From collecting data to making it actionable knowledge and seeing the impact on your business, it could be a challenging path, especially if your organization has not yet engaged its data-driven transformation or is not fully equipped to power it correctly.
Data is crucial when it comes to business strategy across every sector and is the catalyst for innovation and productivity. Nearly all companies are now investing in Data & Analytics.
The common expression “Data is the new oil” defines data as an essential resource to power up companies’ business. Like oil, data can be an immensely valuable asset if you know how to extract and use it properly. Raw data by itself doesn’t bring any value.
A data asset is any data owned by an organization that, when exploited adequately and efficiently, can generate value for the organization. (source: Laurent Fayet)
The 3Vs have long been used to characterize “big data”:
The complexity of data managed by enterprises has never stopped growing on all those 3 dimensions. On top of that, the business context represented by those data is also evolving faster than ever.
All this makes it extremely difficult to identify the right area of focus, and requires moving forward with structured methods and frameworks to inventory, assess, and build value out of those data.
The value of data assets comes from how it is used within an organization, which determines how important it is, and ultimately what monetary value can be determined.
Indeed, the success of a data-driven initiative is when it impacts operational processes, aligned with the company objectives, which requires the delivered solution to address the 3Us:
Fully supporting and integrating the core business functions and processes, and finally creating measurable value and impacts.
Only 32 percent of business executives surveyed said that they’re able to create measurable value from data, while just 27 percent said their data and analytics projects produce actionable insights.(source: Accenture)
… but companies struggle with this data-driven transformation — to push the business past disruptions and prove the value of data, and it is critical to put in place a comprehensive value management approach to tackle the challenge and achieve the benefits.
Data & Analytics value management relies on 4 strong pillars, in order to address coherently all the various dimensions:
Data & Analytics are an enabler to support the business strategy… and not an objective in itself.
Without this clear frame for alignment, the efforts made on collecting, cleaning, preparing and analyzing data are vain, as they don’t lead to efficient decision making.
The end result is frustration amongst executives on the lack of benefits vs the significant investments in people and technology.
It is therefore critical to ensure that the portfolio of Data & Analytics projects is fully focused on delivering outcomes and as such aligned with the business strategy:
This process of alignment needs to be performed by collecting contributions across the whole organization. In this context, collaboration from the very beginning is required to ensure actionability and buy-in.
It is also mandatory to ensure continued visibility and animation all along the lifecycle of initiatives to not lose track. Moreover, define a continuous process for managing new emerging ideas, qualifying them, and adapting the portfolio when needed.
A Data & Analytics strategy serves as a framework to select the right areas of focus and investments along time, in order to build, manage and deliver the optimal portfolio of Data & Analytics initiatives.
Data & Analytics initiatives require adapted tools and solutions to efficiently manage and use data: capture, store, transform, analyze and visualize them across all their different nature and serving the different needs of all users (from occasional users requiring reports and self-service visualizations to experts requiring advanced analytics capabilities).
And because the technology market for Data & Analytics is very dynamic with frequent innovations, the architecture needs to be designed with flexibility and evolution in mind. You want your architecture to scale and adapt with your maturity, and definitely don’t want to miss the next wave of data technology innovation!
The ideal data architecture also serves as the basis for a broader IT transformation, by connecting with operational systems not only as data sources but also for automated or manual decision making.
The goal of the Data & Analytics architecture is to define the key organizational and operational guidelines to deploy tools, operate and manage data storage and pipelines, and evolve, similar to an urbanism plan for a city.
Deploying and making use of those foundations also requires a large and long-term investment in skills in order to leverage the new technologies and accompany both the data literacy and the methodology evolutions across the organization.
Data & Analytics projects are not one-time, they require a continuous cycle of improvement:
As such, delivering Data & Analytics initiatives that have an impact requires to set up a proper operating model to manage and optimize the portfolio along the full lifecycle, from the emergence of initiatives to their qualification, prioritization, implementation, deployment, etc.
This operating model needs to include the ability to track costs, behavior, performance and finally impacts over time — in order to assess value but also the required maintenance and evolutions: prevent model decay or drift, incorporate additional data, manage evolution in data sources, adapt to changing business context, etc.
Continuous monitoring creates a feedback loop that is key to ensure reliability and accuracy of Data & Analytics initiatives over time, enabling continuous improvement.
The key factors of an effective Data & Analytics operating model:
While companies invest in defining their strategy, in setting the right technology foundations and in deploying an effective operating model, they need to ensure every employee has the skills to understand and use data and analytics. Otherwise, the analytics-driven organization concept might remain in a stage of an idea instead of reality.
75% of employees are uncomfortable working with data (source: Accenture)
The risk of individuals not understanding or not trusting data and analytics is huge, putting at risk the adoption and effective deployment of initiatives: they will either fail to correctly use the available data for decision making or revert to the previous way of operating and ignoring the available data.
Data literacy is also the key for innovation, to enable individuals to trust available data and delivered initiatives, identify and propose new initiatives that generate cost savings, efficiency gains, new revenue sources, etc.
Building trust is critical to achieve value. Combining visibility on ongoing activity, accessible and reusable knowledge, the skills and data literacy of workers enable trust!And with trust, organizations can become fully data-driven and boost their innovation capabilities.
This profound cultural change toward data literacy requires
Now that we have been through the key requirements to achieve value with Data & Analytics, what is the pathway?
The best way is to start with an assessment of your own maturity (or maturities as the responses could depend on parts of your organizations), and build your own plan on this basis.
As a recap, that Data & Analytics plan should always include those 4 pillars:
And deploy a continuous improvement cycle, to enrich, evolve and adapt all there along with the growing maturity, the changing business conditions and new risks or opportunities being identified.
To help you ease and accelerate the deployment of your Data & Analytics operating model, we have designed YOOI, a SaaS platform combining portfolio and assets management in order to optimize the value generated by your projects.
With YOOI, you can build your cockpit to manage all your initiatives, from emergence to deployment. Fully connected with your ecosystem of tools to consolidate information, YOOI is providing alignment with the strategy, visibility on progress and risks, supporting animation of your communities.
Don’t hesitate to contact our team to learn more and schedule a demo!