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With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

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FROM HEALTHCARE TO HOSPITALITY HOW BIG DATA TRANSFORMS INDUSTRY

From Healthcare to Hospitality: How Big Data Transforms Industry

Big Data, once a looming anomaly for many businesses, has transformed. No longer a buzzword, it is essential to enterprises everywhere – from healthcare to hospitality. Whilst it’s taken about a decade to get here, the last two years are truly telling.  With the amount of Data flowing through our systems, over 2 quintillion bytes each day. Think Apple Pay at Starbucks, credit card purchase, filling out of forms, GPS, our phone Data, traffic cameras and lights for traffic control. Big data is now big business. Top Industries Using Big Data and Analytics While the most prevalent industries which come to mind are retail, entertainment, and politics. There are two which, until now, have been coming in under the radar and have seen some of the biggest changes using Data & Analytics; healthcare and hospitality. Whilst they don’t seem to go together, they do have one thing in common – the experience. Hospitality  As you plan for your next vacation, you may be debating the merits of a hotel reservation versus an AirBnB. Lodging options in the share-economy have forced traditional accommodation options to rethink their strategies. The ease of “mobile first” which allows customers to manage their bookings, stays, and travel experience through their phones is in direction opposition to the client-facing hotel industry.  There is a massive shift happening in this industry and a powerful Data Analytics tool can help create visualisations from a company’s Data. Not only can these provide insights for the future, but they also offer suggestions for strategies which can be implemented now to impact future prospects. Healthcare  One of the most telling industries being transformed by Big Data is healthcare. Access to care is not only available in-office, in-person, but now with the advent of Telemedicine, patients can get questions even more quickly. No matter the industry today, this is a buyer’s market, or in most cases, a customer’s market. And its customer satisfaction which drives the success of a business. In healthcare, it’s patient satisfaction. Patient satisfaction scores underlies everything from hospital funding to the return visits in the private sector. Like any business, the patient experience in the healthcare industry, begins with initial contact, staff responsiveness, communication by doctors and nurses, wait times, even equipment and cleanliness of facilities to name a few examples. Once all the Data and information is gathered, collected, and analysed, these healthcare professionals are able to make any necessary adjustments. As quickly as Data has grown in the last couple of years, the projections for healthcare can expect to see a high volume in the next seven years. One of the highest benefits which can add to patient experience is the database of patient’s information can be shared across healthcare organisations saving time, money, and patient stress which all leads to better treatment for the patient’s needs.  In fact, according to the International Data Corporation (IDC), healthcare Data is expected to grow faster than industries such as the media, manufacturing, or financial services. Advancements such as chatbots, virtual assistants, Big Data Analytic tools, and medical imaging have all added to the transformation.  As strong and as prevalent as many of these advances are, many organisations still struggle to find the right candidates with the right Data skill sets. Many have neither a blockchain strategy nor have plans to implement one and are falling behind. There is a next generation opportunity here to more fully transform digitally, but the right people need to be in place to make it happen. Digital transformation isn’t slowing down and is becoming more critical at a rapid rate. By making investments in your health IT, analytics tools, and people, you’ll be ready to close the digital transformation gap. If you’re interested in Big Data and Analytics with an eye toward the Life Sciences field, we may have a role for you. Check out our current vacancies or get in touch with one of our expert consultants to learn more. 

Eoin Pierce

Eoin Pierce

19. September 2019

HOW PROGRAMMATIC IS REVOLUTIONISING ADVERTISING

How Programmatic Is Revolutionising Advertising

With consumerism on the rise, and a drastic shift away from traditional avenues of advertising, the use of Digital Marketing and the demand for business to become more technically ‘savvy’ is continuously increasing. The extent of different digital media channels in the advertising space, as well as the recent evolution of approaches such as Programmatic Advertising, has caused confusion as to which approach is the best for businesses to adopt and for well versed Digital Marketers to reflect on what their next career step should be.  Irrespective, Programmatic is such a buzzword within the market at present and is widely predicted to become the future of display advertising. Despite this, many have a lack of understanding as to what it actually is. Whether you are looking for a career change or to embed Programmatic into your marketing strategy, here are some considerations: Defining Programmatic  Programmatic advertising is the automated process of bidding for advertising inventory to allow for the opportunity to display a relevant advert to the desired consumer in real time.  At a basic level, parties from the ‘supply’ side of programmatic will sell an impression referred to as ‘audience ‘inventory’ through a Supply Side Platform. Facilitated by the ad exchange, such inventory is shared with advertisers who have submitted their desired audience preference through a Demand Side Platform. Within this online, automated marketplace, all advertisers will bid within the auction and the highest ‘bidder’ will then win each impression. The advertiser, typically a media agency or in house team of specialists, will begin to target users through Programmatic Ads that can be online or Out Of Home (OOH). Redefining your advertising strategy  With pre-existing modes of marketing such as, newspapers, radio, TV and, more recently, social media and paid search; it is worth considering the additional ways in which Programmatic advertising can benefit your business. Rather than utilising Data-driven ‘trial and testing’ methods to assess what will attract audiences to your site, Programmatic advertising uses a personalised approach by only targeting users who have expressed an interest in specific products or services. The automated process of identifying target users enables this to be a lot less manual than traditional modes of advertising. As a result, this will save your business time and unnecessary resources dedicated to Predictive Analysis, which will particularly benefit smaller businesses who may have a limited marketing budget.  Programmatic advertising is also not just limited to online. The development of OOH has revolutionised the power, audience reach and impact of this long-standing method of advertising, allowing it to “bring data into the physical world” on a mass scale.  As well as delivering a single ad to the right user at the best time, Programmatic advertising can enable your business to target hundreds of relevant consumers based on their online activity and location. This form of audience targeting is still incredibly new to the marketplace and is continuing to expand. By 2021, it is anticipated that Programmatic will further bridge the gap between digital and offline media by programmatically purchasing tv adverts; representing approximately one third of global ad revenue. The future of advertising careers If you are looking for a long-term career within advertising, Programmatic is a great route to gain exposure within, given that it already dominates the industry, and looks set to continue to.  Due to such high demand and the lack of quality candidates within the market, Programmatic specialists are incredibly desired and retained by employers. As such, businesses are consistently searching for more talent within their team. Once onboard, they often invest heavily in training, personal development and internal progression.  There is often a misconception that Programmatic is not scientific, however, specialists often sit in Data teams and utilise Analytics software or Data Visualisation tools daily; extracting and manipulating Data. Server-side scripting is also a huge part of the role; if an ad is not displaying on a site suitably, the Programmatic team will be required to dive into the JavaScript or HTML code to troubleshoot the issue.  So, if you are looking for a Data-led vertical of advertising, Programmatic is a great career path. However, the supply and demand side are kept very separate due to the difference in tools utilised. Transitioning between the two can be incredibly problematic, especially further into your career so, if you are looking into a specific route, make sure you are making an informed decision. If Programmatic sales, inventory analysis and yield optimisation are appealing, the publisher side could be a great route. Alternatively, if setting up and monitoring campaigns or segmenting audience Data is of interest, I would advise starting agency side. Whether you’re looking to venture into a new aspect of digital media or require specialist talent within your team, we can help. Take a look at our latest opportunities or get in touch with myself at francescaharris@harnham.com to find out more.

Francesca Harris

Francesca Harris

12. September 2019

Web Analytics Career To Data Science

HOW WEB ANALYTICS CAN LEAD TO A CAREER IN DATA SCIENCE

The Web Analytics world is evolving. What used to require an understanding of Google Analytics, some tag management and visualisation for presentation purposes has grown into something much more. Whereas Web Analysts may have once been lone players in a Marketing team, they’re now expected to sit as part of, and feed into, an enterprise’s Insight team.  This exposure to more comprehensive forms of Data Analysis has led many Web Analysts to explore what the next step in their career could be. Namely, should they move into a Data Science position? For those who are looking to make this move, here are some considerations: Technicalities and Technologies  Digital Analytics are not excluded from the debate over what it means to be a Data Scientist, especially given that some with a Data Scientist job title may in fact be Web Analysts, and vice versa. Many Web Analysts are now working with a number of Data Science tools, including SQL, Python, and R. By using these alongside Google or Adobe Analytics, they are able to form a comprehensive view of the customer, using different types of Data, in different forms, from different sources. However, there remains a gap between the use of these tools and actually working within Data Science.  The most logical leap for a Web Analyst to make is to a Customer Insight or Digital Insight role. This type of role would still involve the analysis of online Data, but would likely be paired with building models, Predictive Analysis, reviewing customer LTV and creating a picture of customer online, offline and post-purchase behaviour to enable better targeting and retargeting. However, the knowledge gap between Web Analytics and Data Science may be more significant than one would anticipate.  Your Current Position  As a Web Analyst, you may well sit within a larger Data, Digital or Customer/Marketing Analytics department. Your exposure to these experts is one of the best assets you have available. Use the environment you are in to learn, upskill and gain hands-on experience. Knowledge of the necessary tools and languages is unlikely to be enough to lead to a move into Data Science and by getting hands-on commercial experience, you drastically increase your chances of success.  If you are able to expand on the tech that you have already used, take advantage of this. Even if this is just in a consulting capacity, your ability to demonstrate a real-world application of your knowledge makes you significantly more appealing as a candidate. Plus, your knowledge of, and approach to, Web Analytics may actually work to your advantage when it comes to assessing Data quality. Consultancies and agencies often provide the best training opportunities and are more likely to allow you the opportunities to hone new skills. If you are fortunate enough to work in an environment like this, make the most of it. Attitude Is Everything It may sound like a cliché, but Hiring Managers are on the lookout for people that they know will benefit their business and attitude plays a huge part in this. Do not underestimate the importance that is placed on cultural fit during an interview process.  Whether you are looking to make a move internally or externally, you should demonstrate your intrigue and willingness to learn. If you already have a strong record of progression within your current career, this will benefit you moving forward. When it comes to preparing, take time to dive into the world of Data Science, attend events and meet-ups, and continue to widen your remit. If you don’t have exposure to Data Science at work then you will also need to be learning SQL, Python and R at home to ensure you have a firm understanding of all the relevant technologies.  Whatever role you are looking for, the worst thing you can do is not apply. One of the most common mistakes we see is analysts not applying to an opportunity because they would need to develop in some areas once in the role. If you are able to demonstrate the above attributes many enterprises, particularly agencies and consultancies, may still be willing to take you on. And, if you’re not looking to make a move, don’t panic; Web Analytics skillsets remain highly sought-after and valuable. Whether you’re looking for a new career in Data Science or your next role in Web Analytics, we may have a job for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.  

Harriet Coleman

Harriet Coleman

05. September 2019

How Big Data Is Impacting Logistics

How Big Data is Impacting Logistics

As Big Data can reveal patterns, trends and associations relating to human behaviour and interactions, it’s no surprise that Data & Analytics are changing the way that the supply chain sector operates today.  From informing and predicting buying trends to streamlining order processing and logistics, technological innovations are impacting the industry, boosting efficiency and improving supply chain management.  Analysing behavioural patterns Using pattern recognition systems, Artificial Intelligence is able to analyse Big Data. During this process, Artificial Intelligence defines and identifies external influences which may affect the process of operations (such as customer purchasing choices) using Machine Learning algorithms. From the Data collected, Artificial Intelligence is able to determine information or characteristics which can inform us of repetitive behaviour or predict statistically probable actions.  Consequently, organisation and planning can be undertaken with ease to improve the efficiency of the supply chain. For example, ordering a calculated amount of stock in preparation for a busy season can be made using much more accurate predictions - contributing to less over-stocking and potentially more profit. As a result, analysing behavioural patterns facilitates better management and administration, with a knock-on effect for improving processes.  Streamlining operations  Using image recognition technology, Artificial Intelligence enables quicker processes that are ideally suited for warehouses and stock control applications. Additionally, transcribing voice to text applications mean stock can be identified and processed quickly to reach its destination, reducing the human resource time required and minimising human error.  Artificial intelligence has also changed the way we use our inventory systems. Using natural language interaction, enterprises have the capability to generate reports on sales, meaning businesses can quickly identify stock concerns and replenish accordingly. Intelligence can even communicate these reports, so Data reliably reaches the next person in the supply chain, expanding capabilities for efficient operations to a level that humans physically cannot attain. It’s no surprise that when it comes to warehousing and packaging operations Artificial Intelligence can revolutionise the efficiency of current systems. With image recognition now capable of detecting which brands and logos are visible on cardboard boxes of all sizes, monitoring shelf space is now possible on a real-time basis. In turn, Artificial Intelligence is able to offer short term insights that would have previously been restricted to broad annual time frames for consumers and management alike.  Forecasting  Many companies manually undertake forecasting predictions using excel spreadsheets that are then subject to communication and data from other departments. Using this method, there’s ample room for human error as forecasting cannot be uniform across all regions in national or global companies. This can create impactful mistakes which have the potential to make predictions increasingly inaccurate.  Using intelligent stock management systems, Machine Learning algorithms can predict when stock replenishment will be required in warehouse environments. When combined with trend prediction technology, warehouses will effectively be capable enough to almost run themselves  negating the risk of human error and wasted time. Automating the forecasting process decreases cycle time, while providing early warning signals for unexpected issues, leaving businesses better prepared for most eventualities that may not have been spotted by the human eye.  Big Data is continuing to transform the world of logistics, and utilising it in the best way possible is essential to meeting customer demands and exercising agile supply chain management.  If you’re interested in utilising Artificial Intelligence and Machine Learning to help improve processes, Harnham may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.  Author Bio: Alex Jones is a content creator for Kendon Packaging. Now one of Britain's leading packaging companies, Kendon Packaging has been supporting businesses nationwide since the 1930s.

Guest Blog

Guest Blog

29. August 2019

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