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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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Why Data Analysts Should Consider Consultancies

Why Data Analysts Should Consider Consultancies

Over the past decade, the world of Data & Analytics has seen consistent growth in the number of consultancies around, particularly throughout the Nordics. Naturally, the household names, the so called “Big Four”, dominate the industry, but an influx of more niche and targeted consultancies are starting to change the shape of the market.  With new technologies and a never-ending stream of Data challenging businesses, it should be no surprise that many are turning to consultancies for help. And with this increase in demand, follows a need for top talent. But, with so many potential options out there, why should Candidates look to move away from client-side?  THEY’RE INVESTING The Data & Analytics industry is booming, despite the fact that the demand for talent is significantly higher than the supply. As a result of this, a lot of the biggest consultancies are now trying to gain a foothold in this area of the market, investing money into building out their Data teams.   However, they’re facing competition from a number of emerging niche consultancies with direct focus on Data, or even more specific expertise, such as Cloud computing. As a result, consultancies are putting a lot of time and resource towards getting the best people and securing the highest level of competencies. Not only does this put candidates in a strong position, but also means that the majority of consultants are working in environments surrounded by a very high level of expertise.  THEY’RE FEELING ‘THE YOUTHQUAKE’ Consultancies generally have a very strong reputation and often feature highly on graduating students’ lists of preferred employers. In Norway, in the list for most attractive companies amongst students, three consultancies featured in the top ten. The promise of exciting projects, a fast paced environment, fast career progression and adaptability continue to draw the best young talent around.  Interestingly, however, in neighbouring Sweden the list is drastically different, with no consultancies featuring. In fact, in the Swedish list, we see a greater emphasis on home-grown companies with Spotify, IKEA and Volvo all featuring. Potentially this is because Norway lacks tech giants, and world dominating furniture companies, and instead is home to Equinor, Telenor and Aker Solutions.  EXPOSURE, EXPOSURE, EXPOSURE There’s no denying that success at a consultancy relies on a lot of hard work. But, with that, comes a number of benefits and working at one is a great way to get a lot of experience, quickly. Those early on in their careers in a consultancy will frequently face different projects, and will gain a lot of exposure to different situations and problems. Consultants also get hands-on experience in dealing with stakeholders, both internal and external, and, as a result, get to develop skills in explaining their findings to those who are non-Data literate.   They’re also, often, prestigious and highly sought-after places to work at and, with that, comes a level of status and renown that looks great on a CV. Plus, the fact that they’re home to a lot of top talent makes consultancies great places to form a strong network of fellow Data Analysts.  THERE’S SPACE TO GROW From working with a number of consultancies, it’s a abundantly clear that they offer great opportunities for internal growth. It’s not unusual for a Graduate Consultant to build a career and climb the ranks, gaining more and more responsibility as they advance.  Plus, as I mentioned above, consultancies also provide lots of opportunities for your long-term career, given the hands-on skills Consultants develop in technological competence alongside stakeholder and client. Companies like people with consultant backgrounds on their CVs as it highlights exposure to and number of different projects and experience in stakeholder management.  If you’re looking to take the next step in your career, and think a consultancy might be the right place for you to go, Harnham can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

What Will Happen In The World Of Data & Analytics In 2020?

What Will Happen In The World Of Data & Analytics In 2020?

The New Year, and the new decade, have arrived. The past ten years saw Data move to the forefront of public conversation following a number of big leaks and controversies. But, realistically, the impact of the ease of access to a surplus Big Data has only just begun to be felt.  Whilst many are predicting what the world will look like by the end of the 2020s, discussing how far AI will have come and the consequences of automation on the job market, we’ve decided to look a little closer to home.  With that in mind, here are a few trends we expect to see over the next year.   ACCESS TO DATA SCIENCE WILL BECOME EASIER Data Scientists have traditionally been limited in number, a key group of individuals with PhDs, honed skills, and a vast understanding of Data & Analytics. However, with the advent of a number of new tools, more and more users will be able to perform Data Science tasks. However, many of the more sophisticated processes are still far from being replicated, so those currently working in this area shouldn’t be concerned. In fact, the more standard tasks that can be automated, the more time Data Scientists will have to experiment and innovate.  THE 5G EXPLOSION  Whilst there may have been a soft launch last year, the introduction of 5G will have a much more significant impact over the next year. With a flurry of compatible mobile devices around, and many more expected to come, we’re likely see 5G networks hit the mainstream.  In the world of Data, this is likely to have a huge impact on how businesses use the Cloud. Indeed, with mobile upload and download speeds set to be so fast, there is a chance that an online middle-system may no longer be as necessary as it once was.  THE RISE OF THE EDGE On the subject of the Cloud, it’s worth talking about Edge Computing. No, this has nothing to do with the pizza or the guitarist. Edge Computing has been a trend for a few years now, but, following an announcement from AWS, it looks set to become much more prevalent in 2020.  Concerned with moving processing away from the Cloud and close to the end-user, Edge Computing is already beginning to have an impact across a number of industries.  A NEED FOR AUGMENTED ANALYTICS It’s no surprise that the use of AI, Machine Learning and NLP is set to increase over the next year, so it shouldn’t come as a shock that Augmented Analytics are set to become more popular too.  The opportunities, and extra time, offered by using the automated decision making offered by Augmented Analytics are the perfect fit for the increasing number of organisations who find themselves with more Data than processing capabilities.  DATA WILL HELP FIGHT THE CLIMATE CRISIS  Whilst there is a fair argument that the amount of processing required by the world of Data & Analytics is detrimental to the climate, the benefits any insights can offer are likely to outweigh any negative impact.  Indeed, the UK government are already using Satellite Data to help reduce the impact of flooding, whilst Google’s EIE is being used to map carbon emissions with a view to better plan future cities. Given the recent, and tragic, bushfires in Australia, this is going to become an even more pressing issue over the next 12 months.  If you want to be at the forefront of the latest innovations in Data & Analytics, 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 how we can help you. 

HOW AI AFFECTS US FROM JOURNALISM TO POLITICS

How AI Affects Us from Journalism to Politics

It’s been nearly 40 years since the War Games movie was released. Remember the computer voice, JOSHUA, who asked the infamous, “Would you like to play a game?”. The computer had been programmed to learn. You might call it a forerunner of Artificial Intelligence (AI) today. Except AI is no longer the little boy who becomes a stand-in for a grieving family. Now, we’re no longer watching a movie about AI, we’re living in its times. But unlike a movie, we won’t find a solution after 90-minutes to two hours. Now, we must be cautious and pay attention or we will be leapfrogged by our own inventions. Can we change course at this late stage? As we enter a new decade, let’s take a look at some of the concerns and solutions posed by Amy Webb, author of The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity.  How Did We Get Here? As Christmas approaches, we are cajoled by memories and makers to buy back our past and cement our futures with things. Our desires for instant gratification keep us from planning for AI properly. While it can be fun to watch AI play against Chess champions or worrisome to watch it direct our buying decisions, we remain secure in that its not yet to its full potential. But elements such as facial recognition and realistic generation cause concern for a number of reasons. Not the least of which is what will happen when systems make our choices for us. From the Big 5 of Tech to your local commercial or paper, our minds are already often made up. And even when we’re presented with the truth, we may not even realise it because our AI capabilities have grown exponentially and continue to grow making us wonder…what if? So, What Can We Do? Businesses, Universities, and the Media all have a part to play. And in our image-centric world, the greatest of these is Media. Universities can blend technical skills with soft skills and blend in degrees such as philosophy, cultural anthropology, and microeconomics just to name a few. The blending of these skills can offer a more robust understanding of the world around us.  Businesses can work to ensure a more diverse staff and improve inclusion. Shareholders and investors can help by slowing down when considering investments in AI to allow for determining risk and bias before moving forward. And when it comes to the Media, there’s general agreement the public needs greater media literacy. While AI-focused accusations of deepfakes in news and on television abound, there is a greater concern in that much of what people believe to be fake, isn’t. So, the question becomes, how does the media generate trust in a public that no longer believes what it  reads, sees, or hears?  It’s this casting of doubt which is the greater danger. Why? Because it requires no technology at all. While it’s best to be informed, it can be tricky to navigate in today’s world. So, it’s up to not only the news consumers, but is up to researchers, journalists, and platforms to separate the wheat from the chaff. Or in this case, the real from the fake before the news reaches its audience. From Socrates who taught his students to question what they learned to the students of the 20th century expected to remember only what was needed for a test; we have come full circle. But at a unique time in our world, in which the questioning has not much to do with challenging ourselves but is at best used to sow distrust.  While tech companies like Facebook and Google have jumped on the bandwagon to expose fakes, others are moving into how to build trust. Again. At best, these startups offer comparisons of videos and images as the human eye works to discern the difference.  But while tech may be advancing technological wonders by leaps and bounds, there remains a solid grounding of the human element. Humans are needed as content moderators to dispel fiction from truth. And in the media? There’s a renewed focus on training journalists to fact check, detect, and verify their stories. The human element adds a layer of nuance machines can’t yet emulate. If you’re interested in AI, Big Data and Digital or Web Analytics, we may have a role for you. Take a look at our current opportunities, or get in touch with one of our expert consultants to find out more. 

How Has The Short Supply Of Data Analysts Impacted The Industry?

How Has The Short Supply of Data Analysts Impacted The Industry?

Is Data the world’s most valuable asset? Every business has it, most use it, and the best transform their businesses with it. It’s unsurprising, then, that there is now an enormous demand for Data Scientists, Data Engineers, and all forms of Analysts. Whilst many enterprises are now beginning to see the benefit of internal Data education, progress in upskilling remains slow. But how is this impacting the industry?  Education, Education, Education For starters, with the evolution of Data, we have also seen an evolution in education. Universities have long been our source for acquiring knowledge, skills, values and beliefs. As such, they continuously reinvent the way they educate, modernising and adapting to the present day. So, it will come as no surprise that we are seeing more and more Data focused programmes and degrees in top universities around the world, including in the Nordics.  This is a great way of organically growing Data talent and supplying businesses with freshly educated minds, and should, in the long term, help conquer the short supply of talent available. As there is little to no sign that Data will become irrelevant anytime soon, providing an education in this area makes sense. And, with so many training and educational opportunities now available, businesses looking to upskill their employees have the option to externally fund their development. A Fountain of Youth Another highly visible effect of this talent shortage, and something unique to the Data & Analytics industry, is a lack of experienced leaders. Whilst there definitely are great leaders within this space, all with plenty of knowledge, the young make-up of the market means that their experience is often limited. Having reported on the state of the industry in our Diversity Report, Harnham found that over 60% of the Data & Analytics community is aged between 25 and 34, with 35% aged between 35 and 44. In other words, those leading the industry are young, or at least younger than in many more established industries. There are some obvious reasons for this, as Data is a relatively new field, and its importance to businesses has only emerged somewhat recently. Of course, having young leadership does not imply ignorance or inadequacy, but simply highlights how young the industry is, and how those leading may still have plenty of room to develop.  Fast-Paced Progression Going hand-in hand with young management is, unsurprisingly, an industry that offers fast progression. From the moment you step out into the wild world of Data & Analytics, there are numerous opportunities to progress quickly into specialist and management roles. However, this has stabilised somewhat recently.  Our 2019 Salary Guide uncovered that it now typically takes 10 to 12 years to reach a Director/Head of position. Obviously these numbers are an average, with those in Digital Analytics progressing significantly faster than those in Risk Analytics, alongside natural variations depending on the sector and size of individual businesses.  What remains apparent is, with such a high demand for talent that’s in short supply, it is crucial that businesses can both recruit and retain the best individuals out there. By keeping the above in mind, and ensuring that education, progression and leadership opportunities are on each employee’s career path, enterprises stand a better chance of getting hold of, and keeping, the best people in the industry.  If you’re looking to get hold of the best employees in a talent-short market, or are looking to take the next step in your career, Harnham can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

A decade of data

A Decade of Data

Y2K was nearly 20 years ago. Remember when we were all worried about the massive changes that could mean; the preparations we made getting ready for the turn of the century? Ten years later, we scoffed at our worries and hopped on the Data bandwagon…some of us. Others are still trying to catch up but in recent years, most businesses have realised it isn’t a matter of “if” you should have a Data strategy and begin to build your team, it’s a matter of “if you don’t do it, you’ll be left behind.” As the year and the decade come to a close, we thought we’d take a look back and see some of the trends which have shaped a decade of digital transformation. And like everyone who takes a moment to look back and reflect, in our next article, we’ll take a look forward and see what surprises 2020 has in store. Data Trends Then and Now Still reeling from the financial crisis of 2008-2009, budget concerns were top of mind for many. The takeaway? Plan, and be flexible.  Other trends which began in 2010 still exist today, but the vocabulary has changed. And there are further changes still which impact our technologies today and in ways we may not have realized. Train and Retrain becomes Upskill and Reskill. In 2010, organisations were advised to train, and cross train their staff. Not much has changed in ten years as it’s just as important now. Only the vocabulary has changed. Now it’s upskill and reskill those employees with the skill and inclination to pivot into more Data-centric roles within your company.Colocation Concerns Give Rise to the Cloud. Astronomical real estate costs for Data centre space and colocation prices drove businesses to find another way to store and manage their Data. As Cloud Computing spread, it allowed companies to avoid costly IT infrastructures. Not only did this save money, but it also gave businesses the flexibility they needed. In addition to the benefits of enterprise level organisations, cloud computing levels the playing field for smaller businesses to get in on the game.Virtual in the Palm of Your Hand. Smartphones and apps offer project management of our businesses and personal lives from “what’s for dinner?” to “let’s schedule our next meeting.” Our smartphones are a one-stop shop for phone calls, text messages, video conferences, scheduling, communication with remote teams, online banking, bill pay, and more.Eco-friendly is not an option, it’s an imperative. Carbon-emissions and reduction plans were already abuzz within companies. Today, Data has evolved from LEED green building certification to massive advances and predictions on the climate crisis. Standards are set.Blockchain finds friends in finance, and beyond. Though it debuted in 2008 in the finance industry, it was quickly snapped up in every industry from manufacturing to retail to shipping; any business requiring a more organised supply chain.  Rise of Automation and Artificial Intelligence (AI) offers benefits beyond basic tasks. While this evokes fears for many in the workforce, there are benefits which is what’s driving things forward. While this is intended to streamline processes and avoid health risks in dangerous places like factories, there is still some cause for concern. However, some studies suggest people are happy to allow computers to take on mundane, routine, and menial tasks, freeing humans to think more creatively.  Getting Social Goes Online. Though platforms like Facebook and MySpace (yeah, remember MySpace?) were already available in 2010, the plethora of platforms today was a glimmer in our smartphones’ eye. No longer relegated to youth culture, social media has become one of the most important ways for leaders and corporations to communicate with people.  The Information Age has morphed into the 'Data Decade', with improvements across Data and Analytics, AI, and Machine Learning just to name a few. It’s enhancements within these spectrums which allow Data professionals to search and sort more quickly to provide the most useful Insights for their enterprises.   It’s estimated that in the next couple of years, 90% of companies will list information as critical and Analytics as essential to their business strategy. If you’re interested in Marketing & Insights, Robots and Automation, Big Data and Digital or Web Analytics, 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. 

‘Tis The Season Of Data: Black Friday Is Here

‘Tis The Season Of Data: Black Friday Is Here

It’s that time of year again. Decorations are going up, the temperature is dropping daily, and the year’s biggest shopping weekend is upon us.  Black Friday and Cyber Monday may have started stateside, but they’re now a global phenomenon. This year, in the UK alone, shoppers are expended to spend £8.57 billion over the four-day weekend. But, for retailers, this mega-event means more than a cash injection. In the world of Data, insights gained from shopping and spending habits during this period can dictate their product and pricing strategies for the next twelve months.  So what is it, exactly, that we can stand to learn from the Black Friday weekend? THE GHOST OF BLACK FRIDAY PAST There are a few interesting takeaways from 2018’s Black Friday weekend that will likely impact what we see this year.  Firstly, and perhaps unsurprisingly given that it’s a few years since the event has become omnipresent, spending only increased about half as much as initially predicted. There are a number of reasons for this, but cynicism plays a central role. More and more, consumers are viewing Black Friday deals with an element of suspicion and questioning whether the discounts are as good as they’re promoted to be. This, combined with other major annual retail events, such as Amazon’s Prime Day, means that this weekend no longer has the clout it once did.  However, 2018 also saw marketers doing more to stand out against the competition. Many businesses have moved away from traditional in-your-face sales messaging and some are even limiting their Black Friday deals to subscribers and members. By taking this approach, their sales stand out from the mass market and can help maintain a level of exclusivity that could be jeopardised by excessive discounts. In addition to branding, marketers making the most of retargeting saw an even greater uplift in sale. Particularly when it came to the use of apps, those in the UK using retargeting saw a 50% larger revenue uplift than those who didn’t.  So, having reviewed last year’s Data; what should businesses be doing this year in order to stand out? GETTING BLACK FRIDAY-READY WITH DATA Businesses preparing for Black Friday need to take into account a number of considerations involving both Marketing and Pricing. For the latter, Data and Predictive Analytics play a huge role in determining what items should go on sale, and what their price should be.  Far from just being based on gut instinct or word-of-mouth, algorithms derived from Advanced Analytics inform Machine Learning models that determine what should be on sale, and for how much. These take into account not only how many of each discounted product need to be sold to produce the right ROI, but also what prices and sales should be for the rest of the year in order to make the sale financially viable.  In terms of Marketing, Deep Learning techniques can be used to accurately predict Customer Behaviour and purchases. These predictions can then reveal which customers are likely to spend the most over the weekend, and which are likely to make minimal purchases. Marketers can then, in the lead up to Black Friday, target relevant messaging to each audience whether it be “get all you Christmas shopping in our sale” or “treat yourself to a one-off item”. By carefully analysing the Data they have available and reviewing the successes and failures of their Black Friday events, businesses can generate greater customer loyalty and improve their sales year-round. If you’re looking to build out your Marketing Analytics team or take the next step in your career, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

MARKETING INSIGHT AND THE CUSTOMER FEEDBACK LOOP

Marketing Insight And The Customer Feedback Loop

As the holidays approach, Marketers are focusing more than ever on User Experience (UX). They’re not only looking at what kind of product customers might want or need but how will it look and feel to them? If a product doesn’t have what you need or doesn’t function as appealingly as others, what good is it? Key elements such as aesthetics, usability, and ‘feel’ are integral to the user experience. Because these elements come from such seemingly disparate departments as Marketing and Developers, it’s important to figure out how to come together for the ultimate UX. After all, if today’s buyers buy experiences over tangible products, then ensuring the experience is important to bridging the gap between customers, marketers, and developers. This, when done right, helps to build and retain customer relationships; the foundations upon which business is built. Design User Experience with M&D By bringing marketers and developers (M&D) together, you create the opportunity for innovation. But there are some key elements to consider when designing UX and it follows four stages. Do your research. Identify needs, spending patterns, buying behaviours, and historical data to determine what it is customers desire. Find out what they want or need and give it to them. This is the role of the marketer backed by development.Gather the data. Using multiple touch points across multiple sources and channels, find what works. What product offers usability and determine how design choices can help to create a seamless experience for your customer.Design your idea and create a prototype. Brainstorm your design. What are its product features, user interface, and aesthetics? Does it look user friendly? Would you pick it up off the shelf? Why? What is it about the product that makes you want to have it? What problems can it solve for you?Time to Test it. Is your product user friendly? What are its useful functions? How does it look? Feel? Incorporate feedback to improve its performance, function, or aesthetic. What does your test market say? Would they buy it? Why or why not? Bridging the Gap with collaboration We can forget sometimes, lost in our jargon and our buzzwords, that it’s the customer who we hope will benefit from our product or service. Yet, traditionally, marketers gathered customer preferences and drove sales, while developers designed products based on those preferences. However, the two departments were often siloed and creativity, usability, function, and aesthetics either got overshadowed or underrepresented to varying degrees. Enter customer feedback an integral point of reference for all parties involved. Customers are at the heart of user experience and it’s their feedback which can inform the user experience. What better marketing insights than those straight from the customer? Working with Marketers and Developers, customers provide a crucial component to helping marketers understand market dynamics. On the flip side, customer feedback can help mitigate risk or issues down the road by providing solutions and helping to resolve problems. the impact on Product Development By conducting user experience testing, marketers and developers can determine if a product is a good fit for customer needs. At the same time, they may identify issues to be resolved which can be learned of in real-time for a better user experience once the product is launched. Each has their role to play in designing the user experience and contributing to market insights for more informed business decisions.  These include: Marketers are part of the design experience from conception to inception. They are responsible for gathering the data to identify problem areas, working with Developers to create a product or service to solve a problem, and gathering data from the customer. Do they like this product? Why? What pain points does it serve? And how can it be made better or improved? Developers are the designers. They must take the information the marketers have collected and try to make the product into something functional and aesthetically-pleasing. Though they operate more at the back-end, they too much collaborate with customers to capture issues and solve problems. Developers test the products, making improvements as needed. Each stage a constant in UX design.Customers offer invaluable data and metrics through their feedback and reviews. The insights they contain as the end user about using the product, revealing its challenges, and suggesting room for improvement, make this three-part collaboration the final link in the chain between marketers, developers, and customers when it comes to designing the ultimate user experience. If you’re interested in the relationship between insights and UX, we may have a role for you. Check out our current opportunities or get in touch with one of our expert consultants to learn more. 

Integrate Your Data And Business Strategies For Success

Why You Need To Integrate Your Data and Business Strategies

United we stand, together we fall. Not too put too fine a point to it, but how your business and data strategies align are integral to your business. Today’s world is about change, being able to pivot toward new strategies, and being open to trying new things. Consider this: the “mom-and-pop” shop is back and it is flourishing. Younger generations of farmers are returning to their family farms when they graduate and they’re bringing new knowledge with them. And the makerspace, freelance, and gig economies are thriving. These businesses are learning how to work with technology and align their Data Strategy with their Business strategy. Some legacy enterprises are taking notice. Others are missing the mark. Consumers may have changed how they want to shop and learn about services and products, but the services they want and expect haven’t changed that much which is why it’s more important than ever to “know your customer.”  3 Key Elements of Integrated Strategies While there are a number of things to take into consideration as you align your strategies, these three key elements can help get you started. 1. Understand the key elements of Business Strategy. 2. Apply innovation strategy to business objectives. 3. Determine key elements of your Data Strategy for use in a real-world scenario. Understand the key elements of business strategy  A business strategy encapsulates two main ideas; cost advantage versus competition. The cost advantage includes costs and other resources, identification and awareness of strengths, weaknesses, and competition. Competitive advantage happens when you’ve done your market research and can show what makes you different from any other provider with similar goods and services. This is the time you might perform a SWOT (strengths, weaknesses, opportunity, and threat) analysis of your business. It’s helpful to include your mission and vision statements, objectives, core values, risk tolerance, and understanding trends in your business. Apply Innovation Strategy to Business Objectives Ideas and innovation flow when you and your business understand your customers and are able to easily shift into new things. Think R&D into Bioinformatics, automated tasks into AI, or a platform such as streaming services to help sell services such as insurance. Laying the groundwork to apply innovation strategies to your business objectives follow these ideas: Identify your business objectives by asking questions.Assess the budget and personnel resources and develop a budget strategy.Test the market to determine what issues will or need to be solved and understand how this innovation will benefit your overall strategy. If you’re working on a Data initiative to integrate into your Business strategy, one of the key elements is to determine how those changes may affect your business. Determine Key Elements of Data Strategy for Use in Real-World Scenarios As you work on developing your Data Strategy, it’s important to consider all the elements required to ensure success. So, what do you need to take into consideration when working on this type of strategy? Here are some things to consider as you develop your framework. Determine your business needs and their current state.Determine what works and what can be improved upon if there is a technology improvement or process.Evaluate your Data from sales, profit, and evaluate your progress.}Develop an action plan. Many businesses don’t incorporate just one type of Data into their strategy. They consider the potential impact of technologies such as Machine Learning, Predictive and Data Analytics, and other Big Data Strategies to drive improvements when it comes to decision making. They understand these Data-driven insights can help them improve or solve their most critical problems. There is a caveat, however, and it is how you collect the information for real-world scenarios. Certain requirements are in place for a reason and they ensure only relevant Data is collected. This is done by formulating “predictive models” and necessary information to operate and determine whether your case will be something to be done over time or if it’s something brand new to consider when looking at real-time access. One Final Thought… Data-centric organisations have a distinct advantage over their competition. The information gained from collecting and analysing to understanding their customers can offer great insight as to what’s working and what isn’t. Integrating your Business Strategy with a Data Strategy can offer you a more well-rounded understanding of the customers you serve and can ultimately, help you to serve them better; now and in the future. Disruptive business models from this way of thinking can also foster growth and lead to innovative changes in your marketplace. If you want to be at the forefront of change we may have a role or candidate for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.

Data Storytelling Vs Data Visualisation

Data Storytelling vs Data Visualisation

The demand for “unicorn” employees is growing. Those with humanities and communications skillsets are now in demand, alongside those who specialise in Computer Science, Data Science, and anything technology-related. So, what exactly is the world looking for today? Well, with the plethora of online learning opportunities available, the ramping up of technology courses both online and offline, and a cadre of storytelling books on the shelves; answering the question can seem daunting. But there are two ways in which you tell your story. They’re not separate exactly, but they do have their own parts to play. What is Data Storytelling? In a nutshell, it’s the ability to tell a story using the Data you’ve collected and analysed. So, how does this work exactly, and why would someone use it? This way to explain what’s happening the Data to stakeholders and executives helps paint a picture of their company in a different way. And unlike traditional storytelling, this type has facts and figures to back it up. But that’s only half the story. By taking a wider view of Data storytelling, you can provide stakeholders with the big picture in a way that’s relevant and engaging. But you still need the Data to back it up. This is where Data Visualisation comes in. Think of it as the Graphic Novel of your business’s story. Content is the narrative and images are the visual behind the narrative cementing the story in your mind. What is Data Visualisation? This is how you define your story, and you can do this in a variety of ways. You can use Data Visualisation software to help guide your story and keep you on track in the details. Seeing is believing and can help persuade a call-to-action from decision makers. In a nutshell, Data Visualisation enhances storytelling using traditional techniques such as a “hook”, and embodies the basic structure of beginning, middle, and end. And while those in the marketing world know how to draw emotion and get people to act on it, Data Storytelling provides a new, useful skill for Analysts. What are the Elements of a Good Story? First, understand the story you’re telling. While visualising the results happens at the end to cement the story you’re telling, the heavy lifting is done in Data preparation. It’s not unlike baking a cake; you spend more time buying (collecting/gathering) the ingredients, mixing them, and organising (which pan, how long, and at what temperature), than you do baking the cake. The end result is the smell of something freshly baked, that looks amazing (visualisation), and tastes phenomenal – where the story and the visuals come together. Second, identify the main characters; your Data elements. You need ask yourself what is the relationship between your characters (Data elements) and was is their role in the story. This can help you bring together two disparate Datasets. Ask yourself, what tools would you need to make things work together? This is the preparation side of things. Once this is sorted, you have the elements of your story.  Keys to Good Data Storytelling Choose the right subject Source credible DataCraft an interesting, engaging, or enlightening narrativeEnsure your story provides meaning and valueEnsure you’re using credible Data to back up your story.Blend narrative and visuals which can cement the information and make your story stick.Choose relevant, useful topics for a more engaging story. You want your listeners to resonate with what they’re hearing or seeing. When people are engaged, this is where the emotion comes in. Stories come from a variety of sources, but are essentially either internal (you or your organisation) or external (trade publications or industry leaders). For content marketing, external sources offer a variety of ideas to tailor your story around. But what best will resonate with your audience is your internal story. Those tailored to pain points or interests are particularly valuable.  Remember that Data storytelling is not a story about numbers; it’s about humans and how those numbers affect them.  If you’re interested in Data Storytelling and Visualisation, we may have a role for you. Take a look at our current vacancies or get in touch with one of our expert consultants to find out more. 

Data & Berlin: Looking To 2020

Data & Berlin: Looking to 2020

Following our recent Data & Analytics meet-up at our new Berlin offices, I’ve been reflecting on some recurring challenges faced in our industry. A number of our speakers all touched on the same topics and, having looked around, it seems they aren’t the only ones who are concerned about staying ahead of the curve.  In a market of constantly shifting priorities and 2020 just around the corner, I’ve highlighted some of the main themes that keep coming up, and are worth bearing in mind as you begin to look at your Data & hiring strategies for next year: Retention Retention remains a highly important issue for businesses, as covered here, and we heard a number of insightful talks on the topic at our event. In particular, both the optimisation of workloads and the essence of customer centricity and autonomous teams were highlighted as key issues. Both providing interesting approaches to ensuring your workforce remains engaged and happy and  we will be releasing further information on these talks soon so, if you missed the event, watch this space or sign up to our mailing list to keep up to date. Cyber Security Following a number of high-profile data leaks (including the sensitive data belonging to hundreds of German politicians, celebrities and public figures less than one year ago), security really is at the forefront of everyone’s minds. Integrating Security into the DevOps cycle is becoming more and more popular as businesses increase their security and reliability alongside their speed of deployment. If you're interested in knowing more, the Puppet “State of DevOps Report 2019,” is well worth a read. Analysing Data How we analyse and use Data as a business is becoming more and more important as enterprises look to stay at the forefront of their fields and remain relevant in this Data-centric world. With so many different technologies and techniques used to quickly process & analyse data, Data Science, Machine Learning & Business Intelligence professionals are becoming more and more sought after. Recruiting & onboarding The recruitment and retention of staff is frequently the most important thing on the agenda of many businesses, not just in Data. Making sure your recruitment process in a candidate-led market is as streamlined and relevant as possible is something that should be a priority for any expanding business. From my experience, many companies write up their process, then stick with it for years and, whilst this can create consistency, in such a fast-paced and evolving industry is this necessarily the right thing to do? Here's one of my colleagues on attracting the right candidates and I also intend to put together my own article on creating an effective Recruitment Process for your business next week.  If you’re looking for support with your Data Science hiring process, get in touch with one of our expert consultants and we'll able to advise you on the best way forward. 

The Next Generation Of French Web Analysts

The Next Generation Of French Web Analysts

The role and purpose of Web Analysts has evolved over the last few years, and now there are a number of different types of candidate profile across the French marketplace. Whilst, traditionally, Web Analysts focused on Data pulled from websites before using their findings to make business recommendations on how to improve the site and streamline user experience.  However, as, digital channels, including apps, social media and mobile devices have multiplied, the amount of Data available to gather insights from has increased dramatically. Web Analytics has become Digital Analytics as a result of the need to quantify and better understand customer behaviour regardless of the channel or device used.  Across the world’s leading technology hubs, the role of the Digital Analyst is no longer to just relay insights from a company’s website, but to analyse different Data sources, work with complex technologies and tell stories with their findings. We’re now seeing the same evolution take place across the French market.  Today's Web Analysts  Throughout the era of digital measurement and optimisation tools, the use of AB tests and MVT tests has allowed Web Analysts to trial different online solutions for their enterprises. Nevertheless, until recently, these have remained centred on only one channel; the website. Over recent years, however, new categories of Analytics have now emerged, all of which need to be viewed as equally important:  In-store Analytics: The measurement of physical store Data, a real-world equivalent of web analytics. Mobile Analytics: The analysis of users’ traffic and behaviour on mobile sites and applications. Social Analytics: The analysis of Data from social networks such as Facebook, Instagram or Twitter.  As a result of this diversification, businesses are now not only looking for technical Web Analysts who can work with Google Analytics or Adobe Analytics and implement tags with GTM or DTM. There is now an appetite to go further and deeper with their analysis and Web Analysts who can use tools such as Big Query/ SQL, R or Python are high in-demand. A candidate with ‘Data Web’ vision, a strong knowledge of Data and KPIs in different business models, stands out amongst ever-increasing competition.  Furthermore, as Web Analysts use a lot of Data, particularly personal Data, a strong knowledge of GDPR and the legal implications of their work are also incredibly beneficial.  In other words, Web Analysts are becoming more versatile. No longer siloed to their own space, Web Analysts should have experience of collaborating with marketing and technical teams, as well as to top management and senior stakeholders.  Tomorrow's Web Analytics With this progression of Analytics tools and skillsets, Digital Analysts are now playing a more important role in businesses than ever before.  As they continue to present new ways of interpreting and visualising Data, their impact on the bottom line is being felt more significantly than ever.   As a result, Web Analysts are now open to significantly more professional opportunities. Specifically, if they have a strong technical skillset and a business mindset, they can move into a Digital Business Analyst or Data Scientist position. This means that the best candidates are in incredibly high-demand and businesses need to be sure of what skillset they need before beginning a recruitment process.  For example, a company recently going through a big change in tools migration, such as moving from Adobe to GA, would be in need of a strong technical Web Analyst who can implement those tools. A business that is further down the line with their capabilities, on the other hand, may be looking for a candidate with a real business vision, in additional to an analytical skillset, who can make informed business recommendations. Whilst the French market may be in transition, we’re already seeing these changes take place in other regions. In the UK, there is a large amount of conversation around ‘Digital Intelligence’, and Web Analysts are now beginning to be viewed as important as Data Scientists within many leading organisations, partially because these roles are overlapping more and more. In fact, the lack of appreciation for Web Analysts in France is a point of contention for many candidates, something that was discussed frequently at this year’s MeasureCamp Paris.  Businesses who are looking to hire, and retain, Web Analysts need to be aware of this mindset. Candidates often share their apprehensions around the lack of training offered within their companies, as well as concerns about investment in their area. As Web Analysts continue to upskill, enterprises need to make sure they continue to offer growth, opportunity and a good working environment, particularly if they are seeking domestic talent.  Whether you are looking to expend your Web Analytics function or take the next step in your career, we can help. Take a look at our latest opportunities or get in touch with one of our expect consultants to find out more. 

How AI Will Revolutionise CRM

How AI Will Revolutionise CRM

If we can be sure of anything in today’s business climate, it is that new trends will emerge and disrupt, new technologies will continue to be developed and attract hype, and companies will be left to navigate a landscape of opportunity and uncertainty. Customer Relationship Management is an upright concept or strategy to solidify relations with customers whilst at the same time reducing cost and enhancing productivity and profitability in business. CRM systems provide a well-defined platform for all business units to interact with their customers and fulfil all their needs and demands in order to build long-term relationships. Every business unit has an emphasis on developing long-term relationships with customers in order to nurture their stability in today’s blooming market. Customer’s expectations are now not only limited to get best products and services, they also need a face-to-face business in which they want to receive exactly what they demand and in a quick time. New Look CRM CRM is vital for the success of any organisation that seeks to continuously build relationships and manage countless interactions with customers. Now CRM systems bring together customer Data from a multitude of different sources, delivering it to all customer-facing employees to provide a complete picture of each customer across all department Today, there is a ton of available information across many devices and platforms. Companies need a way to integrate this “Big Data” into their intelligent CRM that can produce predictive results. The Value of AI Artificial Intelligence (AI) CRM systems built on Machine Learning algorithms now have the ability to learn from past experience or historical Data. Having these insights at the disposal of any customer-facing employee (sales, support, marketing, etc.) empowers a business to build deeper relationships with its customers. As a result, integrating AI and Machine Learning with CRM can deliver more predictive and personalised customer information in all areas of your business. By predicting customer behaviour, companies can take personalised actions to avoid the use of invasive advertising and to provide material of real interest to each prospect. There is no question personalising communications to customers has become critical. Today’s buyers demand more than a “spray-and-pray” email blast. A recent McKinsey study found that personalisation can lift sales by 10% or more. The analysis also showed that by personalising just 20% of email content, open rates increased more than 40& on average. Reply rates also increased a whopping 112%. As a CRM stores all the information in one centralised place, this makes it a lot easier to analyse your performance as a whole. This helps businesses build a relationship with their customers that, in turn, creates loyalty and customer retention. Since customer loyalty and revenue are both qualities that affect a company's revenue, a strong CRM have a direct result in increased profits for a business.  Those that use Big Data & Analytics effectively show productivity rates and profitability that are higher than competitors and those that put Data at the centre of their marketing efforts improve their ROI by 15-20%.  AI and CRM AI is becoming an ever-present theme across a variety of industries, from healthcare and retail to software development and finance. CRM vendors are no different; over the past year, numerous CRM vendors have introduced AI components into their product offerings. AI will develop in parallel with user interactions using various touch points within CRM and evolve continuously to deliver more intelligent and personalised actions. Learning critical patterns will also enable AI-infused CRM to automate certain actions, decrease the manual work required, and empower sales and marketing professionals to work more efficiently and effectively. The inefficient processes that hinder CRM will no longer be acceptable, and AI-powered automation will play a much bigger role in streamlining workflows. The rise of AI presents businesses with a wide array of unique benefits and opportunities. It can empower them to provide better, more relevant experiences to their customers and forge bonds with them in a way that was simply not possible before.  It’s estimated that 85% of businesses will start implementing AI solutions for their CRM by 2020. It seems inevitable that with further advancements, AI will move from a novelty tool to a must-have feature and dire necessity of every business. If you’re looking for to build a team of CRM experts, or to take the next step in your career, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

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