Creating Value from Change and Technology
by Gaby Flores
If there is one constant in the world of Big Data and Digital Transformation, it’s change. Consider the technologies your organization has adopted or retired within the last year; it’s likely there have been some significant changes. At times, it can feel like technology is just another expense - a cost center for your business. Changes come about that are out of your business’ control. Software and systems updates, data source changes, market data increases, and the skillsets of the team evolve. How do you embrace this and create value from change and technology?
At our YesData Insight event Unlocking Big Data Insights, Sonya Gustafson sat down with Wish Bakshi from Capital Power and Spencer Cummings from FERC to find out. Read on to discover our top insights from the discussion.
Don’t overcomplicate it. Wish emphasizes that you don’t always need the most sophisticated or complex tool available. Prioritize usability and practicality in your decision-making.
Stay flexible. You and your team will make mistakes; that’s how you learn. The key is to make mistakes quickly and cheaply. If you’re flexible, it allows for iteration. Taking an Agile approach can help facilitate flexibility. Additionally, Spencer suggests thinking about your technology stack in terms of capabilities rather than technologies. This enables you to stay flexible about what technologies you leverage to meet which capabilities (especially if a technology is discontinued, changes, etc.)
Two Approaches to Benchmarks and Key Performance Indicators (KPI’s)
Benchmarks and key performance indicators are important measurements of business success. They are necessary for these types of transformations because KPIs provide real numerical values that can be used to measure the success of the change.
Wish and his team have built around five key questions:
What is the opportunity cost of not doing it?
Will the end-users actually utilize it?
Can we scale it?
Does it have the potential to get big?
What value can you get from other solutions?
Spencer measures time to insight. If he can improve the time to insight, he can justify the solution to management and win capacity back for his teams.
Be Data-Centric. Wish is a strong advocate for taking a data-centric approach first. Data-centric means treating data as your primary asset and pivoting your decision making in terms of application and analysis around the data. Utilizing data to drive decisions around analysis, interpretation, and information is taking a data-centric approach. Wish recommends doing your data ops work first and letting the data act as the primary driver for any machine learning capability as you move from the descriptive world to the prescriptive world.
Increase your team capacity. Spencer discussed the importance of focusing on initiatives and technologies that can win your team, specifically DataOps and Security, more time and capacity. DataOps is a team of agile, process oriented DevOps, data engines, and data scientists who provide the tools and processes that enable organizations to be data-centric (CIO). By utilizing technology to decrease the amount of tactical work these teams do on a daily basis, he has created opportunities to look towards the future strategically.
Everyone can be a programmer! Spencer explains that everyone can be a programmer. He and his team are turning analysts and lawyers into programmers by providing technologies and interfaces that allow them to sift through data and ask intelligent, educated questions.
If you missed the Unlocking Big Data Insight Event be sure to check it out on-demand!