Data Built Culture and Ethos – Can it be done?

By Samadhan Belose

We live and thrive in a world that is replete with data. Everything, from your education details to your relationship status to your financial health, is present online. This boom in data has enabled companies to dig deep into their customers’ lives. Although ethical standards dictate that companies respect individual privacy, it’s highly questionable.

Since companies have been making huge profits by identifying their customers’ likes and dislikes, they must focus on creating a data-driven culture. The following points describe how they can do that.

Data built culture: How can we achieve this?

1. Start from the top

The best way to drive a data-driven culture at the workplace is by letting senior leaders adopt it first. They should inculcate the habit of going through facts and figures before starting any meeting. It will help them make decisions based on evidence, experiments, market trials, and detailed summaries instead of raw knowledge and plain intuition. Slowly, this habit will percolate to junior employees because they have to communicate with managers in their language.

2. Choose the right metrics

Leaders should prepare a list of critical metrics that they will use to measure their business productivity. For example, if you are a mutual fund company, predicting what funds will underperform and what will overperform will be the right metrics for you. On the other hand, if you are a telecom operator, then creating customer segments based on calling time and data usage will be the deciding metrics for your company.

3. Data scientists and senior leaders should work in tandem

One of the major problems companies face is the imaginary divide between data scientists and senior leaders. To deconstruct this invisible wall, companies should insist on employees becoming code-literate and gaining fluency in basic quantitative concepts. Knowledge-workers working in a data-centric organization cannot afford to remain ignorant of the language of data.

4. Take one step at a time

When data science and analytics are combined, they can promise millions of ideas, out of which only a handful can be implemented. A quick and easy solution is to provide proof of concept in the initial stage.

Companies should identify ideas that match their organizational goals and can be executed smoothly. They should build simple prototypes, collect initial feedback, use data science techniques to segregate business-critical information from raw data, and then ratchet up the sophistication level if the idea shows some promise.

5. Train your workforce beforehand

Many companies invest heavily in long training sessions that are concentrated over a small period. Since these sessions don’t focus on practice, employees lose interest rapidly and forget the concepts they need. While it’s imperative to gain a complete understanding of necessary computational skills such as coding, employees should also have a working knowledge of data science techniques. It will enable them to understand, contest, and produce counter opinions during the proof of concept stage.

6. Increase the frequency of question-answer sessions

In data science, there are numerous ways of solving the same problem. Leaders should conduct various question-answer sessions to gain a theoretical understanding of the nitty-gritty of the project. They should gain a working knowledge of why the data scientists chose a particular approach over the other alternatives, the trade-offs that exist, and discuss fundamental assumptions. This approach helps to uncover hidden flaws.

Companies often resist going into uncharted territories and exploring new areas because alternatives appear too risky. Data provides proof of concept and evidence to back up hypotheses. But an organization does not become data-centric just by hiring data scientists. Leaders need to adopt new habits and promote this shift by setting an example. Companies should try bringing a change in how they operate and transform their decision-making process by relying more on data.

Author:

Nishant likes to read and write on technologies that form the bedrock of modern-day and age like Web Apps, machine learning, data science, AI, and robotics. His expertise in content marketing has helped grow countless business opportunities. Nishant works for Sage Software Solutions Pvt. Ltd., a leading provider of CRM and ERP solutions to small and mid-sized businesses in India.

More about Irish Tech News and Business Showcase here.

FYI the ROI for you is => Irish Tech News now gets over 1.5 million monthly views, and up to 900k monthly unique visitors, from over 160 countries. We have over 860,000 relevant followers on Twitter on our various accounts & were recently described as Ireland’s leading online tech news site and Ireland’s answer to TechCrunch, so we can offer you a good audience!

Since introducing desktop notifications a short time ago, which notify readers directly in their browser of new articles being published, over 50,000 people have now signed up to receive them ensuring they are instantly kept up to date on all our latest content. Desktop notifications offer a unique method of serving content directly to verified readers and bypass the issue of content getting lost in people’s crowded news feeds.

Drop us a line if you want to be featured, guest post, suggest a possible interview or just let us know what you would like to see more of in our future articles. We’re always open to new and interesting suggestions for informative and different articles. Contact us, by email, twitter or whatever social media works for you and hopefully, we can share your story too and reach our global audience. We are agile, responsive, quick and talented, we look forward to working with you!

If you would like to have your company featured in the Irish Tech News Business Showcase, get in contact with us at [email protected] or on Twitter: @SimonCocking