Outcomes of Anmut’s Data Valuation:
- Changes your organisation’s data perspective to start treating data as an asset
- Improves the management, monitoring and prioritisation of your data initiatives
- Motivates an organisation to excel in areas identified as strategically advantageous for movement towards industry leadership
- Increases valuable insights and decreases data cost per unit
What is Anmut’s Data Valuation capability?
Anmut’s Data Valuation methodologies combine market leading expertise and technology to deliver an accurate and justifiable valuation of your data. Anmut is the proprietor of four market-leading data valuation methodologies:
These tools deliver a rigorous valuation of your organisations data that is communicable across all levels of a company. They also provide a calculation of the potential value of your data and identification of where value is currently being overlooked.
Each method applies different approaches and technology to deliver an accurate and justifiable valuation of data.
Why is valuing data important?
In a data-driven world, all leading organisations recognise data as one of their most important assets, using it to create competitive advantage. Unfortunately, most organisations don’t treat data as an asset, resulting in mismanagement and loss of value. In order to treat data as an asset it must be inventoried, measured and monitored as with any other asset. Data Valuation is the tool which enables this.
Data valuation alters your organisation’s perspective on data. Instead of viewing data as a problem, it is viewed as an asset, enabling the effective prioritisation, management and monitoring of data. It leads businesses towards a state of data maturity, where data is leveraged effectively to create competitive advantage. Read more on data maturity here.
How does the Data Valuation work?
Anmut has developed four market-leading data valuation approaches:
- Application of a neural network combined with public data to enable a peer group comparison and potential data value analysis. The analysis will reveal the data dependency of an organisation’s value drivers. Most appropriate for publicly listed companies.
- Extension of the market-driven approach, leveraging off of a detailed inventory to calculate value at the dataset level. Most appropriate for publicly listed companies.
- Used to calculate data value by analysing strategic initiatives. Integration of data quality insights with the data requirements of initiatives. Most appropriate for privately held firms.
- Method that calculates the data value with respect to multiple stakeholders, and the value of supporting datasets. Most appropriate for large government/privately held organisations?
Using our partnership with the University of Cambridge, we ensure that all our methodologies incorporate the highest level of scientific rigour to ensure valuations are justifiable and meaningful.