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We recently had the opportunity to talk to Rachel Stuve, one of LinkedIn’s Top Voices in Data Science & Analytics, and a leading Director of Data teams. An expert in her field, Stuve has a wide breadth of experience. Having attended college in automotive-heavy Michigan, her first role was analysing the auto-industry at Chrysler. Shortly after she moved into local government, digitising and integrating their law enforcement processes before working on a state-wide Data-sharing initiative. Most recently, however, Stuve has been focusing her efforts in Healthcare. While it might seem to many as a highly-specialised, inaccessible industry, Stuve disagrees. “It’s all about transferable skills,” she says. “You may be looking at different sets of Data with a healthcare provider but, essentially, the analysis follows the same principles”. Despite this, Stuve does admit that there are some hurdles to overcome, particularly when it comes to terminology. “Admittedly the jargon does take some getting used to, and there is a lot of it.” But the main differences are less scientific and more to do with infrastructure. Unlike like many Data-led industries, Health Insurers do not deliver directly to consumers. In fact, their main relationship is with Healthcare Providers. “It’s not the same as getting a mortgage, you don’t approach your insurer to be provided with care. Your direct service is with the Healthcare provider, the hospital, or whoever, and it’s the insurer’s job to cover the payments. Part of the challenge is working out which providers offer the best value for money and, also, which ones offer quality care”. This means managing a team comprised of both Data Scientists and Epidemiologist, specialists who can better identify which treatments provide the most success, at the lowest cost. So, how can you get a team with different backgrounds and approaches to work in harmony with one another? “So much of a project’s success relies on agreeing to the right goals at the start. If you can get everyone to agree on what success looks like, be it a 10, 20% profit increase or whatever, you know you’re all working towards the same thing. Sure, you may have some debate around statistical conversations, but ultimately you’re all pulling in the same direction. "Stuve also stresses the importance of including the right people at the right stage of each project. Too often end-users are not included in the early stages of Data projects, leading to huge gaps in knowledge. Stuve notes: “If those who have true knowledge of what they need from a project are left out of the initial scoping, things will almost certainly be missed” In addition to her work in Healthcare, Stuve also invests in female-led start-ups with her work at Golden Seeds, something that is close to her heart. “I love Golden Seeds. There have been numerous studies that show that female-run businesses produce higher returns, and yet they only receive a fraction of the investment that male-led businesses do.” She points to a recent article in the Harvard Business Review as to why this may be. According to the article, there is an inherent gender bias in the investment process where male entrepreneurs are asked about the potential of their businesses. Female entrepreneurs, on the other hand, were more likely to be asked purely risk-mitigating questions. “People invest in optimism, so if you aren’t allowing an entrepreneur to sell you the dream, you’re far less likely to invest in them”. Stuve also believes that there’s a perception that female-led businesses are less likely to be innovative: “I want to change the idea that these businesses are, for want of a better word, ‘girly’ and purely focused on clothes, food and retail. This is not the case from what I’ve seen, and women are at the forefront of all sorts of industries from biotech, to energy, to any number of specialisms”. So, what does she look for when investing? “Sure I’m looking for an innovative idea that fulfils a business need, but I’m also looking to invest in the person. Are they realistic? Are they are strong leader? Do they know their own weaknesses and have they built up a team around them who can pick up where they’re not as strong?” “There’s also, unfortunately, a double-standard when it comes to the perception of male and female leaders. This means how they carry themselves makes a big difference, particularly if they’re looking for further investment in the future.” Stuve is well aware of the difficulties women face in male-dominated industries, having found herself as the sole female in many of her teams, increasingly so as she progressed into management. Fortunately, she sees light at the end of the tunnel: “Companies are beginning to see the value in broadening the diversity of their teams and there’s definitely been a shift in the corporate conversation around this.” “Also, if you look for it, there is a fantastic network of women in Data out there. Reaching out tends to have this snowballing effect as well. You connect with one person, who introduces you to another, who introduces you to another, and soon you discover this amazing community of exceptional women”. If you’d like to hear more from Rachel, you can follow her LinkedIn for regular updates and ideas. For more information on the current states of Diversity in Data & Analytics, you can download our report on the subject here. If you’re looking to build out your team or for a new opportunity, you can get in touch with one of our expert consultants or view our latest opportunities here.
25. March 2020
Having a Data Strategy Plan for your business is no longer a nice-to-have. It is a must have, and in most circles is mission-critical to success. Where terms used to be fused (e.g. AdTech, MarTech, FinTech, etc.), infrastructures are now merging to create better and more powerful opportunities to better serve business and the day-to-day tasks of our personal lives. Data continues to change the landscape of our world and, as we look forward to the future, this shows no sign of slowing. Here are some of the biggest trends shaping Data Analytics right now: A Smart World: IoT, Conversational Analytics, and NLP It’s estimated that by 2020, there will be around 30 billion IoT connected devices. Think beyond smart houses and smart cars to video doorbells, smart refrigerators and toasters, setting your thermostat by remote and beyond. As this cadence of progress marches forward, IoT will no longer be a hardware challenge, but a data challenge. And according to a Gartner report on Data Analytics trends, it’s estimated 50 percent of analytical queries will be generated via search, voice, or NLP by 2020. Will this make Data Analytics more approachable for the everyman? Augmented Analytics Is Augmented Analytics poised to be the next big thing? With a market valued at US$8.4 billion just a couple of years ago, it’s estimated to grow to US$22.4 billion by 2025. Using Machine Learning and NLP to automate Data preparation for sharing, Augmented Analytics could redefine the way we approach our Data. Cloud Continues to Come of Age Cloud IT infrastructure may already be mainstream, but with spending expected to reach US$82.9 billion by 2022, and with over half all software, services, and technology expected to connect to the Cloud in the same timeframe, expect the conversation around the Cloud to keep growing. Data Science Roles Evolve into Specialties Frequently, the term Data Scientist is used to refer to anything to do with Data. From gathering and collecting to developing metrics and offering Data insights and forecasting. But as Data teams became less siloed and IT infrastructures became more specialised, the role has evolved into more specific functions, often with a Machine Learning or NLP focus. However, this evolution didn’t stop at these specifics. It’s even made room for those with no programming background. From Marketing Analysts who focus on the customer journey to Business Analysts and Communications Directors who can utilize their soft skills to explain Data professionals’ findings. Whether you’ve got a programming background or an interest in how Data fuels business, the world of Data has opened up. Have we reached the end of the beginning? As we find ourselves on the cusp of the next generation of Data & Analytics in both our personal and professional lives, we spoke to Daniel Levine, Trends Expert and Keynote Speaker to gather his thoughts. Here’s what he had to say: "The biggest overall trend I'm seeing for Data in the coming decade is all about ownership, transparency, privacy, and governance. Data famously wants to be free, but the opposite has happened as companies across the industrial spectrum have scooped it up and siloed it away. The 2020s will create unprecedented amounts of Data from biometric recognition, deep learning, digital streaming, smart appliances and more. And ownership will be shared with -- if not controlled by -- individuals rather than governments and corporations. Blockchain will play a pivotal role in this, offering individuals the ability to safely take control of their own Data. Many governments, led by the liberal democracies of Europe, will enact legislation that aligns with new realities and new technologies that empower both institutions and individuals to understand and control their own Data. The frightening alternative that, when it comes to Big Data, we have reached the end of the beginning whereby a totalitarian dystopian future is nigh." If you’re interested in Big Data & 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.
26. February 2020