If you ask a CIO today about the importance of data to their enterprises, they will likely tell you about the need to “compete on analytics” and to enable faster business decisions. At the same time, CIOs believe they “need to provide the intelligence to make better business decisions”. One CIO said it was in fact their personal goal to get the business to a new place faster, to enable them to derive new business insights, and to get to the gold at the end of the rainbow”.
Similarly, another CIO said that Big Data and Analytics were her highest priorities. “We have so much knowledge locked up in the data, it is just huge. We need the data cleaning and analytics to pull this knowledge out of data”. At the same time the CIOs that we talked to see their organizations as “entering an era of ubiquitous computing where users want all data on any device when they need it.”
Why does faster, better data really matters to the enterprise?
So why does it matter? Thomas H. Davenport says, “at a time when firms in many industries offer similar products and use comparable technologies, business processes are among the last remaining points of differentiation.” A CIO that we have talked to concurred in saying, “today, we need to move from “management by exception to management by observation”. Derick Abell amplified upon this idea when he said in his book Managing with Dual Strategies “for control to be effective, data must be timely and provided at intervals that allow effective intervention”.
Davenport explains why timely data matters in this way “analytics competitors wring every last drop of value from those processes”. Given this, “they know what products their customers want, but they also know what prices those customers will pay, how many items each will buy in a lifetime, and what triggers will make people buy more. Like other companies, they know compensation costs and turnover rates, but they can also calculate how much personnel contribute to or detract from the bottom line and how salary levels relate to individuals’ performance. Like other companies, they know when inventories are running low, but they can also predict problems with demand and supply chains, to achieve low rates of inventory and high rates of perfect orders”.
What then prevents businesses from competing on analytics?
Moving to what Davenport imagines requires not just a visualizing tool. It involves fixing what is allying IT’s systems. One CIO suggested this process can be thought of like an athlete building the muscles they need to compete. He said that businesses really need the same thing. In his eyes, data cleaning, data security, data governance, and master data management represent the muscles to compete effectively on analytics. Unless you do these things, you cannot truly compete on analytics. At UMASS Memorial Health, for example, they “had four independent patient registration systems supporting the operations of their health system, with each of these having its own means of identifying patients, assigning medical record numbers, and recording patient care and encounter information”. As a result, “UMass lacked an accurate, reliable, and trustworthy picture of how many unique patients were being treated by its health system. In order to fix things, UMASS needed to “resolve patient, provider and encounter data quality problems across 11 source systems to allow aggregation and analysis of data”. Prior to fixing its data management system, this meant that “UMass lacked a top-down, comprehensive view of clinical and financial performance across its extended healthcare enterprise”.
UMASS demonstrates how IT needs to fix their data management in order to improve their organization’s information intelligence and drive real and substantial business advantage. Fixing data management clearly involves delivering the good data that business users can safely use to make business decisions. It, also, involves ensuring that data created is protected. CFOs that we have talked to say Target was a watershed event for them—something that they expect will receive more and more auditing attention.
Once our data is good and safe, we need to connect current data sources and new data sources. And this needs to not take as long as it did in the past. The delivery of data needs to happen fast enough that business problems can be recognized as they occur and be solved before they become systemic. For this reason, users need to get access to data when and where they it is needed.
With data management fixed, data intelligence is needed so that business users can make sense out of things faster. Business users need to be able to search and find data. They need self-service so they can combine existing and new unstructured data sources to test data interrelationship hypothesis. This means the ability to assemble data from different sources at different times. Simply put this is all about data orchestration without having any preconceived process. And lastly, they need the intelligence to automatically sense and respond to changes as new data becomes collected.
Some parting thoughts
The next question may be whether competing upon data actual pay business dividends. Alvin Toffler says “Tiny insights can yield huge outputs”. In other words, the payoff can be huge. And those that do so will increasingly have the “right to win” against their competitors as you use information to wring every last drop of value from your business processes.
Solution Brief: The Intelligent Data Platform