Which comes first, the data or the data science team? The value of data is fairly incontrovertible today and businesses have increasingly large volumes to contend with. Deriving value from your data is a job that requires expertise and specialist resources – it’s an investment worth making but when, and how, do you make it and what can you do if you already have an in-house data science team that simply isn’t delivering?
Building, or enhancing, your data science team
Data is a golden key, opening up your business to improvements in operational performance, creating a competitive edge and making more of an impact. Having a strong team makes all the difference when it comes to ensuring that investments you make in data will actually deliver. For many organisations this is going to mean a balance of internal and external support. However, whether you’re building an entire team internally from the ground up, working exclusively with consultants, or balancing the two, you’ll need to have a solid basis for your approach.
Focus on the problems, not the platform
Before you start making investments in technology, or hiring people, look at what your business needs, and is hoping to achieve, with the resources that are going to be directed at data. This means identifying your objectives and also your strategic challenges. Look at where the business is right now and where all stakeholders would like it to be further down the line. Although it can be done retrospectively if necessary, this is a process that is more beneficial if completed before making investments in tech, such as analytics platforms.
Review the internal talent you already have
When you’re building a data science team it’s not just about transplanting external experts into your business. Sometimes, the best place to start is with those already employed who are close to your current issues. Who has the skills, aptitude and passion to make a contribution?
Where are the skills gaps?
When you review the team you’ve already built, or the expertise that is available internally to create a team, you’ll be able to start looking at the skills gaps that you need to fill. Identifying missing expertise may not be obvious if your business doesn’t have a wealth of experience with data – we don’t know what we don’t know after all. This is something a partner like Samuylov.ai can help with, offering experienced insight into where the hidden gaps might be.
Start with the low-hanging fruit
Once you’ve established a team you need to test it out, not just in terms of whether you have the right balance of expertise but also how well everyone works together. Begin with small, achievable tasks to build confidence and give everyone in the team the chance to start collaborating effectively.
Troubleshooting issues
If you have already invested in building a team in-house and you’re not seeing results then it’s time to review your approach. One of the biggest issues we tend to see is where data scientists have been blindly hired before a productive working environment has been established for them. This can result in deliverables that don’t meet expectations and a team that feels they have little, or no, opportunity to apply their skills. Demotivated data scientists may even begin to look elsewhere, which is a waste of investment and valuable people.
Where Samuylov.ai can help
We can support you in building a productive data science team or show you how to do more with the data scientists you’ve already hired. Our approach is bespoke, tailored to your business’ needs – among other things, we will:
- Help you focus on the skills you really need internally to make an investment in data productive and cost-effective.
- Identify missing expertise. Help you source, and hire, the right people.
- Provide insightful guidance on how to make improvements and establish a strategy to ensure effective growth of your AI/ML capabilities.
Just as the chicken vs egg conundrum is unanswerable there is no one-size-fits-all solution when it comes to building a data science team. The key is to know where you’re trying to go with your investment and, if you’re not sure how to get there, to partner with those who can help.
