Analytical. Data Science Words and phrases like these tend to conjure up images of guys in thick glasses leaning over stacks of worksheets with the smell of stale coffee that permeates the office. But today 's data and analysis teams could not be further from the caricatures we make of them. And the truth is, when you discover just what is possible, it can be hard not to be excited about it!
So, how do you get the biggest trilobite technology in your office, not only to adopt analytics, but also to share your enthusiasm? Here are some ways to make the idea of data science a lot more tempting.
Understand the Underlying Problems – Then Solve Them
Companies in almost every industry, from B2B to B2C to B2B2C and everything in between, have their reasons – good reasons – for keeping a cool head in the field of analysis. Often, sales teams do not see enough leverage to make the product worthwhile.
Managers are very busy managing and do not have the time to draw a high learning curve, let alone understand the data enough to make safe decisions using them. And even key decision makers are slow to adopt an analytical culture because the protocols for decision making are … you guessed it, done by the committee.
The fact is that no domain changes or adapts faster than data science and in the same way that the Internet has revolutionized the way we communicate and do business Analysis analyzes how to make decisions, products and more. It's just as much an integral part of a successful business as having a website marketed more than ten years ago.
This means yes, some work may need to be redesigned, some outdated protocols will have to be revised, and some objectives will have to be modified to accommodate the rapid growth of the analyzes.
Companies that adopt this chameleon-like adaptation are those that truly benefit from the greatest benefits of science and data analysis. Those who fail to see its potential will continue to struggle as their competitors get more and more information backed up by the data.
In short, it is uncomfortable but necessary to change.
Embracing the democratization of data
One of the biggest terms circulating in the world of data science is the "democratization" of data. In other words, remove it from the analytic geeks and put it down in the hands of everyone, from executives to managers, to customer service and even to the concierge staff (all in all). -be not the last). New SaaS tools and platforms are being developed and deployed faster than ever before, and today's data scientists can use visualization tools to map different scenarios. Elements such as predictive analytics show all models of what can happen with the current data collected, so that new campaigns, new product ideas and overall business growth can have an impact and be scalable.
And did I mention that all of this can be done without a single line of code?
But before I think I'm throwing data scientists and analytics gurus under the bus, keep in mind that they're still very, very important and crucial to any business. # 39; organization. It's their direction that will lead to embrace the democratization of data on a much larger scale. Putting everyone at ease and comfortable with the data leads to greater understanding and confidence. Greater confidence leads to excitement and discovers new opportunities that only one person or team may not have considered.
And knowing this, why would you restrict yourself by leaving all your analytic decisions in the hands of a few, when you can enjoy greater insights and data-driven determinations when everyone can?
Reaching Benefits on a Large Scale
One of the biggest problems that companies face in their quest for better data management is obtaining large-scale benefits. It's one thing to comb through the data and get some new nuggets that can give you a slight increase in conversion or revenue. It is another thing to try to reorganize the structure of a company or an entire organization from the inside. It is overwhelming and virtually impossible, which dissuades many people from adopting a culture of analysis at the company level.
In these cases, start small. Start with the departments or areas that you think could make the most of the analytical knowledge. Make sure you keep others informed through appropriate communication channels such as newsletters or mailing lists. Be patient. Remember, just a few years ago, articles like this one were more focused on accepting C-Suite than on transforming an entire business culture.
Another frequent complaint is the use of tools. In many cases, companies are investing in analytics, but vendors are not able to accurately demonstrate how these tools fit into the existing workflow. If the sales staff can not understand or defend him, he will not use it – simply and simply. Whatever analytical tools you choose to adopt, make sure that they easily adapt to your existing processes, not the reverse.
Why most companies slaughter in analytic mud
Many companies looking to adopt a data-driven culture (more details below) are turning to mega-profitable companies like Amazon and Facebook.
But these businesses, by and large, are relatively new and were built from an analytical culture. They can adapt quickly because it is in their DNA.
For companies not rooted in data science, the change will be made gradually – starting with the departments most likely to be affected. This may even require a change from the inside – how decisions are made, who is responsible and what is the end goal. For example, if you are investing in a data-driven module to facilitate dynamic pricing and the elements are starting to sell faster, you may not be able to hold your inventory managers accountable. Moving to more data-driven decisions means changing the way things are done – perhaps even drastically.
But by showing how much their work can be streamlined and their decisions can be made, people will begin to get used to using analytics in their respective departments. As changes are implemented and new information comes out of the information, people are starting to look for new angles and ways to use the data to better empower their staff and colleagues. It also helps to improve job security, the relationship with customers and the ease and confidence with which they do their work.
Becoming a truly data-driven company
Carnegie-Mellon recently conducted a study LEAP which determined that the companies that made the most of the analytics were those whose leaders focused on "collaboration". team, with the ability to easily share their ideas. Much of this collaboration comes from self-service tools, which can be supplemented for specific industry sectors and niches and deployed much faster than a complete software program.
But becoming a truly data-driven company involves both tools and people – not focusing on the exclusivity of the other. As business members begin to learn and take advantage of analytical knowledge, their enthusiasm and knowledge begin to spread in a coaching effect for other departments. This will not happen overnight, but gradually, as people become more comfortable with the way analytics can be used in their little corner of the city. business, they will begin to rely on the data to fuel their decisions. more.
How do you use analytics to encourage others in your business? Are you becoming more data driven, or is it a difficult climb compared to a more traditional workflow? Share your thoughts and stories with us in the comments below!
About the author: Sherice Jacob helps business owners improve website design and increase conversion rates through compelling writing, easy-to-use design, and analysis intelligent analytics. Learn more about iElectrify.com and download today your checklist for debugging and converting your free copy!