As data becomes an increasingly sought-after asset, data science for business is on organisations’ minds more than ever. While it may be tempting to build an in-house data science team like many large companies, this isn’t necessarily the best option for every business. It’s important to consider not only what’s feasible for the size of your organisation, but also the costs versus benefits, and what you actually want to get out of data science as a service.
A managed data science service could be the answer – outsourcing your data science function means you can simplify your data science, machine learning and AI needs. A modern managed service is flexible, and can be incorporated into your business in the way that works for you. This flexibility allows you to gain additional skills and expertise, without sacrificing control and ownership.
So why should you outsource your data science function? Here’s my top 6 reasons.
1. Data Scientists are in High Demand
It’s no secret that there is a high (and growing) demand for data scientists at the moment; data is on everyone’s minds. Along with this new challenge, there is the ever-present challenge of finding an individual suited to your organisation, with the skills and experience necessary to make the investment worthwhile. A managed data science service negates the need to hire a data scientist, whilst still having the benefits of data science insights.
2. Data Scientists are Expensive
Data scientists are expensive – and a new hire is always going to have a certain level of risk. This risk and cost can be greatly reduced by outsourcing your data science function, and could lead to potential savings with a higher value. Win-win!
3. Focus on Growing your Business
By outsourcing your data science needs, you can focus on actually running your business, and scaling your organisation. Not only do you save time and effort in hiring a data scientist, you also don’t have to worry about your data science function, so you’re not using all your energy in an area that isn’t your specialism. Using a managed services provider rather than an in-house team means you can focus on the bigger picture, whilst still gaining the competitive advantage that a data science function can bring.
4. Take the Pressure off your Team
A managed service takes the pressure off your internal teams, so they can focus their resources elsewhere to further the goals of your organisation. A good team is invaluable, and often, you’ll be able to get more out of them by outsourcing your data science needs to experts. Take away the pressure of having to learn new and complex technology and keep up to date with the data science world by outsourcing to a managed service provider with a wealth of experience and knowledge.
5. Peace of Mind
Working with a team of experts, who have years of experience as well as the necessary skills, can give you peace of mind when it comes to your data science and machine learning needs. Through using a team of experts, rather than a single data scientist, productivity will increase, and as a result, work on your data science function more effectively, producing great outcomes.
6. Know where you are on the Data Maturity Curve
One thing that may be stopping you from going down the managed service route is not knowing where you currently are, where you need to be, and how to get there. Figuring out where you sit on the data maturity curve can be tricky, but a good data company can also help with this, mapping out the best course of action to take for your specific requirements. Knowing where you sit can also be a huge advantage in other areas of your business.
If these reasons resonate with you, why not take a look at our Managed Data Science Services. With a customisable approach to support, we can provide exactly what you need, no matter how big or small your organisation. Outsourcing your data science function ensures you are top performing, and can help inform insights, leading to more effective decision-making.
Blog Author
Andrew Hill, Managed Services and Support Manager, Simpson Associates
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