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Six Big Data Consulting Tips for the SMB Market

February 17, 2017

Six Big Data Consulting Tips for the SMB Market

The big data revolution is creating new reseller opportunities, but one of the mistakes that many companies make is equating big data with big budget. Companies of any size can benefit from big data analytics—you just have to scale the project to suit the company and its budget. Even companies with large-scale big data projects should seriously consider starting with smaller big data initiatives so that they can learn to walk before they run.

Demand for big data is increasing in all sectors with every type of operation. IDC says that big data technology is a multibillion-dollar global market and that big data services are growing at a compound annual growth rate (CAGR) of 26.4 percent that should reach $41.5 billion by 2018. That’s six times the CAGR for the information technology market as a whole.

Along with this fast-growing demand comes  a shortage of big data expertise. According to McKinsey Global Institute, in the United States alone, there will be a shortfall of 140,000 to 190,000 professionals with the necessary analytical skills to implement big data, and 1.5 million managers who lack the understanding to make big data effective. This is an ideal climate for big data resellers with the expertise to help small to midsize  businesses (SMBs) tackle big data projects successfully.

Here are six ways that big data consultants can best serve the SMB market:

1. Determine what data is available to mine.

To get the most from big data, start by determining what data sources are available for analysis. Retailers, for example, should have a wealth of data from sales receipts, including sales volume, seasonal sales trends, profit margins and customer profiles. If you are working with a medical practice, you have access to data about patients and patient demographics, insurance payments, the cost of care, seasonal trends and other details. Depending on the nature of the customer and its industry, you will have different types of data repositories available for big data analytics.

Also consider which external data sources could be of value. For retailers, for example, insight gleaned from warranty cards, social media and call center reports could be useful in isolating any number of trends.

2. Set the right scope for the project.

When working with SMBs, start small and scale up. Develop a use case that is easy to execute and has concrete value to the customer, demonstrating how to increase profits on a single product, cut staff overhead, reduce costs with a specific supplier or realize some other concrete benefit. Once you demonstrate the returns from smaller initiatives, you will gain sufficient trust to scale big data projects. And be sure to communicate expectations from the outset. If you set more modest goals, it will be easy to impress the customer with the results.

3. Develop the right use case.

Helping customers maximize their big data value means finding the right use case. Looking for targeted insights from available data and breaking them into bite-sized projects is the best way for SMBs to get started in big data.

For example, rather than trying to use big data to identify the best sources to attract new customers, use something more specific, such as the impact of a customer loyalty campaign on sales or the effectiveness of specific marketing campaigns. When working with SMBs, you can show them the value of targeted big data use cases with the help of free and familiar tools such as Google Analytics.

Remember that the most common use cases identify business patterns, provide a 360-degree view of the customer, assess operations or address security issues.

4. Provide big data metrics.

Agree on the metrics for success from the outset. Determine what types of measurements will be most meaningful and valuable and use those metrics as a baseline for the project. Big data analytics can reveal a variety of insights, but you should have at least one baseline measurement in order to demonstrate success. You should also work to help the company develop a culture of measurement so that all business activities can be assessed for success.

5. Harness the cloud.

Small businesses have smaller IT budgets, so rather than recommending more enterprise computing and data storage hardware, use cloud-based CRM, file storage, backup, project management and accounting tools  to accommodate big data. This not only saves the customer money, but can also simplify data set integration. Harnessing the cloud lets  SMBs tackle big data with a very small investment.

6. Interpret the results.

As noted above, one of the greatest impediments to big data adoption is a shortage of qualified data scientists and big data analysts. Your job is to not only help design the big data infrastructure, but also to help with data interpretation. Take the numbers and charts that result from a big data project and be ready to explain the results. It’s all part of being a big data consultant to the customer.