At Next Pathway we have the pleasure of helping global organizations along their data journey. We’ve observed that companies that create new businesses offerings, quickly, are the ones that get in front of technology change.
Putting regulatory requirements aside, there are two main reasons why companies should want to be a data-driven business, (1) to increase operational efficiencies and profitability, and (2) to drive revenue, either through enhancing existing services and/or identifying new business offerings.
With our lens of being a technology enabler, let me share my 5 keys to monetizing data:
- Leadership
- Data Strategy
- Data Manufacturing Pipeline
- Speed of Action
- Continuous Learning Culture
1 - Leadership
Regardless of your organizational structure, senior executive leadership (involvement and support) is essential to driving the data strategy and execution.
Some companies think that all they need to do is put someone in the role of Chief Data officer, and they are done. Far too often we’ve seen the role of Chief Data Officer in name only – these individuals have a great title but no impact on the day-to-day data projects. The CDO is your data custodian; this role is responsible for data governance, quality and reporting. In the ideal world, the CDO is the linkage between IT and the Executive Office.
Effective leadership in data requires serious commitment in time, money, people and technology. It relies heavily on consistent and continuous communication from the executive office to both business units and technology teams. When there are competing priorities, or a lack of direction, business and technology units will be divided – instead of making money, you will lose money and even worse, lose customers.
2 - Data Strategy
Everyone says they have it, but when you look under the covers, most companies don’t have a data strategy, let alone an analytics strategy. The lynch pin to your data strategy is data quality. Additionally, the organizational structure must have clear roles and accountabilities, supported by a solid architecture. These elements are essential to success.
Start with a viable use case, one that is well defined, understood and can receive support from both business and technology units. Doing one project right will allow you to build on success and learn from mistakes.
3 - Data Manufacturing Pipeline
A Data Manufacturing Pipeline acts as the technology foundation that enables the ingestion, tagging and transformation of multiple data sources into a standardized format, ready for analytics. It starts with clean, trusted data. When done right, analytics is not only accurate but extremely timely which is essential for the information to be actionable and meaningful to the end consumer.
A modern data manufacturing pipeline (on-prem, in the Cloud or a hybrid of both) will also allow you to retire legacy data warehouses – they are costly and disparate. Moving to modern technology not only has immediate operational cost advantages but allows for AI and analytics to take place.
Whether you develop your own or use Next Pathway's Data Manufacturing Pipeline, make sure you develop with open standards to allow you to integrate with a variety of data catalogues and analytic tools.
4 – Speed of Action
If you can’t act quickly on your data, then you will have challenges realizing the true revenue potential of being a data-driven organization. This is where your technology, your data strategy, combined with steadfast executive leadership truly converge to make money.
Big Data needs lots of data to deliver meaningful results. The good news is, your organization has loads of data; now the question becomes, how do you use it to make money? We’ve seen organizations spend millions on data scientists, AI tools and models only to take months to collect their data – if you don’t have access immediately to accurate data, you can’t make any insights, and you won’t make the right decisions which means you’ve missed the opportunity to drive revenue through data.
5 – Continuous Learning Culture
Companies will struggle to find the right strategy; very few, if any, get it right the first time. You need to be committed to the long-term vision of being data-driven. This will pay dividends, but it requires committed leadership, constant communication and a culture that embraces change and continuous learning.
