Data Valuation Analysis
Beslogic now offers a brand-new service : Data Valuation Analysis (DVA)!
This service, offered by our experts in data science and artificial intelligence, aims to maximize the value of your organization's data. Specifically, DVA involves an analysis that will facilitate the best possible use of your data to improve your operational and/or commercial performance.
What is Data Valuation Analysis?
DVA serves to identify how the use of your data can enrich your organization. It is preparatory work to facilitate your innovation strategies by including the value of data in the decision-making process. In a way, it is an ally to the growth and productivity of your organization without being engaging, intrusive, or compromising.
Today, measuring the profitability of data is vital. Between poorly utilized, obsolete, or limiting data, and structured, automated, and well-placed data in the process, there is a 1 to 10 ratio. Consider your data as an underutilized gold mine. Each piece of information and its process that contributes to creating value in your organization is thus studied and adjusted to align with your goals.
How does DVA work?
DVA is a straightforward process. Our experts audit your data systems for a period of 5 to 10 days, including a few days of on-site presence. The analysis work and the recommendations are then produced, and the final DVA report is delivered within one month.
What are the benefits of doing a DVA with Beslogic?
- Save 10 years of R&D to learn how to integrate AI into your company
- More than 10 years of expertise to identify the growth levers of your data
- Selection of opportunities with the highest ROI tested and prototyped
- Directly applicable technical recommendations
- Transforming your data from passive to active
- Optimal and unique valuation of this asset
All compiled in a comprehensive report and supplemented by technical annexes.
How do I qualify my need for DVA?
- At least three of the following criteria apply to your reality:
- Regular growth results over the past 5 years
- Ambitious growth and development goals
- Elaborate processes, the fruit of your accumulated expertise, are at the heart of your value creation.
- This expertise is why your customers are loyal and continue to appreciate the value of your products/services (internal or external).
- Difficulties in qualifying future innovation projects
- Hesitations to innovate in artificial intelligence for the past few months
How do I prepare for DVA?
It comes down to three central questions:
- What are the most redundant information processing in my department / processes?
- What real value do these data/information contribute?
- How are they involved in your value creation processes?
What are the interests of DVA in an artificial intelligence project?
If one of your goals is to integrate artificial intelligence solutions into your organization, you need to understand its deployment first. A successful AI project that operates at full capacity in an organization requires a minimum of 24 months of preparation. If we include constant learning, it is, in reality, a process that continues indefinitely after those 24 months.
Preparing the data is the first phase of any project. Then comes data engineering, meaning the custom construction of enriched information flows, followed by modeling, which means making intelligence intelligent in these new flows, and finally, exploitation becomes effective in step 4.
This is why DVA is essential to evaluate, qualify the feasibility of a project, innovation, or strategic direction towards AI. It will be considered as the specification of a potential AI project.
Finally, DVA guarantees the confidentiality of the data and non-intrusion into your systems. This is a step that will have to be taken once.
Why AI at Beslogic?
For over a decade, we have been working to make our AI R&D applicable to the reality of businesses that want to stabilize and structure a new momentum for growth. As such, our technological and methodological expertise is unique in the market. We believe that AI should adapt to the realities of organizations, rather than impose itself on them, even though technology has always been a major competitive factor.
Maintaining operational and executive sovereignty of organizations while offering them the best existing technological tools on the market is at the heart of our approach.