Inc.com blogger Jessica Stillman recently wrote about small businesses getting baffled by big data. These companies, she reported, struggle to even define what big data means – much less manage it to their advantage.
I think that the issue is not limited to just smaller and midsize companies. Even larger enterprises are wrestling with the volume, variety and velocity of data being generated. Smaller businesses are just more overwhelmed due to their IT and analytical resources constraints.
The answer is not to give in or ignore the data problem – not if you wish to stay competitive with your larger counterparts. Instead, it lies in finding simple fixes that make big data more manageable. Below are some simple steps you can take to get started on your data journey.
- Start with an end goal – it pays to know which data to track. All data is not equal – so don’t collect data indiscriminately. You will soon run out of your limited resources, and most data will go unused or at least underused. Work with your business partners and executives to explicitly define your business goals and the problems you wish to solve. If the most important goal is to increase revenue, focus on collecting data that provides insight into customer attributes like profitability and buying behavior to help you target right customers.
- Start small – build on the hierarchy of needs. Your business data can help you uncover all different types of opportunities and can generate a myriad of metrics and statistics. Choosing between all the possible opportunities can almost be counterproductive. So establish a baseline. What is the first thing you want to achieve? Maybe it is just consistent, standardized reporting for you to get your finger on the pulse of things – what is happening, when it is happening, and where. Then, build upon your success. In the short term, it will help you cull your data to a manageable size without overwhelming IT or your analytical experts. In the long term, this will help get more executive buy-in for future projects and help build a data-driven mindset.
- Start right – invest in the right tools. Smaller companies often go with standard, off-the-shelf tools like Excel to be cost-effective, and then struggle with the inherent weaknesses of these tools. Take the example of Gilt Groupe, an online fashion retailer. The company initially relied on Excel and SQL queries for analyzing data, which took a lot of manual manipulation. It took Gilt’s analysts as much as 30 minutes to just transfer data from spreadsheets, greatly limiting what they could do. With the right tools, the company was able to access and combine information from any number of sources and start producing reports of various degrees of complexity relevant to different functions across the organization – greatly improving its productivity and profitability. When investing in analytical tools, don’t just focus on immediate cost; look at long-term value as well. With the right analytical tools, you can process more data much more quickly and get better, more precise insights faster for timely, effective decision support.
Large companies have always crunched numbers to track their performance, evaluate risk/reward potential of an investment, and segment and target their customers with more granularity. But smaller companies like , , and have proven time and again that by working smart, smaller companies too can take advantage of their data as well as their larger counterparts.