strategies, create hyper-targeted services or products and analyse their own processes to a greater degree than was previously possible. With an increase in interactions between businesses and consumers taking place online, being able to understand one’s audience better is fundamentally a good thing.
Whatsapp Launches New Venture Aimed at Businesses
Whatsapp has launched a new app targeted at businesses, called the Whatsapp Business App, which they claim will enable companies to “communicate more efficiently” with present and potential customers.
This forms part of Whatsapp’s wider strategy to branch out into the corporate world. It plans to use the app to generate new revenue by charging businesses for using the extra communication tools that will enable them to better connect with their customers.
Although the app is set for worldwide release, at present it will only be available in Indonesia, Italy, Mexico, the UK and US. It includes a feature which indicates a business is authentic with a green tick badge next to their name.
Amex: Troubled Credit Card Company Reports $1.2bn Net Loss
On Thursday, American Express, or Amex, reported a net loss of $1,197m in the fourth quarter, the first net loss the company has experienced for 26 years.
Although the company stated that revenue from interest expenses was up 10% to $8.8bn, Amex said recent reforms to the US tax code meant the company incurred extra costs, including a repatriation cost on its foreign assets as well as a devaluation of its deferred tax assets. It estimates total costs amounted to $2.6m.
For the full year, net income was $2.7bn compared with $5.4bn the company earned in 2017. However, even with the estimated $2.6m the company claims it incurred from the recent tax charge, net earnings were still $5.3bn, $100m lower compared to last year.
In New York, American Express shares (AXP) took a near 1% tumble at the beginning of trade with shares finishing the day on $99.90. JPMorgan Chase and Goldman Sachs anticipate greater earnings for 2018.
“Overall, we believe the Tax Act will be a positive development for both the U.S. economy and American Express” said CEO and chairman Kenneth Chenault. Chenault also said he will be leaving Amex in “very strong hands” when his successor, Steve Squeri takes over next month.
American Express has suffered from an ever-reducing share in the credit card market and ended its 14-year relationship with American warehouse chain Costco who in 2016 made an agreement with the market leader, Visa.
Tencent Extends Facebook Lead
Tencent has shot past Facebook to become the world’s most valuable social network.
Editor’s Remarks: Although Tencent briefly overtook Facebook in terms of market cap in November, the recent selloff of Facebook shares prompted the Chinese tech titan to regain the lead. Facebook investors responded negatively to news that Mark Zuckerberg’s plans to highlight family and friend-based content on the newsfeed would reduce the amount of time people spent on the site. Shares in Facebook have fallen 5% since that announcement, enabling Tencent to gain a $19bn lead over the US company. Tencent’s growth has been spurred on by its diversification away from its flagship messaging app, WeChat, and into video games.
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