Stagnation is the indomitable enemy of the modern business. To maintain the status quo is to fail to compete effectively against other businesses. To adjust sails in modern times, most businesses have major digital and data capabilities. For businesses who have to make changes, like those that want to switch mailing systems from RedShift to HubSpot, data analytics are equally important. Whether you’re making changes to your company or starting a company, you need to invest in analytics. Data analytics are the cornerstone of any modern business. No company lacks data, but not all companies leverage data in such a way as to boost sales and increase engagement among customers.
Even individual people have access to endless data because of the computers in their pockets. There’s plenty of data out there waiting to be put to use. For decades, there’s been no shortage of data across industries, and companies have been able to gather more complex data over the years, but little has been done in the way of optimizing the usage of that data. Tech teams must work to extract information from veritable siloes, turning that information into a series of relationships that paints a picture of a business’s digital landscape.
If you’ve become angered by your tech team’s inability to bridge the gap from data to success, the following pointers may help you get things right consistently.
1. Remember The Importance of Regular People
Insights into data can’t come to fruition without a human mind to notice a pattern. Data must suggest things that IT professionals don’t already know, and they must have the company-wide privileges to bring about change with available data. People must be able to examine results and generate change. Otherwise, immediate data collection holds no substantial value.
A major remedy to this problem is good recruitment. You must constantly be hiring and keeping great talent across all departments, including IT. All employees throughout your business must be able to employ data in some capacity. Information across multiple siloes can create a cohesive business as long as you can organize that information in a clear way.
2. Consider More Than Available Tools
For the purpose of data analysis, most relevant tools are digital analytics interfaces, user-friendly ways for marketing teams and data teams to extract meaningful information from raw data. However, these analytics tools may not always be complex enough to address your company’s needs. As necessary as some tools might be for other businesses, not all tools will be complex enough for yours. The key is not to purchase analytics package after analytics package in the interest of always having the best possible technology. After all, your tech team is doing the work, not whatever tool you buy. Your primary focus should be on creating a data-driven culture within your business so that all departments are capable of using data to their advantage.
3. Demand a Return on Investment
When you’re hiring members of your tech team or installing new digital analytics interfaces, remember to establish quantifiable goals from the get-go. Don’t start doing stuff for no reason. Request tenfold returns or don’t go for it. Measure success at every stage of the data analytics process to make sure your business is headed in the right direction. Don’t beat yourself up if you’re headed in the wrong direction. Just adapt to your new circumstances in a productive way. When you start to see progress, this signals to you that you can add new actions to the mix instead of evaluating current actions.
4. Ask Good Questions
Leaders across industries often employ more advanced technologies like machine learning among other examples of artificial intelligence. These items differ from more rudimentary forms of data analytics in that you don’t need to ask a good question if you have access to more complex data analytics. Pose the right questions to each of your data silos by finding the most skilled data scientists for the job. Great data scientists can ask and optimize the right questions, addressing your business’s needs accordingly.
More specifically, ensure that each member of your business has a bias toward action. What is the data doing? Is it generating any money? These are questions members of all departments must consider in the interest of maintaining key analysts’ involvement in change across multiple sectors, from finance to operations.
To establish this potent bias in data analytics, establish immediately the major use cases for the data to be collected. This top down approach to your business’s data-driven development will best put your tech team to work. Determine great data sources and practices alike, leveraging both to deliver on your priorities. Ultimately, data analytics must be professionally managed in such a way as to guarantee a significant return on investment.
