Collect the best data, hire a Data Scientist and profit. Sounds easy enough right?
The strategy behind becoming a data driven organization may sound simple, but it can often be difficult to implement. However for the organizations that have taken the risk and benefitted from it, their leaps of faith are consistent.
Here’s a common scenario: A company’s data is siloed between departments. Not only do the departments collecting data avoid collaboration, but the employees who analyze this data are also in a different department. This leads to massive misunderstandings, late reports and missed opportunities.
Many companies are familiar with this ordeal. Aberdeen Group Research found that 44% of executives believe they make critical decisions with inadequate data due to internal segmentation.
Luckily, while every company’s data is different, the steps to unraveling this mess and becoming a data driven organization are the same.
The 3 Leaps Organizations Must Take
Everyone wants to be driven by data except for those it would most affect.
Data has a lot of potential to boost the bottom line, but granting widespread access to data also significantly affects the focus of many jobs. While available tools have become more intuitive, employees need clear reasons why accessing this data matters.
This leads us to the first and most important leap an organization must take:
1) Give employees accountability for the bottom line as they understand it.
Many organizations take this step after they’ve secured a business intelligence solution or other reporting tool.
The problem with this approach is that employees are forced to use tools they don’t understand, that don’t align with their workflow and turn out to be downright wrong for the job’s responsibilities as they understand them.
Before investing in new tools, cultural change must take place. In the same way that data sets come with degrees of value, a company’s culture must contain the right values to drive change. These values include:
- Transparency to focus on data that affects the bottom line, not data that supports an opinion
- Collaboration to leverage the company’s full talent pool
- Individual growth within the vision of the organization’s future to demonstrate how each employee’s success contributes to the whole
The process is often referred to as “buy-in” for a software solution, but its purpose isn’t only to gain a stakeholder’s investment.
Each department contains siloed experts, so the solution must cater to their needs. The values of those experts must be well understood in order to prioritize what the software solution will do. The goal isn’t to convince them how great a new BI tool will be, but instead to show them how their work will be better recognized through using the tool.
The conversation around “buy-in” must cater to the information each employee needs to make high-quality work even easier.
Once employees are motivated to work with the data, the next leap is to make an investment:
2) Centralize data as a single source of truth and stick to those metrics from the bottom up.
By this step, employees are clear on how they affect the bottom line and their values and key performance indicators (KPIs) are present within the system. The metrics used to track performance are clear as day for everyone that gave “buy-in”.
When it comes to structuring the system, keeping everyone on the same page should be top priority. Companies may discover at this point that new positions are required such as a Chief Data Officer, and that the right talent for the job isn’t within IT or the most profitable department but instead a linguistics specialist outside the company.
There should be plenty of time reserved for developing the project’s core team. The stage of finding the right talent to execute the project will likely take the longest.
Once the team has centralized the data, priorities should be to:
- Continually update data to maintain one reference point
- Secure the system with strict regulations through data governance policies
- Focus on the data that closely impacts the bottom line
Knowing how to formulate the right reports and basing discussions around data allows everyone to keep up with how the organization changes.
The final leap comes down to both common sense and loyalty from everyone involved:
3) Guide gut decisions based on the insights that come to light.
At this stage employees are able to bring new insights into their daily work and IT has verified the solution is live and running correctly.
By now not only has the company’s frontline focus transformed, but also the direction of high-level supervisors and key decision makers.
However the organization is destined to change, it must come from the way employees internalize their KPIs and the direction organization leaders take in response. Professions such the Data Scientist are continually evolving and have shown that the potential for transforming an organization with data will only grow.
C-level executives may feel it is standard practice to make gut decisions, but now the data will be monitored for quality. The results could sometimes go against the instincts that brought the company to where it is today.
With the benefit of clear insights come clear arguments. Leaders will still need to make those gut decisions, but now they can make them with data-driven mindsets.
About the Author: Julia Scavicchio is an editor with Better Buys, a trusted authority for delivering unbiased, expert insights on the software and technology that businesses rely on.