Managed Data Analytics: 4 Pros And Cons

The past decade or so has been a boon for “exponential organizations,” which are brands that managed to create ten times more impact than others for a reduced cost. It’s not even that difficult to find one: a brand that’s been the talk of the town for a long time is proof of its exponential growth.

While most of these organizations are digital to the core, their ability to harness data sets them apart from others. Many experts agree that today’s household brands wouldn’t be such if their business model didn’t allow for data-driven decision-making. There’s no reason this shouldn’t be the case; to quote one business leader, “data powers everything we do.”

Adopting a data-driven approach doesn’t necessarily mean ditching intuition but rather getting the former more involved in business decisions than ever. Some organizations may elect to do their data-related functions in-house. However, those without enough capital to maintain such infrastructure rely on managed data analytics from a managed services provider (MSP).

In-demand service

One study shows that more businesses prefer working with MSPs than other forms of third-party assistance. Among small and medium-sized enterprise (SME) owners, 68% believe working with one can help them remain competitive. (1)

MSPs such as KM Tech and others offer a wide range of services, but the study shows three in high demand today: data protection, data and analytics, and cloud services. In fact, most SMEs and other institutions say MSPs must offer these services before being considered. Focusing on delivering quality results in these fields is in the MSPs’ best interest. (1)

However, why are MSPs in demand today, not to mention vital in a business’s data-driven approach? Cost and security are the two most general considerations, with more organizations saying it’s the former.

Here’s a rundown of the benefits of hiring an MSP for managed data analytics:

Having an in-house data analytics specialist won’t come cheap, as the salary range for a line of work is from USD$41,000 to USD$131,000 per year. Working with an MSP means businesses don’t have to pay any salary; the MSP already pays the specialists. (2)

Managed data analytics are a more compelling option amidst a looming shortage of data analytics specialists. While the gap between supply and demand has shrunken over time, recruiting and maintaining an in-house team is still filled with uncertainty. (3)

Businesses don’t have to wait years to adopt a data-driven model if they hire an MSP for managed data analytics. In the earlier study, 55% of business owners said it took only a few weeks to set up their data-centric workflow. (1)

Experience comes with MSPs, which is crucial in empowering even non-IT-oriented business personnel in using the data to their advantage. Experts identify this expertise democratization as one of the top ten trends businesses should consider.

The downsides

As with everything else in doing business, managed data analytics comes with as many risks as benefits. Any attempt to shift to a more data-driven business model must consider the following before doing so:

Regardless of how much trust one places in their chosen MSP, entrusting valuable data to a third party has inherent risks. Searching for an MSP that can keep a business’s data safe will undoubtedly entail extra steps, hence requiring more resources.

The relationship between an MSP and its client is, for the most part, contract-based. The contract may offer legal protection in case something goes awry, but a business may find itself sanctioned by it if it’s in the wrong.

Managed data analytics tend to grow more expensive with scaling. Increasing the number of queries, let alone the speed at which they provide data, may strain a business’s budget. Many companies have actually dropped their MSPs over rising costs alone. (1)

MSPs provide managed data analytics to clients in various industries. This means there’s the risk of them lacking knowledge in a specific domain. Experts understand the need to expound on their domain expertise, but such a guarantee doesn’t exist in selecting MSPs.

Pros and cons are inevitable, but the existence of exponential organizations is proof that working around them is possible. An interview of four companies that benefitted greatly from harnessing real-time data analytics offers four crucial lessons:

Know the business well
Focus on what the data says
Find good business partners
Determine success reasonably

Conclusion

Regardless of its applicability, managed data analytics is in high demand, perhaps more than ever. Letting experts in data analytics gather, sort, assess, and interpret the data has its equal share of pros and cons. Being aware of these when proceeding with a data-driven approach is essential.