Updated: Oct 28, 2020
Editor’s Note: The goal of this post is to demonstrates how to integrate data into your business. If managed analytics sounds like the next step for your business, please contact us here to receive more information.
A data driven culture is highly sought after in today’s technology centered world. For many businesses, the thought of integrating data into their daily operations is easier said than done. This post will guide you through building a data strategy from start to finish.
Why do you need to worry about it?
Forbes recently described data as “the lifeblood of any business” when outlining why small businesses can no longer ignore their data. Harnessing the capabilities of data can enhance a business owner’s knowledge of what is really going on in their company: who their customers are, their buying habits, as well as help to identify seasonal and geographical patterns. In addition to heightened awareness of what is included in current data, analytics possess the capabilities to predict future business trends and provide recommendations on businesses can optimize their operations. Collecting and understanding business data has quickly become a key to success in today’s business world. Can your business afford to miss out on these insights?
What is data maturity?
To begin building a data analysis infrastructure, companies must evaluate their current data maturity. Data maturity refers to an organization’s awareness, capabilities, level of buy-in, and allotment of resources.
The Data Maturity Model
Booz Allen Hamilton defines data maturity in their 2015 Field Guide to Data Science as several stages that move from very little data science capability to very powerful insight creation. The graphic shown here outlines their distinct steps to achieving data maturity.
Each section of the model is named for the analytic capabilities an organization should possess at that point of the process. The definitions of these processes are seen below.
How to Judge where your Company lies on the Data Maturity Model
The best place to begin, it is to conduct an internal assessment of what is being done with data currently within your business. Ask yourself questions such as “What data is being collected?” “How is it being collected?” and “Who is using this data and how?” Knowing the answers to these questions will provide a reference point for where your organization is at in the Data Maturity Model.
How to Advance through the Data Maturity Model
Once you have assessed the current state of your data, lay out several short term and long term goals for your data strategy.
LONG TERM GOALS
Consider the reasons why you want to implement a data infrastructure–this should point you towards the long-term data analysis goals you desire. Depending on where your business lies on the data maturity model, you will need to consider implementing the following processes:
Data collection through current records, forms and/or sensor inputs
Data warehousing and/or storage in an on-premises database or an external cloud such as AWS or Microsoft Azure
Access/Extraction/Cleaning/Transformation in programs such as SQL, R, Excel, or Tableau Prep
Analysis and insight creation through a team of analysts and data scientists whether internal or outsourced
Please note that the resources mentioned above are merely recommendations and while they are commonly used within data analytics, there are a wide range of other tools and platforms that may be more suitable to the needs of your business.
SHORT TERM GOALS
These should be easy to implement changes that align with the overall data strategy goals of your business. Solutions included in short term goals need to be scalable, so that they may grow and adapt along with the infrastructure of your data pipeline. If your business is starting from scratch, a good first step would be to audit your current data collection methods, adding in pipelines for data that is needed but is not currently being collected. A suggested next step is to ensure the data already being collecting is stored and aggregated in a singular location.
Short term goals should allow you to move through the data maturity model at a pace that is compatible with the goals and needs of your business. This will help facilitate a data strategy that grows intentionally in a way that will benefit your business in the future with minimal maintenance, rather than the need for a total overhaul of your data strategy every few years.
Establishing a data infrastructure can be a daunting task when considering everything a successful strategy requires; However, breaking down the process of building a data pipeline can make achieving your data goals much more attainable. If your small business is ready to take your data strategy to the next level, consider reaching out to the team at Bear Cognition for more information.