Recently I’ve been speaking to a number of data scientists about the challenges of adding value to companies. This isn’t an argument that data science doesn’t have positive ROI, but that there needs to be an understanding of the ‘team sport’ and organisational maturity to take advantage of these skills.
The biggest anti-pattern I’ve experienced personally as an individual contributor has been a lack of ‘leadership’ for data science. I’ve seen organisations without the budgetary support, the right champions or clear alignment of data science with their organisational goals. These are some of the anti-patterns I’ve seen, it’s non-exhaustive so I provide it.
The follow is an opinionated list of some of the anti-patterns.
- I’ve written before about data strategy. I still think this is one of the things that’s most lacking in organisations. I think a welcome distinction is that data collection which needs to happen before data analysis, and that this needs to happen in accordance with the strategy of the company.
Solution: Organisations should map their data science projects to the key business concerns of the organisation. This will help shape how resources are allocated.
- There needs to be an understanding of what kind of leadership you need for a data science team. This needs to be someone with hands-on experience of doing data science. This is not someone familiar with ‘analytics’ or ‘reporting systems’ and ‘delivery’. It is someone familiar with things like ‘probabilistic programming’, ‘neural networks’ and ‘A/B tests’. So don’t put an ‘analytics leader’ in charge of a team of data scientists.
Solution: Executives – feel free to reach out to me to discuss data strategy, I’ll gladly point you in the right direction.
- You need Business intelligence not data science – there’s nothing wrong with reporting, or building analytics systems, but it’s not data science. Be honest about what your organisation needs.
Solution: Ask clarifying questions when interviewing about why the organisation needs data science versus other things.