To extract value from data, organizations must overcome several hurdles. A broad strategy, built on widely supported business cases, is essential. This can be flanked by rapid projects and low-hanging fruit, as this creates buy-in.
Whether data is the new gold, the new oil, or the new fertile ground on which projects grow: extracting added value from information doesn’t just happen. Organizations must carefully consider what they have, what they want and why, while acting quickly is also important.
What appears to be a split at first glance is, upon closer inspection, the best way for organizations to sustainably extract added value from their data. On one hand, a coherent strategy is important, but on the other hand, quick wins and projects to extract value from low-hanging fruit remain equally indispensable.
Broad vision, quick start
“Companies must determine their strategy, but still realize projects quickly,” clarifies Steven Nuyts, Head of BTP Solution Advisory BeNeLux at SAP. “From those quick wins, you can scale up and evaluate.”
Companies must determine their strategy, but still realize projects quickly.
Steven Nuyts, Head of BTP Solution Advisory BeNeLux SAP
Nuyts shares his insights during a roundtable discussion on data strategy, organized by ITdaily. Also joining the table are Yannic De Bleeckere, Head of Pre-Sales at SAS, Adriaan van Geyt, Datacenter Sales Manager for Dell Technologies, Fen Lasseel, Managing Director of Datashift, Brecht Vanhee, Principal Analyst Architect & Delivery Lead at element61, and Caroline Van Cleemput, Regional Director of the recently established BeLux division of Snowflake.
Visible added value across silos
“By quickly identifying a need and developing a use case, you can create internal goodwill to see the value of a broader strategy,” Van Geyt adds. This is necessary, as the success of a strategy depends on the organization’s willingness to embrace it.
By quickly identifying a need and developing a use case, you can create internal goodwill.
Adriaan van Geyt, Datacenter Sales Manager Dell Technologies
Lasseel clarifies. “Silos are still present almost everywhere. Within those silos, collaboration usually runs smoothly. However, to build an overarching data solution or ‘data product’ as part of a coherent strategy, silos must work transversally, and that’s a challenge.”
To build an overarching data solution, silos must work transversally, and that’s a challenge
Fen Lasseel, Managing Director Datashift
Projects can quickly get stuck on that reality. Employees, both on the business side and the IT side, need to know why they should do certain things differently. When they’re asked to integrate silos and invest time and effort in that, but it’s unclear to them where the added value lies, then that project won’t get enthusiastic priority from the employees.
GenAI can accelerate this area, often with overarching use cases that provide clear added value for end users. Think of an internal chatbot that unlocks information for everyone and provides added value,” Lasseel continues. “In this way, a first success case makes clear to everyone what the purpose of the broader strategy is.”
Start small, then expand
Van Cleemput wholeheartedly agrees. “The key to success is starting small and beginning with a few use cases. With a successful and accessible case, you can increase adoption. Then you can scale up with new projects within the same structure of governance and security. This creates a snowball effect.”
The key to success is starting small and beginning with a few use cases.
Caroline Van Cleemput, Regional Director Snowflake BeLux
The small projects are therefore indispensable to get everyone on board. Change management, as it might be called, although Lasseel is allergic to the word. “That shouldn’t become a goal in itself. People often don’t want to change because they don’t know very concretely what they’re going to change. You need to tell a focused story to get people on board.” Successful pilot projects contribute to that story.
Not an IT project but a business strategy
The entire table agrees that this strategy only works when the smaller projects fit within a broader vision, where business is also involved. A successful ad hoc project that is not part of a wider strategy will never be more than that.
This is not about an IT strategy, because those who push data and AI into the IT corner will also be disappointed. Nuyts: “The connection with the business is super important. We organize workshops with clients, for example, to show very concretely what the data plans mean for everyone.”
The faster you involve everyone, the better. For example, all too often data owners and the legal & compliance department are forgotten and brought into the plans too late, Nuyts believes. “The faster they participate, the higher the chance of success.”
But don’t forget IT either
That doesn’t mean a data strategy isn’t also an IT project. “You shouldn’t underestimate the influence of IT either,” Vanhee wants to clearly point out. “An internal IT team can sometimes also resist a transformation where tools and products change. Co-development is our solution: we sit alongside the IT people to build new tools together with them and help them understand where the added value lies.”
You shouldn’t underestimate the influence of IT either
Brecht Vanhee, Principal Analyst Architect & Delivery Lead, element61
“Data will always be accessible,” Vanhee continues. “Even if it’s in an old AS400, there’s always a way to unlock the data. The biggest difficulty from the IT standpoint is helping IT people organize themselves around new tools.”
Back to basics
De Bleeckere takes a step back to add the final piece. He notices that in developing a strategy around data, it’s sometimes forgotten that many employees in a company still lack basic knowledge. It doesn’t matter that through a large project they’ll soon have the ability to talk to all company data in natural language, if they don’t know what the business value of data analysis can be and how to get started with it.
You need to know the customer, of course, and then you can work out how analytics provides added value.
Yannic De Bleeckere, Head of Pre-Sales, SAS
“You need to know the customer, of course,” says De Bleeckere. “And then you can work out how analytics provides added value. In doing so, we train people in the real basics of analytics, in a technology-independent way. We work with workshops and create templates to show real business value.”
Van Cleemput also notes that inspiration across company boundaries is very important. “I’m a fan of user groups, where companies come together and learn from each other. Such a community is very powerful.” For Snowflake in Belgium, she strongly focuses on such initiatives, driven by users.
Interplay of factors
The participants at the roundtable highlight different factors of a good data strategy from all angles. It’s clear that organizations can only extract added value from their data when they can orchestrate a complex interplay of factors. Companies must:
- Set out a clear vision around what they want to extract from their data,
- Link the vision to business needs from the very beginning,
- Not lose sight of IT in the broader strategy, and also involve legal quickly,
- Identify small and quickly executable projects within the broader established framework,
- Concretize the strategy and its added value to employees through those projects,
- Organize practical workshops with everyone to clarify the basics,
- Start small, to grow from there.
A lot needs to happen, Van Geyt also agrees. “You need to identify needs, find use cases and quick wins, ensure quality implementations, provide change management, also around tooling, create internal enthusiasm… But ultimately, someone also needs to bang on the table and say ‘we’re starting.'”
This is the first article in a series of three following our roundtable on data. Click here to visit the theme page with the other articles, the video and our partners.