Spinning Straw into Gold: Using Expertise to Leverage Your Data & Gain Insight into Your Business
By Patrick Long
Stop me if you’ve heard this story before. The Board sets a growth target for the upcoming year. The deal team is assembled from a cross-functional section of the business. They’re on the prowl for the best asset(s), looking for that diamond in the rough. After months and endless nights of proposals and bids, the offer is finally accepted, and a public announcement is made. Sound familiar? Like the Grimm Brother’s fairy tale of Rumpelstiltskin, it seems as if you’ve been given a pile of straw tasked with turning it into gold by morning, or else face dire consequences. The question now becomes: how do you utilize the data housed in that asset in order to manage it and manage it effectively in a way that captures a comprehensive view of your business and supply chain?
When Reality Sets In
It’s at this point where the buyer learns about the new system and data used to “sell the assets”. The management team knew what was “sold” to them. That is the high (and sometimes unreasonable) benchmark. Management must now incorporate the new asset and get it to perform and live up to its potential. It’s now time to understand what was “really purchased.” Can the assets truly deliver on their promises? Where do you begin?
Integration? What Integration?
In the best-case scenario, the CIO has been a part of the deal team and was aware of what is soon to be “inherited” with all its pitfalls and risks. At worst (and most likely the norm), the CIO suddenly inherits a “Rube Goldberg carve-out” with minimal input. It wasn’t a mess on paper and in the negotiations. The seller spoke of separate instances and management reports. What made that work? What was the “secret sauce” behind the model and those visual dashboards? No amount of graphics, charts, gauges, heat maps or dashboards can help when a management team demands answers and the CIO struggles to integrate disparate systems, minimally viable products, flimsy analytics together with existing architecture.
Living Up to Expectations
So, how did Rumpelstiltskin do it? How did the straw get spun into gold magically overnight? The “Rube Goldberg architecture and systems” are pieced together with vague promises of a strategic overhaul in years to come. The data feeds start up and, suddenly, daily inventory starts flowing. The asset team mumbles abstractly about “this nuance and that nuance” with the data. No one has the mindset to appreciate the nuances. The experience walks out the door when sales-side representatives leave the room and suddenly you have the proverbial keys to the car.
What do the numbers mean? Daily end-of-day inventory, estimated custody transfers, certified inspection reports, bills of lading (BOLs), lab reports, vessel reports…how do you make sense of it all?
Stabilize, Fight for Accuracy, Consistency
Just like the King who demanded that the Princess spin straw into gold again and again before marrying her, management will demand consistency with the result. The first fight is hand-to-hand combat—to lock down data sources and ensure that the base level of transactions is accurate. Develop and have confidence in the numbers only after implementing health checks and monitoring processes as backstops to prevent breakdowns (or at least identify them quickly when they occur). Plan for success but expect challenges along the way as resources develop new habits around new processes. Set up health checks to catch issues before they manifest and become larger and more expensive (time and money) to correct.
Paying the Price: Having to Give Up Your First Born
At the conclusion of Rumpelstiltskin, the (now) Queen had to give up her first-born if she didn’t answer his arcane riddle. Just as she was settling into her new life, she was revisited by the hasty decisions of the past. The same malaise can creep into any integration.
As the acquisition stabilizes, it becomes clearer to the business about the performance of the recently acquired asset and how it’s fitting into the larger portfolio. Needs change. No longer is management content with just baseline transactional inventory data. That’s now the given. At this point, the data should be molded to begin unlocking secrets.
Resist the “quick, easy magical silver bullet” to solve all your data needs for purported insight into the future. Instead, as management starts to change questions from “what” into “why” and “how”, use data to support your resources and empower the business. Let data drive conversations and challenge preconceived notions of how the business works. The data should be stable. Rely on it and trust it. Let analytics drive new hypotheses. This can help draw new correlations that you (and the management team) didn’t know existed.
Unlocking the Secrets & Insight
In our example of the asset integration, move beyond the tactical daily imbalance conversation. Let the data trend shed insight into behavior of customers.
For example, take note of truck rack liftings. Marry in the pricing data and use the liftings to determine the price sensitivity for customers. Do lower prices drive more business? Do higher prices drive away more business? Chances are you don’t truly understand your buying levers for customers. The data will undoubtedly surprise you to understand which customers are more sensitive (and which ones aren’t) to prices.
Look for consistency and trends with respect to imbalances. Do they signal process improvement needs because the correlation can be pinpointed to specific resources? Do they signal the need for work orders and justifying capital improvements to gauging and meters? Let the data drive new areas for continual improvement.
Whatever the insight, rely on the expertise of your team to drive the business. Make the data work for you. Doing so will unlock the secrets for a successful integration.
About the Author:
Patrick Long is a Director in Opportune’s Process & Technology practice. Patrick has over 20 years of experience in providing clients with energy trading and risk management, packaged software implementation, trading and risk processes and business process automation. Patrick leads the BI initiative within the firm. He focuses on applying BI tools (e.g., Spotfire and Tableau) to client data in order to allow proper insight for management around both upstream and downstream business issues. Prior to joining Opportune, Patrick worked in the energy consulting trading and risk systems practice at Accenture where he managed multiple project teams through the entire process of software selection to successful implementation of trading and risk management systems for energy trading entities.