Every company is a data company. With terabytes upon terabytes of data to interpret, business leaders across industries are under increasing pressure to build a thriving data culture.
But according to a recent survey on corporate data initiatives, 74% of companies(opens new window) believe they are inadequately data-driven. Many employees feel the same, with just 25%(opens new window) believing they have the knowledge and skills required to use data effectively.
The situation is often made worse by chronic data silos that prevent employees from finding, interpreting, and sharing key insights.
As modern enterprises continue to invest in emerging technologies, the call to increase confidence in data skills and decrease costly data silos is more urgent than ever.
The real cost of data silos
Data silos arise when information is dispersed among different systems, departments, and applications, leading to a lack of access and information sharing.
This issue is not a novel challenge for organizations. Even before the digital age, employees in different departments would often fail to share information. But with the rise of digital tools and technology, problems related to data silos are quickly compounding.
Poor data quality currently costs organizations close to $13 million a year(opens new window) on average. If left unchecked, that number could become even greater.
Here are some of the ways data and information silos could be holding you back.
- Wasted time and money - In our survey of more than 100 data and analytics practitioners, over half pointed to project delays as a significant factor that negatively impacts efficiency, with 8.5% of annual revenue lost as a result of data and digital skills gaps.
- Reduced return-on-investment (ROI) on technology investments - Without a data-confident workforce to use it, organizations end up investing in technology that delivers little ROI. Business leaders are forced to rely on a handful of senior employees experienced with digital and data tools, leaving opportunities for increased revenue and cost-savings on the table.
- Poor decision-making - In the age of big data, decision complexity has increased by 65%(opens new window). When information is unavailable or difficult to access and visualize, data is incomplete and confident decisions are harder to make.
What does a typical data silo strategy involve?
The task of centralizing and organizing decades of isolated data may seem daunting, but developing a strategy to remove your data silos is critical to building a modern data-driven culture.
A well-planned data silo strategy will focus on centralizing data from various sources to create a data management system that is both accessible and actionable.
This can involve integrating your business applications, removing duplicate or inaccurate data, and enabling your databases to send information back and forth.
Break down data silos by building up skills
A strong culture of skills development is key to removing data silos and sharpening your competitive edge. By providing applied learning opportunities to new starters and existing employees, you can:
- Increase successful implementation of new systems and technologies
- Fully harness the benefits of improved access to data
- Empower employees to leverage centralized data insights
Today, 74% of employees(opens new window) say they are willing to learn new skills to remain employable in the future. To capitalize on their desire to learn, start by identifying your current data champions for a clearer picture on where to focus your efforts.
How to build data champions in your organization
Not every employee needs to be a data analytics expert, but they should be able to understand how proper use of data drives value for the organization and everyone in it.
Here are some steps you can take to begin developing a company culture where employees at every level are encouraged to break down data silos and increase productivity.
1. Identify your current data champions
Data silos proliferate when only a select few team members understand how your data is collected, interpreted, and applied in day-to-day decision-making.
In our work with over 1,000 companies, we have identified three core categories of employees who are routinely involved with a company’s data functions.
- Data specialists - These employees have high levels of data skills and knowledge but typically account for less than 5% of a company’s workforce. Data specialists tend to work in small, centralized data teams and spend a great deal of time putting out fires. They are the most qualified team members for working with data, but are often too busy handling emergencies to be the change agents your company needs.
- Data champions - These employees make up 10% to 15% of most companies and tend to act as translators to bridge the gap between data specialists and the rest of the team. They usually have enough applied experience with key data tasks to be great resources for team members. However, productive cross-functional collaboration with data champions can be limited as it tends to pull them away from other daily duties.
- Directors, managers, and business leaders - These team members oversee key functions within the organization but may lack the data literacy and confidence to access, process, and visualize data efficiently. Usually accounting for 30% to 40% of a company’s workforce, these individuals may manually collect and consolidate data into spreadsheets to help drive business decisions.
Nearly nine in 10 executives already face skill gaps or expect gaps to develop within the next five years(opens new window). In the near future, a handful of data champions simply won’t be enough.
To stay competitive in a digital business environment, data skills will be required at every level and within every department.
2. Assess skills gaps across business units
Once you identify the data champions in your workforce, you can begin to create a strategic plan for company-wide data upskilling to reduce data silos and drive greater collaboration across the business.
Today, it’s not uncommon for companies to have multiple data warehouses, each with its own data sources and platforms. As data ecosystems become increasingly complex to navigate, the main goal of data integration is to deliver clean and consolidated data for a variety of business users.
Review each department to identify the percentage of team members who:
- Work with data more than three times per week
- Use Excel spreadsheets to manipulate data from “raw” data sets
- Create data reports and dashboards
- Use insights from business intelligence tools in their daily work
- Work with a programming language to manipulate data
Employees must feel empowered to locate isolated data and use it to meet the requirements of various stakeholders. Review each business unit to identify which team members are working with data daily, which ones are using data to drive decision-making, as well as those who are still held back by siloed data or a lack of data skills.
With a clearer picture of which team members need the most support to increase their data capabilities, you can work to develop a scalable skills development program that combines the fundamental theories of data analysis with real day-to-day training on your own data platforms.
3. Grow your in-house data champions
If your organization is like most others, data champions may only account for 10 to 15% of your workforce. With the right training, that number can be greatly increased.
Recent LinkedIn data(opens new window) shows that the skills needed for a given position are expected to change and shift by roughly 50% by 2027. Although 69% of organizations(opens new window) are doing more skills building now than pre-pandemic, there is still a large gap between the day-to-day requirements businesses need and the types of skills traditional training routes deliver.
By leveraging the best of data science theory, plus real application on your organization’s tools and workflows, modern training methods, such as professional apprenticeships, can help you:
- Build data skills from day one - Professional apprenticeships train new team members on your own data, metrics, and ecosystem. By offering data apprenticeships at the entry level, you can grow your own data champions while reducing your recruitment costs.
- Offer upskilling opportunities - Data upskilling apprenticeships are designed to help employees expand their data skills in their current roles while reducing internal bottlenecks and increasing capacity among senior data specialists.
- Reskill employees into new data roles - Offer employees the option of developing new skills so they can successfully move into in-demand data roles within the company.
With the ability to meet your employees where they are — whether that’s at the start of their careers, growing in their existing role, or moving into a new one — professional apprenticeship programs can help you build a highly skilled workforce capable of making the most of your data in real-time.
“By upskilling individuals to become data efficient in their varied roles and functions, they could move the business forward and deliver products and services without dependency on the data analytics and science team,” explains Rachelle Rhinehart, Strategic Account Director at global trends forecaster WGSN.
Despite having over 250 in-house experts and data scientists in over 200 countries, leadership at WGSN struggled to embed relevant data skills across the organization. With help from Multiverse, WGSN’s apprentices increased their data skills and their impact.
“A lot of businesses didn’t realize how much we were doing on the data and analytics side,” says Ryan Keane, VP of Data and Analytics. “As soon as they heard that and saw how embedded it was in our forecasting process, it helped us win new business.”
Build your future data champions with Multiverse
In many cases, what feels like a silo mentality is simply a lack of data management skills.
Today’s employees believe the opportunity to learn and grow is the number one driver of a great workplace culture, but only 52%(opens new window) feel their manager encourages the use of work time to gain new skills.
By training employees on real day-to-day data tasks, our expert team at Multiverse has helped companies like WGSN, Citi, and more to overcome their data challenges and elevate their productivity.
We can help close your data skills gaps through apprenticeship programs that drive real results for your business.
Learn more about how our programs can help you build a workforce of data champions.
