To address this challenge, many businesses are opting to partner with external organisations that can fill this skills gap. By doing so, they gain access to expertise that helps them unravel the true narrative hidden within their data, and generate valuable insights that drive tangible outcomes – all without the burden of sourcing and training new talent.
However, selecting the right data analytics service provider requires careful consideration and thoughtful deliberation. With a multitude of agencies in the market, it is crucial to strategically evaluate various factors to ensure a mutually beneficial partnership that aligns with your business needs and supports your goals, both now and in the future.
In this blog, we will explore 5 of the key factors that you need to consider when choosing a data analytics service provider.
Let’s get to it.
#1 Assessing Internal Capabilities
On your journey to identifying the right data analytics partner for your business, the absolute first thing you need to do is assess your internal capabilities. This starting point allows you to identify what, if any, capabilities you can manage internally, and therefore specifically which areas you need to outsource. Ask yourself what talent, tools and technology exists within your current team and infrastructure, and whether current bandwidth permits your team to fulfil any of your businesses data needs.
This will help direct you towards either finding an end-to-end agency whose capabilities span a wide area, or a specialist agency who can simply bolster your internal skillset.
#2 Services Offered
Once you have established the level of support you need from an external agency, you can then match these requirements to the service offering of each agency.
Collate a list of agencies that are in the line-up and work through your checklist of technical and analytical capabilities you’re specifically looking for from an agency. This will help you to identify the agencies whose offering aligns with your needs vs the agencies whose specialism and services aren’t well-matched.
Whilst it can be easy to simply consider your current requirements, it’s imperative that you also consider what type of support you may need in the future, so you can opt for an agency that can provide long-term support.
#3 Expertise and Experience
Now that you have established the breadth of services provided from each agency, and disregarded those that are not closely aligned to your requirements, you need to consider the extent of experience and expertise they can provide for each area within their service offering. For example, an agency may claim that they have experience in AI and building predictive forecasting models, but to what extent?
Are they well equipped with the right expertise internally to give you full confidence in their ability to perform? And, what case studies, testimonials and demos can each agency provide to back this up?
Industry experience is also a critical factor to consider here. Does their experience specifically relate to your industry, demonstrating that they can not only deliver on the project, but can also provide an in-depth understanding of the meaning behind your data and as well as context behind the insights?
Similarly, you should consider their level of experience with companies that are similar in size and scale to your own. Do they usually partner with smaller scale businesses, or are they well-versed in working with larger scale organisations and can therefore appreciate the complexity of internal processes and varying requirements of stakeholders that sit across the business.
After all, the partnership will look vastly different with a smaller company vs a larger global company with numerous project streams and vested stakeholders.
#4 Analytical Capabilities
Effective data analytics relies on advanced analytical capabilities, and it’s important that the analytical capabilities of the data service provider match your analytical requirements. It’s therefore imperative that you assess the provider’s proficiency in certain areas of analytics, such as:
- Statistical analysis
- Data modelling
- Visualisation tools
- Cloud infrastructure
- Data mining
- Machine learning and AI
- Advanced analytics
Whilst you need to evaluate their core skills, the agency’s analytical capabilities should span far beyond basic reporting.
Can they provide sophisticated insights, spot patterns and trends in your data and provide business and industry context to further aid strategic decision-making?
Further to this, you needed to establish each service provider’s level of technical capabilities. This exceeds standard analytics, as it’s their ability to build and maintain the infrastructure that sits behind your data.
#5 Tools and Technology
Another key consideration is the tools and technology that the agency uses for data analytics. They should be proficient in working with the latest data analytics software, programming languages, machine learning frameworks, and visualisation tools. Are they ahead of the curve when it comes to new technologies within the data and analytics industry?
It’s also essential to ensure their platform expertise is compatible and aligns with the tech stack you’re already using internally. For example, if your organisation currently uses Microsoft products, and are now in need of a business intelligence solution, then Microsoft Power BI is probably the most suitable tool for you to use. Selecting an agency who only specialise in Tableau may not be the optimal match in this case. You also need to take into account any pre-established preferences you have regarding software stacks in order to identify if this aligns with the agency’s software capabilities.
So, there we have it, 5 key areas you need to consider when assessing which data analytics service provider is right for you and your organisation. However, this is just scratching the surface – choosing a data analytics service provider is no small feat, and so there are many more factors you need to consider when searching for the right agency to meet your challenges and build a long-term partnership with.
We have created an in-depth guide outlining the main 12 considerations – think of it as the core criteria you should be using to guide you on your search.