Top Reasons to Outsource Your Data Science

The outsourcing of Big Data and Business Intelligence projects is becoming an increasingly attractive and feasible option for Small and Medium-Sized Businesses (SMBs). In fact, those companies who are not taking advantage of their data are getting left behind. As the name itself implies, Business Intelligence provides its practitioners with a compelling competitive edge. When an organization cannot afford to have their own in-house team of analysts, outsourcing is a good option. Here is a brief list of the advantages:


Advantage #1) Increased productivity and efficiency.

Some managers give in to the temptation of thinking business intelligence is just the latest management fad. This not the case. In fact, just the opposte is true. We can take any number of examples, but for our purposes Amazon is a perfect case in point.

If you check the track records of companies like Amazon and FedEx, which have been utilizing data analytics for over a decade now, the case will be clear. Amazon, with its historically unprecedented investment in data science, has built algorithms based around their customers’ daily buying patterns and needs. It has access to vast amounts of data on its customers, and this helps it build a picture of their shoppers. Amazon uses all of that data to target customers with very specific products, which greatly increases of the chances of additional purchases.

With this data-based approach, Amazon has disrupted virtually every industry. All of it is based on data. The industry sometimes refers to this as the ‘Amazonification’ of data. Many smaller businesses look to Amazon and are eager to implement analytics but don’t have the know-how or the resources. For these smaller companies, outsourcing is one possible way to reap the benefits without having to invest in hiring a data scientist full time.


Advantage #2) It allows you to focus on your core business

If you have to stray too far from your core business, you’re may be taking a risk to hire in-house for data science. When in doubt, it’s often better and certainly less expensive to outsource small tasks. Specialists, such as EISM, are experts and concentrate on what they do best. Through outsourcing, you can test the waters.

The return on investment is clearly defined with a third party. The outsourcing company needs to create value. Data analytics vendors are assessed on the business outcomes and not on the time and materials we use. A successful data science project translates into success for the client, and this is a mutually beneficial relationship for the company as well as the vendor.


Advantage #3) Cost Savings

Finances are a major factor for all businesses, and even more so for smaller businesses. Hiring a full-time data scientist is expensive. In addition to the base salary, which is notoriously high, there are taxes, employee benefits, and the risk of losing the talent. If you need more than one analyst, multiply the costs accordingly.

This is why outsourcing your data science projects to a company like EISM makes sense. If you perform a cost-benefit analysis, it will likely show that the value of the benefits of working with EISM far outstrip the value of the cost. Keep in mind that costs include not only direct resources but also indirect resources and the human effort that must be put forth over a period of time. Outsourcing will leave managers with more time to focus on the core business. In this regard, there is great value in well-developed business intelligence to help make better, faster and informed decisions.


Advantage #4) Lower Financial Risk and Lower Costs

It is a well-established fact that there is a shortage of good data analysts in the market today – there are far more jobs than eligible candidates.  This shortage of qualified data scientists makes it hard for hiring managers to find the correct candidate. And if a company is fortunate enough to find a great candidate, the candidate will immediately begin to targeted as a recruit by other companies. Hiring also requires a serious investment of time, especially when its done right. If a company does not have the budget to outsource, the company can do so on a per-project basis.


Advantage #5) Focus on your customers

Being able to understand and serve your customers better is one of the main fruits of business intelligence. This is especially the case with marketing and predictive analytics. Data analytics is vitally important for customer-centric companies in the business-to-consumer world. Business intelligence allows such companies to learn more about their customers, even anticipate their needs. Marketing professionals who work with large numbers of customers understand that the goal is to reach the right customers with the right message at the right time through the right channel. Good data analytics provides the tools to get this right.


In closing, it’s worth mentioning that a recent Gartner survey showed that over half of the respondents used outside partners for some or all of their analytics needs. In fact, 55% of those companies reported working with third-party partners to address the lack of skills.

If you find any of the information above applicable to your business case, please contact us. We would be happy to provide you with a no-obligation assessment of your situation and outline a potential solution.

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