Data governance at Delicato: How a family-run winery is utilizing big data
There is more data in the world right now than there has ever been.
Even in the time it took you to read that, over 13,000,000GB of data was created.
Ian Swanson, CFO at Delicato likened trying to find useful insights in unmanaged big data to attempting to boil the ocean.
For Delicato, a “mom and pop” family run wine business, getting actionable insights is about identifying and managing relevant data that can inform better decision making.
Getting your data governance right is key to reaching your desired goal
If you can answer the following questions, you’re going in the right direction.
- Do you have standard definitions for each data element?
- Do you know who ensures the data is maintained in accordance with the definition?
- Do you know who owns the data and the definitions?
- Do you have a governance process around data management and gatekeepers as to data that is cleansed?
Structuring, defining, and codifying your data turns it into usable information. Further categorization and calculation can begin to turn information into insight. Insights are then what a business can act upon.
A recent Moss Adams webinar highlighted that “Tapping into the potential of your data can deliver major value, but without specialized technology and forecasting tools, you could be missing out on important insights.”
Tools and software can transform a business, but an over-reliance on software too early can prove counterproductive.
Sorting out the data and getting it to a point where it is usable is an important part of the process. Tools can then build upon that data set and present actionable insights.
Data governance at Delicato
The framework Ian implemented at Delicato consists of four key components.
- Leadership buy-in
Data governance is sponsored at the highest level of the Delicato organization to communicate its business value and set expectations for participation and measurement.
- One central governance forum
Delicato has a data governance council as the go-to resource for discussing and communicating data definitions, processes, standards, responsibilities, and ownership.
- Role definitions
People weren’t understanding what was meant by data ownership. Ian relieved the information services (I.S) team of the responsibility for translating and understanding business definitions, requirements, and generating ad hoc reports.
- Self-service with trusted data
Delicato established an interest in self-service analytics with trusted data available to a broad set of stakeholders.
Delicato’s data governance organizational framework
Data strategy, development, and evolution
Ian separated the phases of data usage into 3 distinct eras at Delicato.
| Data 1.0 is fairly rudimentary, with data being used for specific applications. It consists of: | Data 2.0 represents the enterprise-wide use of data. This encompasses: | Moving to Data 3.0 is Delicato’s goal. This era involves: |
| Value: reports to support operations
Constraints: availability of data Organization: departmental Role of the business: operational reporting Focus: report writing and data extracts Time-to-value: months Scope: data from a single application |
Value: refined, governed enterprise data as a trustworthy asset in reports and dashboards
Constraint: performance Organization: centralized Role of the business: Governance and BI dashboards Focus: tools and architecture Time-to-value: years Scope: enterprise data |
Value: agility and innovation
Constraint: imagination Organization: de-centralized Role of the business: self-service analytics and value realization Focus: getting value from data quickly and innovatively Time-to-value: weeks to a small number of months Scope: data from anywhere |
The development of the program has also taken shape in 3 stages.
1. Design
- Determining data governance readiness
- Designing an organizational framework
- Determining decision rights and rules of engagement
2. Pilot
- Defining the data governance charter
- Identifying appropriate pilot projects
- Assembling core working teams
3. Extending
- Launching the data governance program
- Monitoring and refining processes
- Expanding the program
What has the program achieved?
Ian explained that there have been both expected and unexpected benefits from the implementation of their data governance programme.
The creation of self-service business performance dashboards has been one of the expected positive outcomes, with daily updates now on an automated basis.
The level of access is based on the individual’s business role, and contains the relevant data that the employee controls and is measured on. Definitions are standardized across each part of the business.
Reports can be modified and analyzed on an ad hoc basis to suit each individual worker’s needs.
Some of the unexpected benefits came in the form of business integration and leveraging existing data standards. The speed of mergers and acquisitions (M&A) integrations have been improved.
The sales force of Delicato has also been more effective through better alignment and KPI visibility, increasing their market share.
The immediate next step for Ian as CFO is to bring in financial reporting within the same self-service model.
