“Knowledge is power,” and today’s businesses have access to more knowledge, in the form of digital data, to power their growth than ever before. Establishing a data-first corporate culture is key to increasing efficiency and productivity, making informed decisions, improving the customer experience, and managing risks. However, implementing a data-first culture can come with challenges, including resistance to change, data silos and a lack of data literacy among employees.
Anticipating and understanding these challenges is key to addressing them and ensuring the entire team is on board with, and benefits from, a data-first culture. Below, 20 members of Forbes Technology Council detail some of the challenges that can come with creating a data-first culture and share actionable strategies for overcoming these hurdles.
1. Concealing Sensitive Information
Controlling access to sensitive data is hard, especially when that control is applied to professionals who need to use the data. An organization must incorporate limited access into its data-first culture in such a way that professionals expect to only have access to sample data while getting wide-ranging answers from systems that have access to larger amounts of data. In this way, sensitive information is concealed. – Dorit Dor, Check Point
2. Providing Paradata
One challenge is providing paradata—information on how the data was collected—in addition to accurate metadata. In the era of AI, it’s important to not only provide metadata alongside corporate data, but also paradata. The use of blockchain technology may help in this regard. – Jamil El-Imad, Imperial College, Institute of Biomedical Engineering
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3. Ensuring Everyone Uses Data In Decision-Making
One challenge in building a data-first corporate culture is ensuring that everyone in the organization, regardless of their position or seniority, consistently uses data to support their decisions. To address this, all employees should be knowledgeable about identifying and presenting the data that best demonstrates their outcomes and results. – Doron Sitbon, Dot Compliance
4. Overcoming Confirmation Bias
Most people are driven by their intuition, which leads to confirmation bias. It’s easy to agree with data you favor and difficult to accept contrary data. Techniques for combating confirmation bias include ensuring teams have a diverse range of perspectives, respecting one another’s opinions, and, ultimately, working toward building consensus among the group that’s interpreting the data. – Kevin Marcus, Versium
5. Building Around The Customer Experience
A good data-first culture prioritizes and builds around the customer experience. Companies that rely on spreadsheets or shared drives to manage data will struggle to provide a differentiated experience and reap the benefits of AI, which requires a strong data foundation. If the goal is to grow customer intimacy and trust, consolidate your data into a single system designed around them—not you. – DJ Paoni, Certinia
6. Addressing Ethical Concerns
One challenge is the ethical and philosophical debate about amassing so much data about customers. Intentionality of use and placement—understanding where specific data fits into an organization’s goals—will help to alleviate employee and customer concerns. – Arjun Bhatnagar, Cloaked
7. Tracking Duplicate Data
Because of cloud computing, organizations now use a massive amount of data that moves seamlessly across the data estate. While data can move, it can also hide. Even if an organization thinks it knows where to find valuable data, there could be copies of it in other places. To solve this, an organization must adopt a holistic, cloud-native security strategy that acknowledges its own unique security requirements and risks. – Asaf Kochan, Sentra
8. Overcoming Employee Resistance To Change
One challenge in building a data-first corporate culture is employee resistance to change. To overcome this, provide comprehensive data literacy training, foster open communication about the benefits of data-driven decision-making, and incentivize employees to embrace data-driven approaches through recognition and rewards. – Mohit Gupta, Damco Solutions
9. Making Timely Decisions
One challenge is not being able to make timely decisions. Data may not always be perfect, and occasionally, data points may conflict with each other. Settling on a discrete set of KPIs and metrics will help clarify decision-making. Additionally, learn to make decisions without complete or perfect data. In some circumstances, speed is just as important as accuracy. – Ken Ringdahl, Kantata
10. Correcting Previously Unknown Operational Issues
In manufacturing, data comes from many sources and devices. When manufacturers start using data-driven manufacturing, initial numbers may highlight previously unknown operational issues. Leadership must ensure that facing these truths is part of the improvement journey. Emphasizing that transparency and accuracy in data are essential for long-term improvement can help build trust in the process. – Ravi Soni, Amazon Web Services
11. Defining SMART Objectives
Get your team started by defining a goal that can be broken down into small, achievable objectives. These objectives should be SMART (specific, measurable, achievable, relevant and time-bound) and act as milestones for progress tracking. You will also need to regularly ensure that the data is accurate and relevant. Finally, you should invest in training in best practices in data analysis. – Alfredo Ramirez, Vyopta
12. Overcoming A ‘Siloed Data’ Mentality
One challenge in building a data-first culture is a “siloed data” mentality. Employees could be reluctant to share information they consider “theirs.” To combat this, create data governance guidelines and educate employees on the advantages of sharing data and how it may enhance overall performance. – Jas Bagga, Abusiness LLC
13. Incorporating Data Into All Workflows
When building a data-first culture, teams may fear that their input will be dismissed unless it’s supported by data. Yet, a data-first culture equips organizations with insights for customer-centric decision-making, promoting trust in data over intuition or past experience. Organizations must educate skeptics on how they can incorporate data into their workflows so they don’t feel left behind. – Alan O’Herlihy, Everseen
14. Maintaining High Data Quality
Maintaining high data quality can be a significant challenge, as low-quality data can yield inaccurate insights and lead to poor decision-making. Organizations can overcome this by establishing robust data governance frameworks that include data quality standards, regular audits and clear accountability for data management. – Andrey Kalyuzhnyy, 8allocate
15. Changing Reluctant Employees’ Attitudes
Employee resistance to change is a common challenge when building a data-first culture. Resistance can be due to concerns about mastering new tech, an “if it ain’t broke, don’t fix it” mentality, and/or a fear of being replaced. A solution is to appoint employee “change champions” to demonstrate how the new technology will be easy to learn, enhance each employee’s performance and make them even more indispensable. – Carl D’Halluin, Datadobi
16. Storing Data Just For The Sake Of It
Many organizations have built a data-first corporate culture, and that leads to them storing a massive amount of information across their enterprises. The challenge is when an organization stores data just for the sake of it and it gets out of control, contradictory and inaccurate. A data-first company will need to invest in a proper data governance strategy to ensure quality and relevance. – Eric Helmer, Rimini Street
17. Optimizing Data Collection And Management
One challenge an organization may encounter in building a data-first culture is associated with the data itself. For the extracted insights to be truly valuable and useful, the analyzed data should be representative and of high quality. Therefore, conduct an audit of your data and review your current approach to data collection and management. Think of ways to improve it before moving in a different direction. – Yuriy Gnatyuk, Kindgeek
18. Getting Leaders Up To Speed
A key obstacle is a lack of knowledge and skills among leaders, who often don’t have an understanding of new AI technologies or how and for what purposes data could be used. This is especially true for traditional, established corporations such as banks and insurance brokers. To overcome this challenge, start by educating leaders and addressing the question of how the business will change its operating model to use data. – Luboslava Uram, UniCredit
19. Enabling Employees To Access And Query The Data
Too often, organizations hire data and/or analytics teams to interface between employees and data. This creates both a crutch and a bottleneck. To create a true data-first culture, all employees need access to the data and the tools that allow them to ask questions of the data. Large language models are quickly replacing visual querying tools for this, allowing employees to ask questions in natural language. – Sam Glassenberg, Level Ex
20. Fostering Understanding Of The Value Of Data
The biggest challenge—fostering a teamwide understanding of the value of data—can only be solved at the top by establishing a value and reward system for leveraging data. Without this, it will be difficult for groups or individuals to prioritize data literacy, data debt reduction, metric ownership and other aspects of data culture over the functions and activities that align with their core organizational roles and KPIs. – Elliott Cordo, Data Futures
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