What would you think about a business that gave away its intellectual property, products or services to third parties? Altruistic? Charitable? How about a business that gave all of this away without realizing it? Naive? Badly run? Downright crazy? Well, as odd as it may seem, many businesses are freely giving away one of their most valuable assets - data. This is the reality for organizations that rely entirely on outsourcing their data capabilities to third parties. They are, in effect, sharing a profound amount of company, product and customer information and, in return, paying for the privilege of understanding what it means. This may sound like a weird argument to make, after all, what is the harm in working with another company to plug a skills gap or services? However, this is not what is happening in many organizations. There is a colossal difference between using a data company to enhance your understanding of your data, and completely farming out your capability to be a data led business. Relying entirely on another business for your management, maintenance and analysis of data is at best expensive and, at worst, incredibly risky. How this situation arises has a lot to do with misconceptions around data and data science. Rectifying the problem requires a mindset change and a business committing to better education and training of its staff.
Let’s start by looking at some of the misconceptions around data. First, many businesses often have difficulty getting their head around exactly what information they currently hold or could collect. They are essentially limiting themselves from the outset because if you don’t know what you have you can’t possibly know what you could do with it.
Next, there is limited understanding of what insights can be derived from data. Often, businesses only look at data as a tool to enhance functions such as marketing by helping them to identify their customers. However, it is so much more. Good data science can enhance nearly every aspect of an organization. In respect to marketing, real data science doesn’t just identify your customers it helps you create new ones, retain your current base, and maximize value. It can reshape product design, HR, business strategy and performance, procurement, logistics and so forth. Seeing data through the narrow lens of one business function or one or two potential benefits severely limits its potential and prevents your business from becoming data-driven. On that note, it's also worth remembering not all data is created equal. Without insight into how it could be applied, businesses can either end up hoovering up way too much data - which can damage the privacy of their customers putting their brand at risk and creates more work for them every time they look to gain insight - or they can leave a lot of valuable data points uncollected.
Finally, let's talk about costs. One of the biggest myths around data science is that it is expensive. This can lead to businesses either foregoing data science entirely, limiting their ambitions or outsourcing it to a third party for what they consider to be a low, fixed price. The reality is that the ROI for data science is often very clear and compelling. There is a long sliding scale of required expertise and work that can be undertaken which means that even an SME can afford to build some form of internal data capability. Importantly for any organization of any size it is not about how much you spend but how effectively you spend it, finding the right blend of spend of people, technology and external expert advice and support. I see companies spending £10 million a year on data getting less ROI than those spending £250k.
What unites all these misconceptions is education. Too many business leaders do not upskill or educate themselves on the basics of data and data science. This leads to an overreliance on third parties or those with the knowledge in your organization, or /and a failure to seize opportunities. By being an uninformed purchaser, you will always get a worse deal. By understanding how data science works, how it can be applied and what expertise is required, a much more thoughtful approach to making your business data-led can be taken. And becoming data driven should be the goal of nearly every business. This means using data to inform every decision across every function of the business. It necessitates a cultural shift from seeing data science as a tool to supplement some processes to understanding that it is core to your entire team's day-to-day jobs. Naturally, this is impossible if you completely outsource your data capabilities.
Achieving full value from your data can not stop at a business educating its leaders. The ambition should be to grow your own capabilities. This doesn’t just mean hiring some data scientists, it involves committing to business-wide upskilling or in some cases retraining to provide every staff member with the understanding and skills they need to use data to maximize how they do their job. All of this needs to be underpinned by new processes and policies that embed data expertise and empower your team to use data creatively. It may mean some upfront costs related to creating architecture and infrastructure which enable data to be collected, stored and managed in an efficient and open way, however, the benefits of this very quickly outweigh the costs. Again, there is also a sliding scale of infrastructure packages available which makes it an affordable option for smaller businesses. As a brief sidenote, it’s important to remember that tech infrastructure shouldn’t just take into account your current needs, flexibility is a critical factor to enable it to adapt as your business scales. It is always worth consulting data experts to identify your options before committing.
The benefits of creating your own in house data expertise and skills also opens the door to some serious innovation. This is where third parties come back into the picture in a big way. Using outside experts with strategic precision can enable the execution of cutting edge projects, experimentation with new techniques, bespoke team upskilling and much more. The key is the collaboration between your internal team, who will now have the knowledge of their exact requirements, possible applications of data and a better understanding of areas in which they want to innovate, and the external experts who have the experience and skills to advise, build and execute the project. By working together these projects can be better defined, tested and refined. The result is much more efficient and cost-effective innovation - more importantly it lives on in application in the business long after the ‘project’ is over.
Marathon, not a spring
Embarking on the journey to become data led can seem daunting for a lot of businesses. However, with any big project it’s best to take an incremental approach. I would recommend beginning with educating your leadership. This will provide the base needed to better understand the right approach for your business. Do not just pull the plug on your third party. Collaborate with them. They will be best placed to work with you to achieve your goals. Believe me, any data science company worth their salt would jump at the chance to support you on this journey. After education comes the graft of auditing your existing data, expertise and infrastructure. It can be time consuming, but as I’ve outlined, it’s well worth the effort - again external experts can help get you going on this. When these building blocks are in place you can develop a roadmap for your team, identifying the talent you need to recruit externally and those within the business you can start to upskill or retrain. To minimize costs and risk you can start by piloting upskilling with specific departments and then assess the impact before rolling it out across your business. Remember becoming data-led is a marathon not a sprint. It will be the bedrock on which your business stays competitive for decades to come. It’s worth taking your time to make it happen.
Natalie Cramp, CEO, Profusion