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5 points to consider when building or buying analytics

Written by Harry Dix  | 

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5 points to consider when building or buying analytics

A common question many organizations face, when it comes to rolling out analytics, be it organization-wide or embedded into a software product, is that of deciding whether to build in-house or buy off-the-shelf.

There are, of course, pros and cons to both approaches, and deciding which works best for your organization will ultimately depend on your team’s composition, your analytics use-case, and your expectations.

In this article, we’ll walk you through some of the main points to consider in your journey to analytics acquisition, ensuring that, when you hit “go”, you’ll be investing in the option that best suits your needs.

Knowledge and skill sets

If you plan on rolling out analytics within your own software product, then your teams may be able to leverage some of their existing cloud infrastructure and software development-related skill sets, making a built-in-house analytics solution a possibility.

However, while your team may hold some of the knowledge and skills required to build an advanced analytics platform, it’s likely that you’ll have gaps to fill. Identifying, recruiting, and onboarding highly skilled architects, engineers, and developers is not only time-consuming, but also costly, especially considering their short supply.

Control over your data

Without a third-party analytics platform for your data to pass through, if you store your data in your own private cloud, you keep complete control over it. Regardless of whether you use a private or public cloud, using a third-party analytics platform means that your data will have to go through another vendor.

Therefore, you need to be sure that the analytics platform you choose and its back-end, data transformation processes fulfill the highest privacy and security standards.

Costs and scalability

On top of increased hiring, building your own analytics platform requires the obvious upfront investment in infrastructure, architecture, and back-end data management software. Of course, you may possess some of these resources already but, as is often the case with internal development projects, unforeseen costs can arise along the way.

This can make it very difficult to predict the scope of a DIY approach in the long term.

Much like any forecasting, it’s not so much about initial deployment costs, but about building ROI and sustainably building profits in line with your customer base. And when you work with an analytics vendor, you’ll only pay for what you use. You can pick & choose pre-built platform components based on your current and future needs, including; data computation power, data volume, and the number and size of user groups (i.e. customers, teams).

Time to market

The biggest hurdle for your organization may not simply be resources or investment, but time. With basic in-house analytics solutions, it often takes around 10 months to get them up and running; with fully developed, end-to-end analytics solutions, taking much longer (several years in some cases).

By contrast, acquiring an advanced analytics platform results in a much quicker deployment, as little as eight weeks, along with the ability to drive customer growth and retention almost instantly.

Maintenance and updates

Your users (or customers) will expect the same continuous service levels regardless of how fast data and usage are growing and, therefore, an in-house analytics solution must be constantly updated, maintained, and, at times, scaled.

In this respect, an off-the-shelf solution will mean that you won’t need to go through the hassle of recruiting and onboarding hard-to-find specialized talent and, by employing a vendor with long-term industry knowledge and experience, increased efficiency for your company.

Analytics platforms are complex solutions requiring the development of a full-blown engine as well as multiple tools to support them. Your provider will have a dedicated team ready to quickly deploy solutions, troubleshoot any issues or discuss what new features you would like to see developed in the platform.

Which makes more sense for you?

It is clear to see, that while an in-house analytics solution ultimately gives you a blank canvas to create a solution tailored to your needs with your data handled only by you, there are caveats in the form of potentially prohibitive costs, hiring requirements, and longs launch times.

Mitigating the above is a possibility, but when purpose-built analytics solutions exist, with the ability to be fine-tuned to specific use cases and organizational needs, then it’s easy to see why the latter option starts to make more sense for many organizations.

Want to learn more? Download.

Want to dig deeper into the pros & cons of building in-house or buying off-the-shelf? Read our “Buy vs. Build” ebook and get more in-depth information about which is the best for you.

Does buying an analytics solution sound like the right way forward?

Request a demo and let our experts take you on a guided tour of the GoodData platform. They’ll help you discover why GoodData is the leader in headless BI, with a platform uniquely built for scaling analytics to an almost infinite number of teams, departments, and business partners. They’ll show you how the processes of scaling, change management, and control can be cost-efficient, fast, secure, and automated, as well as answer any of your questions.

Written by Harry Dix  | 

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Go back to Blog's hub Blog   |   tags:  

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