When it comes to casting a data team, it’s not just about finding the right people with data magician skills. To hit the jackpot you should strike a balance between your internal and external teams. Whether you are a seasoned data leader or just starting, this post is a must-read for everyone up-to this challenge.
None can argue with the fact that in today's business environment data has become a crucial asset for organizations - a gold mine that offers unique business opportunities. At the same time data leaders are increasingly grappling with the need to prioritize efficiency over speed and volume.
Besides recruiting the top data talents and casting a robust team, most companies have invested heavily in their data infrastructure in the last few years. CEOs and stakeholders now set expectations that require measurable results from the data teams. The good news is that data is among the best candidates in IT to provide solid and measurable ROI. However, the cost side of things is more under control nowadays. The challenge is to live up to the growing expectations of the business teams while keeping costs at bay.
If you want to pave the way for optimal performance, enable your organization to harness the power of data and stay ahead of competition, you should evaluate the added values of your internal data resources and external consultants and build a data team that relies on both.
By no means, the internal team is key to the success of data projects, as they have a much better organizational involvement and a better feel on the nuances of processes. Given that data is usually deemed to be a precious business asset, furthermore an important source of competitive advantage, it is rare that the whole data organization gets outsourced.
Infrastructure and SaaS spending shot up in the last few years, their toolset and usage is likely to be optimized. The internal data team can be asked to try and suggest ways to economize on SaaS and/or cloud spending. However, there is a good chance that they won’t be able to think “out of the box” due to the lack of their external perspective. Experts who are up-to-date with data-driven achievements in several sectors are usually more efficient in judging ideas and suggesting better ones.
No matter in which industry or sector your company plays in, it is inevitable to have Chief Data Officers or Heads of Data/Analytics to run the show. These guys steward the data movement and have a vision of the data strategy. Keep in mind that this role cannot be outsourced effectively (interim CDOs can be a band-aid fix to some situations, but far from ideal in the long term).
Data analysts are best to be organized within the business line/unit (eg. marketing, finance, etc.), in smaller organizations they are even shared between business functions. These analysts have a perfect understanding of the company’s business and also the data coming from the source systems that get calculated in the data warehouse. Thus, my advice is that most of these roles should be kept in-house, however in order to get some fresh perspective, I suggest augmenting data analysis with external experts.
When it comes to technical roles, it is crucial to keep up with the rapidly evolving technology landscape. However, we must face the fact that internal engineering teams are often stretched thin and lack the bandwidth to constantly explore new technologies or tools. Even if time is set aside for education, the pain points of the current tech stack can limit their ability to gain a comprehensive understanding of new technologies. Cutting-edge consultants are incentivized to stay on top of emerging trends and have the opportunity to work with diverse tech setups, providing them with a broader perspective.
Teaming up with a reputable data engineering consulting firm can yield several benefits that go beyond simply gaining new insights. Their expertise can be utilized to conduct an audit of your current cloud usage, leading to potential enhancements in the efficiency of the data processing operations. Fine-tuning system performance often requires a fresh set of eyes and an outside perspective. This evaluation, in turn, can result in substantial cost savings from the get-go, without compromising functionality.
While audits can be game-changing in the short-term, we shouldn’t overlook the long-term value of comprehensive team augmentation and knowledge transfer. Reliable data engineering partners will provide guidance to clients on strategy, technology selection, and best practices. Furthermore, they often possess a more flexible resource pool, enabling partners to handle workload spikes and address skill gaps for short-term needs. Unlike permanent team members, consultants can offer long-term stability and dependability, as they retain critical information that might have been missed when previous employees departed – making them even more committed than traditional staff, in a way.
Ultimately, a strong partnership with a consulting firm can lead to greater efficiency, stability, and success for organizations in the fast-paced world of data analytics, where employee fluctuation can be especially challenging.
Striking the right balance between internal and external resources will become an ongoing challenge, especially as data technology continues to evolve rapidly. Data leaders who can navigate this balance and build effective teams will be well-positioned to succeed in the data-driven future.
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