Data Culture Methodology
Evolving the analytical maturity and data management of large companies.
A DCM
Combining artificial intelligence and collective intelligence to generate Expanded Intelligence DCM (Data Culture Methodology) is a methodology that is part of our consulting program and is fundamental in the process of understanding and training our clients.
Intelligence that surprises
The methodology is focused on evaluating and proposing strategic changes so that companies evolve their analytical maturity and develop a Data Driven culture. Based on more than a decade of AI and Analytics projects and on Agile Methodologies, Design Thinking, Lean and Growth Hacking, applied to digital transformation, DCM maps and indicates improvement paths to boost results.
How it works
DCM uses a 5-level scale to understand the current maturity of customers, proposing specific courses of action to move up a level.
The first analysis involves assessing internal processes, technological tools and the soft and hard skills available, generating recommendations and proposing tailor-made actions, always considering each client’s specific current situation
The Analytics maturity improvement plan includes various actions, depending on the desired objectives. Some of them are:
Creation of data office and establishment of organizational policies and guidelines to support it.
Definition of cultural intervention actions to promote a data culture at all levels of the organization.
Drawing up a training and personal assessment program to train employees in Data Driven techniques and tools.
DCM levels
EXPONENTIAL
- State of the art data-based management.
- Systematic data collection and enrichment.
- Decisions executed automatically or semi-automatically using AI with high level transparency.
OPTIMIZED
- Collecting and enriching data from sources with high quality and speed.
- Automatically generated predictive and prescriptive clippings and analyses.
- Decisions based on robust metrics.
DEFINED
- Indicator-oriented data collection.
- Decisions based on monitoring and visualization systems, collegiate decisions.
ADHOC
- Most Brazilian companies.
- Data collected without a data-oriented information architecture.
EMPIRICAL
- Chaotic environments, no data collection.
- Individualized empirical decisions.
Some companies may be at more than one level simultaneously, depending on the maturity of each sector. For example, a company may have HR at a high level, while sales does not yet have an established data culture and is at a lower DCM level.
Global and national clients
Partners
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Talk to our experts.
Let’s find out together your company’s level of analytical maturity and how to optimize your results with efficient data management.
Data Culture Methodology
Evolving the analytical maturity and data management of large companies.
A DCM
Combining artificial intelligence and collective intelligence to generate Expanded Intelligence DCM (Data Culture Methodology) is a methodology that is part of our consulting program and is fundamental in the process of understanding and training our clients.
Intelligence that surprises
The methodology is focused on evaluating and proposing strategic changes so that companies evolve their analytical maturity and develop a Data Driven culture. Based on more than a decade of AI and Analytics projects and on Agile Methodologies, Design Thinking, Lean and Growth Hacking, applied to digital transformation, DCM maps and indicates improvement paths to boost results.
How it works
DCM uses a 5-level scale to understand the current maturity of customers, proposing specific courses of action to move up a level.
The first analysis involves assessing internal processes, technological tools and the soft and hard skills available, generating recommendations and proposing tailor-made actions, always considering each client’s specific current situation
The Analytics maturity improvement plan includes various actions, depending on the desired objectives. Some of them are:
Creation of data office and establishment of organizational policies and guidelines to support it.
Definition of cultural intervention actions to promote a data culture at all levels of the organization.
Drawing up a training and personal assessment program to train employees in Data Driven techniques and tools.
DCM levels
LEVEL 1 - EMPIRICAL
- Chaotic environments, no data collection.
- Individualized empirical decisions.
LEVEL 2 - ADHOC
- Most Brazilian companies.
- Data collected without a data-oriented information architecture.
LEVEL 3 - DEFINED
- Indicator-oriented data collection.
- Decisions based on monitoring and visualization systems, collegiate decisions.
LEVEL 4 - OPTIMIZED
- Collecting and enriching data from sources with high quality and speed.
- Automatically generated predictive and prescriptive clippings and analyses.
- Decisions based on robust metrics.
LEVEL 5 - EXPONENTIAL
- State of the art data-based management.
- Systematic data collection and enrichment.
- Decisions executed automatically or semi-automatically using AI with high level transparency.
Some companies may be at more than one level simultaneously, depending on the maturity of each sector. For example, a company may have HR at a high level, while sales does not yet have an established data culture and is at a lower DCM level.
Global and national clients
Partners
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