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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.

Liam Wilson

Liam Wilson

14. November 2019

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. 

Richard Jones

Richard Jones

07. November 2019

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. 

David Webb

David Webb

23. October 2019

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. 

Cindy Walusiak

Cindy Walusiak

10. October 2019

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