We spoke this week with Corné Brouwers, a recent transplant from Amsterdam to California's Mendocino County.
With 25 years of experience as an Director of Information Technology, System Architect, and Business Consultant, Corné's work has spanned both the business and IT communities and provides insights into an analytics and data strategy.
His career has afforded him powerful and actionable insights into how technology can create data ROI in an enterprise.
We asked Corné Brouwers our 7 Questions on Creating Value from Data. Answers have been edited for clarity and length.
1. What professional experience has led to your understanding on how to deliver data ROI?
What I have noticed is that data analytics projects are started with a very optimistic view: “The data we have is a goldmine. We just have to get the value out of it. Therefore we need to invest in a tool and start some projects."
This mostly happens in companies that are just getting their feet wet. What I have also noticed is the need for a change of mindset.
You have to shift your mindset from merely reporting and dashboarding to digging deeper and analyzing the data. This requires out-of-the-box thinking, data mining and a R&D approach.
2. How does a manager frame a successful analytics project?
A manager should frame an analytics project just like any other project.
This means defining the business case (reasons, costs, benefits, risks) - including a clear scope, a time schedule, project team, communication plan, etc.
The amount of detail in which this framing occurs depends on the corporate culture, but one of the most important items here is scope.
Scope can be defined in terms of ‘what data will be analyzed’ or something more abstract like ‘the purchase order process.' In the case of ‘the more abstract definition,’ it is important to identify the underlying data ASAP after the project is started.
3. How would you prioritize multiple analytics projects with limited or competing resources?
If your company is just starting with analytics go for the quick wins.
Successful baby steps will show skeptical elements within the company what value analytics can bring to the company.
Prioritize from the least complex and shortest time to complete, but make sure the expected outcome has substantial value.
4. What would help executives and stakeholders establish more successful data initiatives? (And how might they take a project off-course?)
When defining a project forget about data. Start with questions or start with complaints, but don't think of solutions yet.
Most employees, including executives and other stakeholders, know the reasons why they did not make some or all of their targets. Write those reasons down and ask questions that get at the causes:
“No time” - Why?
“X takes too long” - Why?
“I always have to check Y or confirm Z before I can do X” etc.
The initiative can zoom in on these problem statements to verify if they are true, demonstrate where process improvement is possible, and estimate how much value improvements might bring.
One of the main reasons executives take a project off-course is by changing scope. Changes in scope should be allowed as long as they are agreed upon. Critically, this is a decision for the project steering committee, not the executive.
5. What's the best way to ensure the business takes actions on the insights that an analytics team delivers?
Communication, communication, communication.
The business should be involved all the way. Primarily as advisory partner in the definition phase of the project. Then, as member of the project team: they are experts that know what they are talking about and are able to verify the data.
Most importantly, they can tell the rest of the business about the benefits of the project. The CEO should do this, too, but the impact of initially skeptical colleagues can be a lot bigger.
6. How do you demonstrate bottom-line value to stakeholders? (How do you make success quantifiable?)
A lot of times it is actually hard to make success quantifiable. For example, sometimes the reason for an initiative is simply to improve the way employees feel about their job.
What’s important is that you think about the measures for success when defining the project. Think about the possible outcomes, and then define what this means for your business.
Preferably, verify these outcomes during the project and not just after. If the outcome isn't what you had expected, then think of the reason why. Learn and improve.
7. What other insights have you learned about creating value from data?
What I have learned over the years is the importance of definitions.
Make sure everyone uses the same definition. This can be challenging when there are different cultures or several business lines within the company.
For example, "What is a Client," "What is a Former Client," "What is the North-East Region?" When exactly do we say the client belongs to a certain region? Do we use visit-address? Invoice-address? HQ-address?
From a business perspective, data definitions seem too simple to even talk about - until you actually start talking about them. Without agreement on definitions, there is the risk of miscommunication and misinterpretation of the results.