Dive Brief:

• Even small investments in data analytics strategies have a propensity to pay off if the need is defined and people are invested, tED reported.

• Though returns on investment (ROI) are typically targeted, smaller companies moving toward the introduction of data analytics should focus on lower numbers, such as 1:1 to start. Balancing out an investment is good enough for a beginning user.

• Data analytics will not solve all company issues, but companies should measure its effectiveness on a marginal basis. 

Dive Insight:

Supply chain managers may want to ask themselves the following questions before diving in to a data analytics project.

Do you have a specific issue in mind? The problem should be defined before the solution can be offered. Has there been an ongoing issue you need to solve, that you suspect analysis might answer? If so, go forward. Do you have the right data to help with your specific problem? Not all data is applicable to every situation. It may be that you can acquire the proper data to help with your problem, but do an investigation first, so you don't waste time. Is your data usable? A variety of data exists, such as structured or unstructured, endogenous or exogenous.The type you need depends upon the particular problem at hand. 

Do the algorithms exist? At this stage of data analytics, algorithms exist for most issues. However, there is always a chance that your particular problem is the first of its kind and cannot be solved by data analysis. Confirm that currently available algorithms are truly applicable to your concern. What size sample should I choose to start? Always start small, ensuring your own comprehension as the project progresses. Then, if you find that you achieve both understanding and success, you can more successfully expand your project if needed.