Used effectively, data can help you make faster, better quality decisions. And better decisions of course mean happy customers, happy employees and commercial growth. But for all the talk of AI, ML and robotics being explored at digitally native players, many companies still can’t even get a consistent sales figure.
So how do you start? What do you need to do? What will it feel like when you get there?
Pete Williams is a self-confessed data evangelist, a true believer in the power that data as to transform businesses. In 2017 he was ranked number 6 on the renowned DataIQ top 100 list which profiles the most influential people in data-driven businesses.
Ahead of his session at BA Innovation & Tech Fest, Pete shares his thoughts on starting and maintaining a journey towards a data driven culture, and gives his personal reflections on data culture, data leadership and the future of data teams.
As well as a Data Evangelist, you’ve described yourself as a “medium level data geek”. How did you get into the data space and what does your data journey look like?
Yeah, it seems strange reading that back!
I was born into the generation that first experienced home computing through the Sinclair Spectrum and Commodore 64, and I would code and game for hours. When some years later I needed to make a career pivot when I realised what I was doing wouldn’t give me the life I wanted, I consciously chose to go back to those early passions. I went back to university and studied computer science. Unfortunately funds meant I could never finish my degree, I stopped at HND level in my mid twenties, but I’m pleased to say my life has been transformed in the direction I hoped by going back to university and back to my passion for data.
What I was getting at in the quote was that I have been more technical in my life, working at the code line and building datawarehouses. But I realised that what inspired me even more was the individual and organisational empowerment that comes from fact based decision making driven from data. So, I made another conscious choice to focus on bringing that opportunity to life for others rather than deepening my technical skills. That’s why I now call myself a Data Evangelist.
Yet, when given a dataset, my curiosity gets the better of me! I can’t resist peeking in, disassembling, profiling, understanding transformations. On my last engagement I stayed up way into the early hours when I stumbled across a dataset – it wasn’t my role to look at it, but it was there and my expertise on how it could be used was being sought. I did manage to find some data that posed some challenging questions on what we’d been given and it actually invalidated the dataset meaning a new extract was required.
Medium level means I too quickly reach the level where my technical capability constrains my data driven curiosity!
We’re thrilled you’ll be presenting at Business Analytics Innovation & Tech Fest later this year. Your session is titled “Don’t Get Left on the Bench When the Data Game Starts” and you’ll be giving us some practical tips on how to get started with data, what you need to focus on, and what’s irrelevant. What’s one lesson you hope people will walk away understanding?
I’m thrilled to have the opportunity to talk about data to a new audience, thank you.
It’s hard to boil down to one lesson. I guess what I really want people to know is that using your greatest asset – your data – is both vital to your survival and growth and an achievable outcome.
There’s so much hype around the data industry. Technology, capability and opportunities are evolving so quickly and a lot of the language sounds impenetrable. It might be tempting to avoid diving in. But you really must. However, where and how you might start is what I hope to offer attendees.
The benefits of cultivating a data-driven culture are extensive but many people have no idea the opportunities exist or are skeptical about the benefits. How do you best show your colleagues the power that data has?
I think this boils down to a lesson in change management. The answer is no different to offering a new delivery concept in logistics or a new machine to a manufacturer. It’s also the reason why I suggest not getting dragged too deep into a technology conversation when trying to sell an analytics programme. If you haven’t seen it, I suggest you take a look at the Simon Sinek video on “Start with Why”.
I advocate pull over push. In general you’re not selling analytics to an IT function, you’re selling it to commercial folk to give them deeper insight and competitive advantage. These people don’t care about your technology, they care about what it can do for them. So, you need to understand their ”Why?”. What are their frustrations? What question can’t they answer? What do they wish they knew? When do they need to know it? What would it mean to them if they could?
Your job is to distil this into a set of opportunities. Then frame your data proposal within these opportunities to solve a feasible problem they care about, is important to the business strategy and preferably under a sponsor who’ll advocate on your behalf when successful. They’ll pull you in, and others will embrace you too so their problems can be solved. Success feeds on itself, a data culture evolves quickly when people see the benefits and you ignite their curiosity on what else it could do.
My mantra…start small and be ready to scale quickly.
During our roundtable discussion groups earlier this year, we heard the need for organisations to address ‘data literacy’ as a skill. How important is it and how do we start building it?
This is the most vital cultural change your organisation needs to make to embed the use of data so it becomes the default way of working. It means your organisation will make better decisions, faster than before. It gives you the best opportunity for commercial survival and growth.
I’ll be presenting what I call the Data Literate Ecosystem which I believe is the nexus of the modern business. Taking advantage of data has to go beyond the technology, which can be a disproportionate focus as this is often what people are selling to you. It’s the human factors around the technology which will ultimately make you successful.
Business people need to know how to ask an analytical question that can be answered by their data insight teams. These questions can come from anywhere in the business. But it’s absolutely vital they do come from the CEO/Board to help set the strategic aims of the organisation as well as drive the tactical delivery of those strategies.
They should expect to receive or preferably self-serve data insight confidently and then quickly make decisions from that data. Organisations should be ensuring they have responsive, collaborative data and technology teams who also train their colleagues in relevant data concepts, visualisation and interpretation.
Everyone, from top to bottom, needs to be comfortable with the data that is available, know what they need for each decision, where to get it, and be confident in using it. The workforce will in general need to become more mathematically competent.
As an example of legacy behaviour, if you’re throttling real time data by cutting it from systems into PowerPoint decks and Excel sheets, passing it through management layers for “sign off”, presenting it to senior teams to maybe receive queries 3-4 weeks later then frankly, you’ve got it horribly wrong.
With all the talk about AI, robotics and machine learning, what do you think a modern BA team will look like if our reliance on artificial intelligence continues to increase?
What am interesting question, and one I have never been asked before.
All new technology, like all great science and knowledge, eventually becomes commoditised and distributed. In 1905, only one person knew the Theory of Relativity and now every 14 year old is taught it. Fifteen years ago, ecommerce analytics was a highly specialised skill, now it’s common place and so much of it can be achieved by machine. The same with social media analysis. The human differentiation an organisation can make is the local configuration and the “knowing what’s important”. However, repeated patterns of implementation have led to many vendors now offering solutions that take your data, understand what it is, tell you what you should be looking for inside it and suggest how to report it out. I don’t think it’s quite as easy as they say but it’s a potential step forwards…
Speed to insight is what every organisation should be seeking. Competitive advantage will be in the use of that insight to make a better decision, faster. The modern BA team will therefore need to be strategically aligned and commercially focused so they can understand the opportunities that exist within an organisation. They’ll need to be expert at training the organisation to work in a new way and evangelising the power of data driven insight. With more automated self service of insight, it’ll be their job to consider new data sources that might help join correlation with causation. Sourcing and ingesting this data will be therefore be in their role.
Over time, the organisation will evolve and automated decision making through AI will become more prevalent. It’ll be the BA team’s role to translate business rules into machine rules to train the algorithms to “think” in the organisational way. Being a guardian of the ethics of the organisations AI will be important, as will the performance management. You could see the future BA team as the HR department for AI, helping algorithms achieve their full potential for the organisation and exiting those that no longer add value. I can see a time when the most valuable and closely guarded employee in an organisation will be an effective, commercially astute algorithm.
You’re proudly associated with Datakind UK. Can you tell us a bit about what they do and how/why you got involved?
Datakind was founded by Jake Porway in New York. I saw him present the concept when he was a guest speaker at a conference in 2014. He presented data folk as super heroes, demonstrating the things they could know by bringing together disaggregated data at scale with modern technology and mixing it with human inspiration.
The resulting insight would have seemed like witchcraft – or super powers – in earlier times. Even in quite recent times (the 1990s) when one of the most famous data structures, Tesco Clubcard, was first presented the shocked response from the board came from Tesco’s then chairman Lord MacLaurin, who said, “What scares me about this is that you know more about my customers after three months than I know after 30 years.”.
So, play that capability forward. Commercial organisations have some of the largest but least variable data sets. They buy the deepest data skills and deploy them to solve similar problems and drive their own success. The third sector, charities, have some of the most varied and interesting datasets and challenges, and the issues they are trying to solve benefit people and society. They save and enhance lives. But they don’t have the processing power or the data skills to take advantage of what we can now do.
Pro Bono data science was Jake’s idea. Pose interesting data challenges to data folk at special datadive events and in so doing, help solve the world’s most pressing problems.
The concept excited my colleague and I so much we asked Jake if we could work in partnership and bring it in house to Marks & Spencer where we were working at the time. For organisations the benefits are significant and it fits so nicely into a skills-based volunteering programme and a corporate CSR agenda. To be honest, it had some philanthropic and some selfish benefits for me. I needed to mobilise a data community in an organisation that didn’t really get it. By working through a two day event, helping four charities and guided by Datakind, I effectively trained at scale 80 analysts on new technologies. I gave them problems to solve that paralleled commercial challenges. I created collaborative, cross functional teams that persisted back in the commercial world. I generated self esteem in people usually seen as Excel jockeys. And of course, we did some great work for four charities who didn’t have access to the data skills we provided – even winning an award with Macmillan.
I’m so proud of what we achieved and my relationship with Datakind UK has persisted to this day through what became an annual event and their most successful partnership of its kind.
About the Speaker
With over 20 years’ experience of business intelligence and transformational change leadership, Pete Williams is ranked amongst the top data people in the UK: ‘Power 10’ in The DataIQ Big Data Top 100 2017; ‘Data Titan’ in The DataIQ Big Data Top 100 2016; and Winner of the B2C Category in the Information Age Data Top 50 2016. Pete believes that better, faster decisions can be made in every situation by empowering decision makers with relevant data. He does this by designing an organisational strategy to bring together insight from marketing, digital engagement, dynamic customer insight and operational analytics to deliver high quality insight, machine learning and predictive analytics.