How To Foster A Data-driven Culture Within Businesses
“In today’s digital world, we must ensure data lies at the heart of their culture to grow and survive.” Easy to say, not so easy to accomplish. Marcos Monteiro, CEO and co-founder of data analytics firm, Veezoo, outlines five steps companies should take to foster a data culture. 1. A data-first culture starts at the […]
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“In today’s digital world, we must ensure data lies at the heart of their culture to grow and survive.” Easy to say, not so easy to accomplish. Marcos Monteiro, CEO and co-founder of data analytics firm, Veezoo, outlines five steps companies should take to foster a data culture.
1. A data-first culture starts at the top
Senior management often contrives corporate initiatives and values without explicit guidance to ensure these concepts are successfully realised. A commitment to creating a data-driven culture must start at the top. This requires the organisation’s leaders to focus on using facts and figures to demonstrate to the whole team the importance of making decisions based on data rather than instinct or experience.
So, whenever you’re communicating something new or making a change to the company, use data to illustrate why that decision has been made. This demonstrates that senior management uses data to guide decisions and helps set expectations for all team members, consultants, and contractors. Make a point of showing the role data plays in informing all decision making.
Often, what holds organisations back from embracing an open data culture is the fear of exposing underperformance or other shortcomings to employees and shareholders. But being humble and admitting that you got things wrong (and how data can guide course corrections) creates a transparent environment where constant learning and evaluation becomes ingrained into the organisation’s fabric.
2. Make data available as a commodity
To get the most benefit from a data-centric culture, you need to have the relevant datasets and sources working together so you can get the full picture. Implement a data infrastructure that pulls in core company data and syncs with each department’s data to provide a complete overview of the whole business. For example, it’s no good asking ‘What was the best seller last month’ if you don’t factor in the amount by which marketing boosted ad spend on certain products.
This, therefore, requires investment both in infrastructure and in implementing data quality processes and governance to ensure the accuracy, integrity, and security of the data streams the company generates.
This is not something you can achieve overnight, nor will it generate an immediate ROI. It requires commitment and buy-in from all departments to develop a model and the required dataflows. You need to frame data as a collective good rather than something that benefits key operational teams such as sales and finance.
3. Your data is only as good as its supporting tools and processes
Large databases are complex resources and can only work efficiently if supported by well-designed data-collection processes. This is especially true for human-generated data such as customer records in the CRM system. Maintaining effective CRM systems may require detailed input into many different fields—a potentially overwhelming and time-consuming task with a high potential for being avoided or skipped.
When you put garbage in the system, you get garbage out of it, and data quickly becomes useless. So, limit the amount of data that you require teams to capture and automate as much as possible using RPA tools. This significantly reduces the time spent on data entry and increases data quality. Keep in mind that the best way to get team members to commit to data entry is to see the benefits it brings to their role and their team’s success.
It’s not until people start making data-driven decisions and directly seeing their value that they feel motivated to maximise its accuracy and collection. This chicken-and-egg issue can be accentuated by complex reporting tools that make it difficult to derive insights from the data.
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4. Choose key metrics that align with your business objectives
Two main issues hold a business back from success. The first is that the wrong metrics create flawed incentives. For instance, a business focused solely on maximising profit and stock price rather than long-term growth inevitably stalls as R&D fails to produce new products and the C-suite cash out their inflated stock options and leave. This plays out at every level of the organisation, down to the individual employee, such as a salesperson, who might be incentivised to sell as much as possible without considering the customer’s needs. Choosing the correct metrics is an art that needs to be practised attentively within companies.
The second issue is failing to measure; you cannot manage what you cannot measure. Failure here can kill employee motivation. People like to see the tangible results of their efforts, which is why employee incentives and KPIs should not only be realistic and aligned with those of the organisation but be readily available so individuals can know where they stand.
Data can be compelling when it is used the right way. But to do so, leadership must define which metrics matter most to the business and align initiatives and incentives accordingly. Anything else is destined to fail.
What metrics matter most to your business, and how are you tracking them?
Also Read: How to Really Measure Consumer Engagement
5. Enable your entire team to use data — in real-time
Traditionally, data was used only by top management, with a focus on financial data. Then, real-time inventory and resource planning data expanded the focus to include ops data. Today, companies measure everything: from every email sent by sales to the mouse clicks and viewing seconds of every website visitor. This data can assist employees in making the right decisions—but only if it is accessible in a usable form by all roles within the company.
Foster a data-first culture that encourages people to make better and faster decisions in pursuit of the company’s objectives. If sales, for instance, is struggling to meet their quarterly goals, procurement needs to make a snap decision on which supplier to go with, or marketing needs up-to-date insights on last month’s ad campaigns before re-upping their budgets. They need those answers now — not in three days when the data team finally has time to process their inquiry.
The challenge here is not necessarily educating the team on why the data is valuable but rather making it accessible. You need to invest in platforms that provide users with a simple way to obtain information and digest it. Veezoo, for example, uses a conversational approach that provides advanced analytics just by typing in a query.
Certainly, creating a data-centric culture isn’t going to happen overnight, but don’t let that put you off. The long-term benefits far outweigh the initial time and financial investment to get the data at the heart of your company. Great ideas can come from anywhere, so make sure all employees’ insights—not just those with a technical background—are empowered to uncover and leverage data-driven.
Marcos Monteiro is CEO and co-founder of Veezoo. Born and raised in Rio de Janeiro, Marcos moved to Zurich to study mathematics & statistics at ETH Zurich. He specialized in computational statistics and artificial intelligence, researching how the brain encodes information in the primary visual cortex V1 and graduated from ETH Zurich. Together with João Pedro Monteiro and Till Haug, they founded Veezoo AG to make business-critical data easily accessible.