Background
Infographic

Six Hurdles of Modern Data Teams

A data team’s value is only as clear as the data they operationalize for the business.

Download the eBook
Hurdle One

Data Collection

Yes, gathering data is essential to your business. But In order for data collection to be effective, it must be relevant, timely, and high quality.

44%

Only 44% of data & analytics leaders reported that their teams are effective in providing value to their organization.

Source: Gartner CDAO Effectiveness Diagnostic

hurdle1

The Symptoms

  • Inaccurate, excessive, and irrelevant data collection

  • Too much complexity that doesn’t align to strategic goals

  • Unnecessary risk with data privacy and compliance

The Remedies

  • Complete a comprehensive data audit to identify areas of improvement

  • Identify and document a data strategy that maps to overarching business goals

  • Document and communicate your data governance standards to ensure adherence to privacy and compliance standards

hurdle2
Hurdle Two

Data Silos

Silos are a dreaded word, especially when it comes to datasets

47%

The number of people who report that silos are their biggest problem when it comes to gaining insights from data.

Source: Treasure Data Research Report 2023


The Symptoms

  • A lack of collective insights across the organization

  • Inaccessible data, outside of what’s available in one’s own department

  • Inconsistency data formats and structures

  • Higher costs to manage, consolidate, and store data 

The Remedies

  • Document specific data sharing principles and practices

  • Conduct a technology stack audit, specifically focused on tools that serve data collection needs and goals 

  • Regularly review data tool and technology costs

Hurdle Three

Data Quality

High data quality is essential for generating valid insights, making informed business decisions, and achieving strategic objectives.

<50%

Number of companies that are confident in their internal data quality.

Source: LinkedIn B2B Institute data


Group 5

The Symptoms

  • Inaccurate, inconsistent, and outdated data

  • AI-generated insights that don’t reflect observed customer behaviors or aren’t in line with current market trends

  • Diminished engagement, conversions, or revenue

The Remedies

  • Conduct a comprehensive customer data audit

  • Create a streamlined process for regularly updating and cleansing datasets

  • Train and monitor AI-driven outputs to ensure AI models learn from high-quality and diverse data 

Group 7 (2)
Hurdle Four

Data Literacy

Being able to read, analyze, and communicate data effectively is what sets successful companies apart.

78%

Amount of US leaders who consider data literacy essential for their teams’ daily operations

Source: DataCamp’s 2023 State of Data Literacy Report


The Symptoms

  • Low (or no) engagement with data tools

  • A tendency to make decisions based on gut feeling rather than data-driven evidence

  • Possession of data but no clear insights or conclusions made based on it

The Remedies

  • Document a unified vision and language for data usage

  • Provide customized data management and analysis training for employees at all levels, in all roles

  • Adopt tools that are intuitive, are easy to use, and help foster a data-driven culture  

Hurdle Five

Org Design

Having a thoughtfully-structured arrangement and coordination of teams, processes, and tech within your company is the key to maximizing your data.

25%

Number of organizations that do not have centralized customer data management teams

Source: 2023 Gartner Market Survey Report

Group 6

The Symptoms

  • Lack of effective collaboration between data scientists and analysts

  • Ambiguity in responsibilities, leading to overlaps or gaps in data management tasks

  • Variability in data handling and analysis methods across different teams

  • Data strategies that do not align with overall business objectives

The Remedies

  • Identify whether your data team should be centralized or decentralized, based on your business needs

  • Have clear and consistent alignment and communication with clearly defined roles and responsibilities

  • Document a unified data strategy that guides all data-related activities

Group 8
Hurdle Six

Culture & Leadership

Without proper leadership, data can only go so far. Emphasizing the importance of data in strategic decision-making across all levels will lead to better outcomes.

Top 3

Culture challenges & accepting change are considered to be one of the top three roadblocks to successful data and analytics initiatives.

Source: 2023 Gartner CDAO Study

The Symptoms

  • Overemphasis on surface-level metrics, as opposed to deeper behavioral analyses 

  • Absence of personalized experiences due to a lack of in-depth data analysis

  • Lack of priority on data-driven innovation, like strategies, technology, and training

The Remedies

  • Invest in data technology and ecosystems that support a comprehensive data strategy

  • Conduct regular trainings and workshops focused on data utilization and analysis

  • Embed data scientists across various teams to improve data fluency across the organization