Tag Archives: Alvin Toffler

Competing on Analytics: A Follow Up to Thomas H. Davenport’s Post in HBR

CompetitionIf 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?

DavenportSo 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?

FixMoving 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.

Related links

Solution Brief: The Intelligent Data Platform

Related Blogs

Is Big Data Destined To Become Small And Vertical?
Big Data Why?
The Business Case for Better Data Connectivity
What is big data and why should your business care?
Twitter: @MylesSuer

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Driving Third Wave Businesses: Ensuring Your Business Has The Right To Win

TofflerAs adjunct university faculty, I get to talk to students about how business strategy increasingly depends upon understanding how to leverage information. To make discussion more concrete, I share with students the work of Alvin Toffler. In The Third Wave, Toffler asserts that we live in a world where competition will increasingly take place upon the currency and usability of information.

In a recent interview, Toffler said that “given the acceleration of change; companies, individuals, and governments base many of their daily decisions on obsoledge—knowledge whose shelf life has expired.” He continues by stating that “companies everywhere are trying to put a price on certain forms of intellectual property. But if…knowledge is at the core of the money economy, than we need to understand knowledge much better than we do now. And tiny insights can yield huge outputs”. 

Driving better information management in the information age

information age

To me, this drives to three salient conclusions for information age businesses:

  1. Information needs to drive further down organizations because top decision makers do not have the background to respond at the pace of change.
  2. Information needs to be available faster which means that we need to reducing the processing time for structure and unstructured information sources.
  3. Information needs to be available when the organization is ready for it. For multinational enterprises this means “Always On” 24/7 across multiple time zones on any device.

Effective managers today are effective managers of people and information

information

Effective managers today are effective managers of information. Because processing may take too much time, Toffler’s remarks suggest to me we need to consider human information—the ideas and communications we share every day—within the mix of getting access to the right information when it is needed and where it is needed. Now more than ever is the time for enterprises to ensure their decision makers have the timely information to make better business decisions when they are relevant. This means that unstructured data, a non-trivial majority of business information, needs to be made available to business users and related to existing structured sources of data.

Derick Abell says that “for (management) control to be effective, data must be timely and provided at interval that allows effective intervention”. Today this is a problem for most information businesses. As I see it, information optimization is the basis of powering the enterprise through “Third Wave” business competition. Organizations that have the “right to win” will have as a core capability better-than-class access to current information for decision makers.

Putting in place a winning information management strategy

If you talk to CIOs today, they will tell you that they are currently facing 4 major information age challenges.

  • Mobility—Enabling their users to view data anytime, anyplace, and any device
  • Information Trust—Making data dependable enough for business decisions as well as governing data across all business systems.
  • Competing on Analytics—Getting information to business users fast enough to avoid Toffler’s Obsoledge.
  • New and Big Data Sources—Connecting existing data to new value added sources of data.

Some information age

siloedLots of things, however, get in the way of delivering on the promises of the Information Age. Our current data architecture is siloed, fragile, and built upon layer after layer of spaghetti code integrations. Think about what is involved just to cobble together data on a company’s supply chain. A morass of structured data systems have vendor and transaction records locked up in application databases and data warehouses all over the extended enterprise. So it is not amazing that enterprises struggle to put together current, relevant data to run their businesses upon. Functions like finance depend largely upon manual extracts being massaged and integrated in spreadsheets because of concern over the quality of data being provided by financial systems. Some information age!

How do we connect to new sources of data?

At the same time, many are trying today to extend the information architecture to add social media data, mobile location data, and even machine data. Much of this data is not put together in the same way as data in an application database or data warehouse. However, being able to relate this data to existing data sources can yield significant benefits. Think about the potential benefit of being able to relate social interactions and mobile location data to sales data or to relate machine data to compliance data.

A big problem is many of these new data types potentially have even more data quality gaps than historical structured data systems. Often the signal to noise for this data can be very low for this reason. But this data can be invaluable to business decision making. For this reason, this data needs to be cleaned up and related to older data sources. Finally, it needs to be provided to business users in whatever manner they want to consume it. 

How then do we fix the Information Age?

fixing

Enabling the kind of Information Age that Toffler imagined requires two things. Enterprises fix their data management and enable the information intelligence needed to drive real business competitive advantage. Fixing data management involves delivering good data that business users can safely make decisions from. It, also, involves ensuring that data once 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.

We need at the same time to build the connection between old data sources and new data sources. And this needs to not take as long as in the past to connect data. Delivery needs to happen faster so business problems can be recognized and solved more quickly.  Users need to get access to data when and where they need it.

With data management fixed, data intelligence needs to provide business users the ability to make sense out of things they find in the data. Business users need as well to be able to search and find data. They, also, 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 and put it together and do it from different sources at different times. Simply put this is about data orchestration without any preconceived process. And lastly, business users need the intelligence to automatically sense and respond to changes as new data is collecting.

Tiny insights can yield huge outputs

payoffs

Obviously, there is a cost to solving our information age issues, but it is important to remember what Toffler says. “Tiny insights can yield huge outputs”. In other words, the payoff is huge for shaking off the shackles of our early information age business architecture. And those that do this will increasingly have the “right to win” against their competitors as they use information to wring every last drop of value from their business processes.

Related links
Solution Brief: The Intelligent Data Platform
Related Blogs

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