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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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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.

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.  

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.

MeasureCamp Berlin

MeasureCamp Berlin: A Preview

In preparation for this year's MeasureCamp Berlin, we sat down with Benjamin Bock, communications lead, to discuss what to expect, as well as his thoughts on the industry in general. Here's what he had to say: Can you explain MeasureCamp for people who haven’t been yet? MeasureCamp is an open, free-to-attend analytics 'un-conference' made by analytics professionals for analytics professionals (and everyone who wants to get there) around the globe. In that sense, it’s different to any conference you know of. Our schedule is created on the day of the event, and our speakers are fellow attendees. Listen to talks, give a talk, and discuss topics that really tickle your fancy. What can we expect at MeasureCamp Berlin this year? Let’s begin with what you can’t and never will expect at MeasureCamp Berlin: Sales pitch presentations. We’ve all been there… you are visiting a fancy, expensive conference and all you get is Heads of 'This n’ That' talking about what their team did, what they spent money on and that you should buy Product X to be as Data-driven as them (mind the cynicism). At MeasureCamp you can expect talks and discussion rounds by around 150 fellow experts, who all know the daily adventures of cleaning Data, setting up analytics or debugging tracking code or running mind-bending analysis first hand.  What is your best tip for someone that has never been at MeasureCamp before? Don’t rush it! MeasureCamp is about mingling with the analytics community as much as it is about the talks and discussion rounds. Pick a few talks that really interest you and use the rest of the day to get to know other attendees. Our awesome sponsors are also more than happy to talk to you. What is the best advice you got last year at MeasureCamp? On a personal level, I was able to get some really good advice when it came to data privacy topics. GDPR was still fairly fresh and nobody really knew if what they had done was actually enough to not get into trouble. That’s the kind of advice you only get if you have the chance to talk to other professionals face to face. On another note, what are the most sought-after skills and technologies currently used? I can only speak of my experience here. On a hard skill level and depending on the individual role, you need a solid understanding of web technologies (JavaScript, HTML, CSS) and tag managing systems to be able to implement tracking (plus some knowledge in mobile development when your focus lies on apps). When it comes to analysing and visualising Data, you should understand the tool you are working with and its underlying Data-structures. Being able to retrieve tool-agnostic Data with SQL and running more sophisticated calculations (e.g. with Python) has become more and more important over the last few years. But there are some softer skills, that should not be overlooked as well. As an analytics professional, you should never assume that your knowledge and language are common ground. You need to be a strong communicator, who is able to explain complicated concepts broken down to the absolute basics. In your opinion, what will be the biggest challenge in digital analytics in the next year? Two weeks ago, I would have answered “bringing web and app Data together”. Now that we know Google is working on that topic, it’s still a challenge, but one I am happy to tackle in the coming year. Digital Analytics is constantly changing. What do you expect to be the most talked about topic at MeasureCamp this year? As a Tracking Specialist with a focus on Google products, I’d love to hear some talks about Google Tag Manager Custom Templates. But my top guess is, that the newly released Apps and Web properties beta for Google Analytics will be the talk of the hour. MeasureCamp Berlin is an open and free-to-attend 'un-conference', taking place this year on the 28th of September. The final batch of tickets will be released on the 21st of August at 03:00 PM (CEST). Click here for more information and to get hold of your place. 

Where Tech Meets Tradition

Where Tech Meets Tradition

If you’re lamenting the decline of handmade traditional products, cast your cares aside. There’s a new Sheriff in town and its name is, Tech. Just a generation ago, children would leave the farm or the family business, go to school, and then move on to make their place in the world doing their own thing. Away from family.  Today, the landscape has changed and those who have left are coming home. But this time, they’re bringing technology with them to help make things more efficient and more productive. Is Tech-Assisted Still Handmade? In a word, yes. Artists still make things “from scratch”, except now technologies allow them to not only see their vision in real-time, but their customers, too. Have you ever wondered what the image in your head might look like on paper or in metal? What about the design of prosthetic arms and healthcare devices by 3D printers? You’re still designing, creating.  But just like any new technology, there’s still a learning curve. Even for cutting-edge craftspeople who find that sometimes, the line between craftsmanship and high-tech creativity may be a bit of a blur. Not to mention the expense for either the equipment required or being able to offer art using traditional tools at technology-assisted prices. Somewhere between the two, there is a trade-off. It’s up to the individual to determine where and what that trade-off is. Life in the Creative Economy One of Banksy’s paintings shredded itself upon purchase at an auction recently. AI is making music and writing books. Augmented Reality, Virtual Reality, and Blockchain all have their place in the creative economy from immersive entertainment to efficient manufacturing processes. Each of these touches the way we live now. In a joint study between McKinsey and the World Economic Forum, 'Creative Disruption: The impact of emerging technologies on the creative economy', the organisations broke down the various technologies used in the creative economy and how they’re driving change. For example: AI is being used to distill user preferences when it comes to curating movies and music. The Associated Press has used AI to free up reporters’ time and the Washington Post has created a tool to help it generate up to 70 articles a month, many stories of which they wouldn’t have otherwise dedicated staff.Machine Learning has begun to create original content. Virtual Reality and Augmented Reality have come together as a new medium to help move people to get up, get active, and go play whether it’s a stroll through a virtual art gallery or watching your children play at the playground.  Where else might immersive media play out? Content today could help tell humanitarian stories or offer work-place diversity training. But back to the artisan handicrafts.  Artistry with technology Whilst publishing firms may be looking to use AI to redefine the creative economy, they are not alone. Other artists utilising these technologies include:  SculptorsDigital artistsPaintersJewellery makersBourbon distillers America’s oldest distiller has gotten on the technology bandwagon and while there is no rushing good Bourbon, but you can manage the process more efficiently. They’ve even taken things a step further and have created an app for aficionados to follow along in the process. Talk about crafted and curated for individual tastes and transparency. It may seem almost self-explanatory to note how other artisans are using technology. But what about distilleries? What are they doing? They’re creating efficiency by: Adding IoT sensors for Data Analytics collection Adding RFID tags to their barrels Creating experimental ageing warehouses (AR, anyone?) to refine their craft. Don’t worry, though. These changes won’t affect the spirit itself. After all, according to Mr. Wheatley, Master Distiller, “There’s no way to cheat mother nature or father time.” Ultimately, the idea is to not only understand the history behind the process, but to make it more efficient and repeatable. A way to preserve the processes of the past while using the advances of the present with an eye to the future. If you’re interested in using Data & Analytics to drive creativity, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expect consultants to find out more. 

How Will New Financial Risk Regulations Affect European Banks?

How Will New Financial Risk Regulations Affect European Banks?

The financial crisis of 2007-2008 changed banking. The world moved from taking mortgage loans in our dogs’ names to introducing strict regulations for banks prohibiting them from giving out loans to “anyone” without assessing Risk properly. In 2010 the Basel Committee on Banking Supervision (BCBS) introduced BASEL III, a regulatory framework that builds on BASEL I, and BASEL II. This framework changed how banks and financial institutions asses risk. It introduced an Advanced Internal Rate Based Approach (Commonly known as the AIRB approach).  Now, the committee has introduced new changes and, by 2022, all banks and institutions will have to implement the revised IRB Framework, as well as new revised regulations for the standardised approach, CVA Framework and new frameworks for Operational Risk and Market Risk. So, what does this mean for those working Risk? Change Is Coming Change is inevitable, no matter what you do. If you work in Risk Management and Compliance, change is something you can expect to happen, often. As mentioned above, by 2022 there will be lots of changes. The Basel Committee calls this initiative the “finalised reforms”, or BASEL IV which builds on the current regulatory framework BASEL III. Quickly summarised, the changes limit the reduction in capital that effect banks IRB models.  This change is predicted to impact banks in Sweden and Denmark the most, with estimations that capital ratio will fall by 2.5-3%, far higher than the 0.9% expected for the average European bank.  So what does all this mean for Swedish and Danish banks?  What’s Happening Now? One of the main things that Swedish and Danish banks need to revise for these new regulations, are their internal models. The new regulations introduced a new definition of Probability of Default, measured through a model commonly known as a PD model. Effectively this means that every bank must “re-develop” their internal PD Models in the IRB approach. Consequently, we are already seeing a clear response from the banks in their strategies moving forward. It has already become quite apparent that many banks are looking to make IRB model development their focus for 2019-2020 and 2021. This has resulted in a boom in the hiring space for developers with experience in IRB Modelling and Credit Risk Modelling in general, which in turn has led to high demand in the face of the low supply of these types of candidates. Understandably aware of this, modellers are now looking to negotiate higher salaries.  What You Can Do  For candidates that hold the right experience, there are good opportunities at hand. If so inclined, they can utilise this chance to finally see if the grass actually is greener on the other side, or not. However, there are a couple of things worth considering before making a move.   Firstly, are you actually keen on switching jobs? Your skills are probably equally in demand at your current employer and, if you are having doubts about moving from the get-go, you may well be able to negotiate a rise without pursuing a new opportunity. However, if you are serious about finding something new, this is a great time to do so. The majority of banks have found that these new regulations are creating an unsustainable workload,  and are now looking for talent externally to expand their teams. This means that the experienced modeller can pretty much have their pick of the litter.  Furthermore, if you are a junior modeller, there are now plenty of opportunities for you to enter a niche area known for being exciting and innovative. So, wherever you are in your career, these regulatory changes  are likely to have a large impact and open up new avenues for you to explore.   We all know that regulations in banking and finance are now essential, we all agree, even if they can be a little frustrating. However, what people often fail to think of are the opportunities new regulatory requirements create. In the case of BASEL IV, we’re already seeing an increase in demand for strong talent, and a demand for people who are passionate about Risk Management and model development.  For businesses, new regulations also provide the chance to not only improve their teams, but to  create new models that can be utilised to optimise and automate. A lot of financial institutions are already aware of this and are using these models to gain competitive advantage over their competitors, as well as to stay one hundred percent compliant.  If you’re looking to build out you Risk Management team or take on a new Risk opportunity for yourself, we 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. 

How Data Is Shifting Defence

How Data Is Shifting Defence

When looking at the cyber security measures in 2019 the outcome is uncertain. Threats come in the form of pariah states, extremely skilled individuals, and illiberal actors. However, what is certain is the leaps and bounds made in technology.  Before computers, defence documents were in government offices. By the Second World War this would progress onto secure sites, take Bletchley Park for example.   The real watershed would come years later in the Cold War. While there was no direct military action (aside from the proxy Korean and Vietnam War), this tension was illustrated elsewhere, with the space race and nuclear armaments to name but a few. Both sides went to extraordinary lengths to guard and seize intelligence through covert ops. As this classified information made its way onto computers and in turn brought about new risks. This theme continues to the present day; as technology improves, so do offensive and defensive capabilities.  Hard Power With the advancement in technology this has been used by militaries to take and saves lives. Only a matter of years ago aerial bombardment would have to involve putting pilots at risk, flying deep behind enemy lines. These days, a bombing run could be carried out anywhere in the globe with the ‘pilot’ not having to leave their chair. How? Through Unmanned Aerial Vehicles (UAVs). This removes any casualties to their pilots, using advanced systems in Computer Vision to operate across the globe.  The ethics of this remain debated and there are many who express doubts at the use of AI, fearing their destructive potential. Others, however, see this as necessary advancement.  Indeed, in asymmetric warfare, established states’ advanced technology is near enough untouchable. Take an example from the US Marines. Still in testing, an advanced platform can allow troops on the ground to see if a room has been cleared, saving friendly lives. This is way above the capabilities of rogue terrorist forces, and looks set to play a crucial role in saving lives. It would seem highly unlikely that the Taliban, for example, could use sophisticated weaponry to bring down a jet.  However, the danger in 2019 now lies with the established illiberal states who still pose a serious threat. It is paramount that nations continue to advance, to both deter and, if needed, counter a hostile force. Soft Power While NATO states have shown dominance in physical terms over past foes, 2019 brings uncertainty when it comes to soft power, most notably cyber-security. The threats to this are very real, and are a put civilians at risk - take the Sony and NHS hackings as an example.  Moreover, the notion of alleged election meddling continues to plague politics, notably the US 2016 Election and the Brexit referendum. There have been several accusations of state-sponsored foul play incorporating the use of bots to influence people’s decision making, mostly through continual pressure on either fake news or mass-support of certain decisions. They impact society directly into our homes, considering the popularity of social media platforms like Twitter and Facebook. Alongside many other nations, the UK is taking action to counter this type of threat. Only recently a specialist cyber-security division in the army has been established, quite literally to both counter, and if needed, launch cyber-attacks.   Ultimately, society has come a long way, physically and online when it comes to defence. Sophisticated weaponry continues to develop but is raising new ethical questions, particularly in regards to the use of AI and Computer Vision. Civilian institutions remain at risk, with many having been targeted in hacks or through intervention on social media. Threats may continue to evolve, but so will defence strategies, with the two competing to stay one step ahead of the other.   If you’re interested in applying Data & Analytics to national security, we may have a role for you. Take a look at our latest opportunities, or get in touch with one of our expert consultants to find out more. 

How movie studios use data

Lights, Camera, Data

Whilst Data continues to play a huge role in all aspects of life; developing businesses, schools, health care etc., one industry has already seen a massive impact from the Big Data revolution. The film industry, and its television counterpart, were among the first see to the potential of how Data can transform the way they work.  Beyond profit, access to new types of Data is allowing companies to consider what audiences will be most interested in at specific times, utilising current viewing habits, what topics are the most popular on social media, and even the news so they can create something that tailors to everyone’s different interests. The Streaming Revolution Netflix’s popularity is down to more than the variety of movies and series it has to offer. Its pioneering use of recommendation systems, originating when it was purely a DVD rental service, means that it always knows what its subscribers want to watch, when they want to watch it, and on what device. Their ability to tailor bespoke recommendations, down to which poster people see, has created an entirely different approach to how viewers chose and engagement with entertainment.  Netflix’s Data collection means that it knows its audiences very well, something they can utilise as part of their marketing. By contrast, even a behemoth like Disney can struggle to compete. Following the success of 2015’s Star Wars: The Force Awakens, Disney Chairman, Bob Iger admitted ‘we don’t have any idea who went to see Star Wars in the cinemas’. Whist this may have not been too much of a problem at the time, given the film’s $2 Billion box office, the diminishing returns of the films that have followed suggests that better insight as to why the film was a success may have been beneficial. It’s no wonder, therefore, that Disney are launching their own streaming service later this year.  Beyond Box Office In the majority of businesses these days, Data is used to decipher consumer buying habits, web traffic and social media interactions, as well as to monitor supply chains, costs and sales. This is no different for the movie industry, particularly when examining what makes a move work. By using Data Science, producers can determine which actors, directors, release dates and even running times are likely to make a movie profitable. For example, history may dictate that the summer is likely to be the most profitable time of year. Whilst this may be true for June, where average profit is $100m, ten times that of January, November and December are the second and third most profitable months.   Beyond assessing profitability, however, Hollywood is using technology to try and re-establish a relationship between creators and audiences. Newly emerging tools are empowering studios to convert massive quantities of movie-goer reactions into meaningful actionable insights. With Big Data analytics, movie executives have gained an insight into audience’s perspectives and this is dramatically altering the way in which movies are made, marketed and distributed. Companies like IBM are looking at new ways of tracking sentiment analysis that will have a massive impact on the creative process. However, whether or not the industry’s leading writers and directors will want to work within these parameters is yet to be seen.  #DataDrivenAds Data’s impact on the movie industry goes beyond the insights it offers on audience perceptions. When it comes to marketing a movie, the Data & Analytics space offers a number of opportunities. Studios are beginning to realise that, in order to drive the small-screen generation to the big screen, they need to come to their territory. To promote ‘The Dark Tower’ in Singapore, Sony ran a series of targeted mobile adverts that allowed users to choose a character to engage with. A follow up campaign then targeted users who had engaged with relevant messaging and details of showtimes at their nearest cinemas, using the mobility of their devices to their advantage. Furthermore, for the release of ‘Ready Player One’, Facebook offered an augmented reality experience for those who engaged with the film’s poster in public.  However, sometimes, the most effective marketing technique remains word-of-mouth. Netflix’s ‘Bird Box’ received little critical praise and minimal attention initially upon release. However, once users started posting memes about the movie onto their social media feeds, viewing figures picked up exponentially. This allowed Netflix to reassess their marketing efforts and respond to public sentiment, creating a strategy that fed off the zeitgeist and was significantly more effective.  Data has transformed the movie industry. If you’d like to work with Data & Analytics to transform another, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

Creating Your Own ‘Unicorn’ Employee

The elusive unicorn. Once a mythical beast, it is now a term for a new mythical creature; the unicorn employee. As Data fields transition from generalist to more specialised niches within the industry, businesses are realising the need for more agile and adaptable employees. However, there is a bit of a twist on the business end. It’s a mix of a diversified skillset and expertise. Though one seems at odds with the other, it doesn’t have to be. On the flip side, employees want development, citing it as the number one reason for leaving a business in our 2019 Salary Guide. So, we thought we’d take a look and see where the disconnect was. After all, if employees want development and businesses want diversification, couldn’t the two come together for the benefit of all?  In a word, yes. Investment in employees through reskilling and upskilling are two important and useful ways to create your ideal employee and placement. There’s no better return on investment. Let’s take a look at how finding your unicorn employee can add value to your business. Think Outside The Job Description While the job description offers a good guideline of what’s expected in your day-to-day role, it can’t predict the changes, trends, and other issues within your industry. And in the digital tech world, change is the name of the game. Businesses need someone who can react quickly and effectively. Employees need to have skills either to manage the job themselves or know when to reach out to team members for help. This can’t happen in a siloed situation.  A few traits of the unicorn employee include flexibility, a curious nature, excited about learning new things, and the openness to offer suggestions within and across teams.  In a recent LinkedIn article, Hootsuite CEO Ryan Holmes captured it best. “Like actual unicorns, they’re hard to find, but once hired, offer up enormous benefits in the workplace. To name a few, they shatter expectations, raise the bar for everyone and are simply a joy to be around. Unicorn employees can literally take your business to the next level.” If you’re looking to hire a unicorn employee, look beyond their resume. While it’s a tool and will offer skills the employee has now, it can’t show you whether or not he or she will go the extra mile. And like the mythical beasts, these unicorn employees may come from surprising places, be open to new possibilities and think beyond the job description.  How to become a Unicorn Employee Be Coachable. Have a growth mind-set, a desire to learn, and find every opportunity to upskill. This is lifelong learning at its finest.Be a hard worker, but know when to rest and recharge.Raise the bar as a teammate and encourage others to do the same. Raise your Emotional Intelligence. Demonstrate empathy, be aware of your emotions and your teammates’, and help motivate others. How to Attract and Retain Top Talent As you plan your next level of hire in search of the not-so-elusive ‘unicorn’ employee, consider these few steps to get you on the right track. Understand job roles. The job beyond what’s on paper. See what it’s like on the other side and make assessments from the point of an employee. What’s their day-to-day routine, touchpoints, and technology turn-ons to help them do their job?Employee experience and technology are forever entwined. What tech skills do your potential employees have and what would they like to learn? Does their curiosity spark yours? Broaden your range. Encourage employee participation in technology decisions and include people from a wide range of levels and departments. Let them help with planning, selection, and design. After all, who better than those who use it and know it inside and out?To upskill is to create lifelong learning opportunities through classes and beyond. Other ways to upskill include exploring new mind-sets, developing diverse relationships, and redefining how people work. These few suggestions scratch the surface. Though, Gartner does offer these strategies in competing for talent. The demand for top talent and the scarcity of it hasn’t diminished, but with a few tweaks to your planning strategy, you can lay the groundwork for attracting great employees. If you’re an employee hoping to broaden your range, open to new technologies as well as reaching out in a department not your own, and a team motivator. You might be a ‘unicorn’ employee. Somewhere between the two, we hope you’ll meet and in next year’s guide, development and diversification won’t be quite as at odds with each other. Companies need to remember candidates are stakeholders in the hiring process. Candidates need to remember sometimes it comes down to education. Educate the company how you can best serve them. That question they ask – why do you want to work for this company? This is where you ‘wow’ them and educate them to your why. Be flexible in your hiring and consider flipping from top-down to manager-centric in a bottom-up approach. After all, who is better positioned to offer insights into how jobs are changing and the skills required for it. If you’re looking for a unicorn, or to make your mark on a company, check out our current vacancies or get in touch with one of our experts consultants to learn more. 

Data & Analytics in Munich

Three Reasons Why Munich Is The Place To Be For Data Analysts

As one of the world’s largest economies, Germany continues to attract tech talent from all over the world, and has even overtaken the UK in terms of intra-Europe tech immigration in recent years. Whilst Berlin may be the first place that comes to mind when thinking of places to live as a Data Analyst in Germany, with its numerous start-ups and international culture, there are several reasons why you should also consider the southern gem of Munich. Here are three of the best: A First-Class Quality Of Life While the first thing that comes to mind when thinking of Munich is often the world famous Oktoberfest and the beer induced crowds packed into small beer tents paying the equivalent of a year´s salary for a pint, this is not the only thing Munich has to offer. During the other 349 days of the year when Munich is not packed with Lederhosen-wearing crowds from all over the world, it is a tranquil, green place to live.  Munich is home to a number of large parks, including the beautiful Englischer Garten, Museums and a number of non-beer related cultural events throughout the year. It’s also the third largest city in Germany and, as such, has all the benefits that big city life has to offer. However, nature is never far away, with a beautiful mountain landscape just on the horizon, including the tallest mountain in Germany, the Zugspitze, which sits only 90 km away. On top of this, the transportation system in Munich is one of the best in the country; clean, efficient and so simple to use, it actually makes commuting bearable.  Expansive Opportunities  Most major European cities have seen a boom in the tech market in recent years and Munich is no exception. Not only home to some of the biggest global and German players such as Amazon, MunichRE, Man, Allianz and Linde, the city is also seeing an increasing amount of investment in tech start-ups.  This has led to tech talent, particularly Data & Analytics talent, being highly sought after by a number of the country’s biggest and best employers. And healthy competition means even healthier salaries. Even though Munich doesn’t have the lowest cost of living around, the average pay for Data Analysts is higher than in most other German cities, meaning you’ll get to make the most of your time away from the office.  A Thriving International Culture With 25-38% of Munich´s residents originating from other nations, more and more companies, big and small, are open to welcoming English speakers into their teams. While the culture in Munich still makes it easy to immerse oneself into the German language and culture, the city is also very welcoming to its international inhabitants.  Of course not everyone can speak English, but it is surprising how many people do. This makes getting around as a non-German speaker that much easier, especially considering that the Bavarian version of German can sometimes feel like a completely different language to what is spoken by the rest of the country.  Like every country, different cities attract different personalities and find the right place for you is crucial before making a move. But, with its high quality of life, great job prospects and international culture, Munich certainly has a lot to offer for any Data Analyst looking to move to or within Germany.  If you’re considering making a move to Munich, take a look at our latest opportunities, or get in touch and we can discuss what could work best for you. 

Our New Berlin Office

We've launched two new offices

I'm incredibly pleased to announce that this week we have launched two new offices.  The first, in central Berlin, will solidify our on-the-ground presence in the German capital and allow us to continue to develop our client base in this rapidly-growing market. Run by Senior Manager Peter Schroeter, under the guidance of our Director of Europe, Alex Hutchings, we're really excited to see the new space become a hub for Berlin's Data & Analytics talent.  Secondly, we've also opened a second Wimbledon office. Despite only moving in to our current home 18 months ago, our rapid growth has led to us opening an additional Executive Office to house our Operations team as we bring in more and more expert consultants. Fortunately, it's just over the road, so there's no need to grab a bus between meetings.  This continues to be a great time for Harnham and watch this space for more growth news in the not too distant future. 

Machine Learning: How AI Learns

Machine Learning: How AI Learns

Amazon has begun curating summer reading lists. How? Patterns. Facebook shows you ads for items you may have been searching for online. How? It learns from your browsing habits. Ever wondered how Facebook knows you were just looking at that pair of shoes or that particular guitar. The Data you feed it, feeds its brain. In other words, this is how Artificial Intelligence learns. Machine Learning. Whilst it can be disconcerting to know that a machine understands our buying habits, that’s not the only thing it’s used for. It’s also a pivotal tool in such areas as Bionformatics, Biostatistics, Computational Biology, Robotics, and more.  What is Machine Learning? Ultimately, it’s a method of Data Analysis which helps to automate model building and is part of Artificial Intelligence. In other words, it helps to solve Computational Biology problems by learning from Data to identify patterns and make decisions with little human intervention. This helps scientific researchers learn about many aspects of biology. However, running a Machine Learning project can be difficult for beginners, who may experience issues when trying to navigate the information without making mistakes or second guessing themselves. This is one of the reasons a Computational Biologist might want to upskill with a course or two in Machine Learning for a more robust understanding of the information being learned and applied.  The Good News and the Bad With each shift of industrial revolution, there has been one system which has made an indelible mark on our daily lives and the Fourth Industrial Revolution is no different. Just like we can no longer imagine factories without assembly lines, we can also no longer imagine not having Siri, Google Maps, or online recommendations. But, as exciting and as important as these things are, Machine Learning has become so crucial to our daily lives, so complex, it takes a technology expert to master it leaving it nearly inaccessible to those who could benefit from it. Why is Machine Learning Important? By building models to peel back the layers and discover connections, organisations can more easily and more quickly make improved decisions with little to no human intervention. Computational processing is both more affordable and more powerful. It’s possible to quickly scale and produce models which can analyse bigger and more complex data and there’s also a chance to identify opportunities and to help avoid any unknowns such as risk. Machine Learning is used in every industry from Retail to Financial Services to Healthcare. Here are just a few ways it has already transformed our world. Retail – Retailers are able to learn from their customers buying habits, predictive buying habits, how to personalise a shopping experience, price optimisation, and customer insights.Financial services – Machine Learning helps to prevent fraud and identify Data insights.Healthcare – Wearable devices allow for real-time data to assess a patient’s health. Medical professionals can also more quickly find red flags which can help improve diagnoses and treatment.Oil and gas – It cannot only help find where oil might be, but also predict refinery sensory failure, and streamline distribution.Transportation – Help to make routes more efficient and predict problems that could affect the bottom line. While humans can create at least one or two models a week; Machine Learning can create thousands.  Ultimately, the goal of Machine Learning is to understand the structure of Data. As it learns to determine what Data is needed for its structure, it can be easily automated and sift through Data until a pattern is found. This is how machines learn. If you’re looking to take your next step in the field of Machine Learning, we may have a role for you. Take a look at our latest opportunities, or get in touch to see if we can help you take that next step.

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