Data has become the most precious resource for businesses. The problem is that most companies don’t know how to turn data from an asset into an advantage. While we celebrate innovative companies like Netflix for their mastery of data analysis to benefit their business, the reality is that the vast majority of big data projects -- a staggering 85% -- fail.
How can you ensure your company bucks the trend? It starts with assembling the right team and creating the right environment for their success. Here are a few suggestions to consider as you begin pursuing big data initiatives.
Start Small
I currently lead a team responsible for customer analytics and artificial intelligence. When we started our division five years ago, you could count the number of people on the team on one hand. Today, our team is almost 40-strong and features a mix of data scientists and DevOps, data, quality assurance (QA) and software engineers. While a bigger team enables us to make a much greater impact, it is difficult to start with that many people.
Having a big team from the get-go increases the probability of runaway scope, especially if key stakeholders aren’t aligned on priorities. When you over-scope, you run this risk of delaying the entire project and the crucial first wins. Going too big too soon can sink your project before it even gets off the ground. So, aim to start small and expand your team strategically over time.
Narrow Your Focus
Focus makes or breaks a big data project. According to Dr. Thomas “the Data Doc” Redman: “The worst mistake a company can make is to hire a cadre of smart data scientists, provide them with access to the data and turn them loose, expecting them to come up with something brilliant. Lacking focus and support, most fail.”
So many companies fall into the trap of thinking they can leverage big data analytics to immediately solve all of their problems. Going broad in your approach can overwhelm your team and significantly delay results. On the other hand, having a laser-focus on something like saving money gives your team a true North Star. With a clear focus, it becomes easier to prioritize initiatives that are likely to drive success.
For example, if your objective is to reduce wasteful spending, you could start by identifying inefficiencies in your organization’s largest expenditures. For an e-commerce retailer, it is often more costly to process returns than to ship items. A big data team could uncover contributing factors to customer returns and help reduce logistics costs by providing data-driven recommendations based on customers’ previous purchases and returns. Specific, measurable goals are key to helping your team deliver a meaningful impact with big data.
Create A Shared Definition Of Success
In order to increase headcount on my team in the early days, I needed to demonstrate that our work was adding value to the business. That meant focusing on projects that aligned with our executive team’s top business priorities -- generating incremental revenue and enhancing the customer experience.
As an overarching principle, I would advise big data teams to take this same approach. Adding value to the business can mean different things to different companies, so it’s critical to get aligned before you start any project. For example, if your company is focused on cost-cutting, you are unlikely to be successful if your big data program is finding and reporting on growth opportunities. Getting value-aligned wins is important. Wins will not only energize your team but also buy you support from key stakeholders to expand your scope of work and dedicate more resources to your efforts.
In today’s data-driven economy, companies that are capable of extracting value from their data enjoy a competitive advantage. Big data holds incredible promise to solve so many problems -- just make sure to focus on the valuable ones.
