September 24, 2021
5
min read

Overheard: Data & Analytics do not generate the expected value!

Given the tremendous focus of enterprises on the topic, and the huge investments… this is an expected frustration. But what can be the root cause…? And how can this be overcome ?

Photo by Ricardo Viana on Unsplash
Photo by Ricardo Viana on Unsplash

In the recent months, several studies and reports are raising the same issue over and over, enterprises heavily invest in Data & Analytics but are still frustrated with the actual outcomes!

A compilation of a few examples (as the list goes on):

  • An ESI Thought Lab survey reveals that “the average return on all AI investments by company is only 1.3%
  • An MIT & BCG report finds that “just 1 in 10 companies generates significant financial benefits with AI
  • Gartner’s last CDO survey reported that “while nearly half (44%) of respondents are now measured on the objective of “ROI from data and analytics investment,” under a third (30%) are successfully meeting that objective
  • An Accenture research found that “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.

An easy culprit in many cases is to blame execution: not enough skills, not the right tools, not the right infrastructure, or even to blame data: quality is getting in the way, we need more data, etc.

But the root cause usually lies in some key aspects having been left out or forgotten in the process:

  • not being clear on what to measure, and being able to measure it
  • not having thought about activation, i.e. integration into operational tools, processes and workflows
  • not having thought about adoption, i.e. users onboarding and trust

Another way to describe though 3 items is with the 3Us: Useful (measurable and measured), Useable (integrated), Used (by users).

Frameworks and people

In order to overcome this, it is key to define a clear framework to be able to frame initiatives, evaluate them, select them, deliver them and ultimately measure their impact…

And keeping continuous improvement in mind, measuring the impacts is the basis to frame further improvements. The cycle starts again!

Such frameworks need to encompass several dimensions. Among the most classic and usual one, you have:

  • Goals of the initiative,
  • Risks implied,
  • Expected costs for build and run,
  • Required data,
  • Skills needed,
  • Dependencies on other initiatives,
  • Etc.

But on top of that, you must also be able to capture, from the very start:

  • The link to the enterprise strategic objectives
  • The associated measures, that will be used to determine success or failure
  • The transformation impact, to start assessing the process changes, the technology changes, and the people accompaniment to be put in place

And most importantly, the target users must be part of the project since its inception, ideally as early as during the ideation phase when initiatives are first described, assessed and qualified.

Indeed, user adoption is critical and requires an early engagement to ensure people are onboard.

Lifecycle

Those frameworks are notoriously very useful:

  • in the ideation phase, to guide users with the right set of questions and through the qualification process
  • in the roadmap phase, to build the ideal portfolio and select the most relevant initiatives based on the company’s ambitions.

But their value is often overlooked for the following delivery phase.

Indeed, I have seen so many cases where delivery teams lose track of the actual goals of projects. And end up focusing on technical aspects, forgetting to build in measurement against expected outcomes, or about the integration within operational processes, etc., leading to with pains, frustration and potentially project failure.

It is therefore key to make sure that :

  • the content of the framework is used as a support along the delivery phase, to ensure that the project is aligned with objectives
  • target users are involved all along, in order to provide feedback, validate adjustments or compromises that need to be made.

Indeed, changes always happen during projects either because of external factors, or because of the learning : about the data itself, about the performance & viability of the modeling, about the processes, about how users deal with the output, etc.

And again, without the ability to relate to a clear frame, it is easy to lose track.

Of course, that frame is subject to change and evolution depending on the learning. It is then key to validate it again with stakeholder — therefore ensuring its traceability and visibility all along.

Once delivery is complete, you now need to monitor the behavior and performance of the initiative over time: costs, qualitative and quantitative impacts — still using that same shared frame of reference.

That dusty Excel spreadsheet containing your ideation canvas, half-filled and sitting in a lost folder since the project kickoff is definitely not enough!

Portfolio and automation

In order to achieve value with your Data & Analytics initiatives, the first thing… is to be able to measure it.

By considering your set of initiatives as a portfolio, and managing them as-is, you are setting yourself up for success!

And by combining the visibility of your portfolio of initiatives with your portfolio of data assets, you are also able to assess the value of those assets, to further encourage and promote their reuse.

A powerful Data & Analytics portfolio management solution helps you manage your full lifecycle, by capturing your value management framework, and engaging users and communities around it and all along the lifecycle.

Connected to your ecosystem of tools, you are able to automate the measurement and are able to analyze the impacts of changes across the value chain.

In conclusion, in order to achieve value with you Data & Analytics program, you really need to manage it as a portfolio!

To help you consolidate, manage and optimize your portfolio of Data & Analytics initiatives and assets, 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!

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