Does your data foundation support business agility?
Surveys of The Data Warehousing Institute (TDWI) membership found:
- 70% feel the rate of business change outpaces IT capability to keep up
- 38% take up to 3 months to integrate new information for decision making
- 40% need up to 3 months to deliver new views on data after a reorganization
The Value of Time and the effects of Agility
The tables below show the economic effects of agility (data efficiency) as determined by employee productivity and lost data value to support a decision cadence spanning days or weeks. The tables are automatically created from responses to 8 diagnostic questions. For these examples, we used the results of the TDWI Agility surveys as responses to the diagnostic and baselines from which to start. Each of the subsequent two diagrams illustrate enhanced results leveraged by improvements to data efficiency.
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Get your assessment »Diagram 1: Reflects results of the TDWI survey (baseline)
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Hours to Weeks + Fair Efficiency
This diagram sets the baseline for areas of needed improvement indicated by the TDWI survey results. It assumes an organization where 2500 employees spend 20% of their time assembling, interpreting and acting on data. It quantifies the impacts of inefficiencies incorporating new data sources to standard reports or quickly integrating outcomes of organization changes into those reports. This diagram reflects inability of the data foundation to serve the needs of a business for agility.
Diagram 2: Reflects adjustments made to improve data integration
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Hours to Weeks Tempo + Moderate Efficiency
This diagram shows impacts of marginal improvements in the time to integrate new data sources or reflect organization changes to new reports. Using the TDWI survey information baseline (Diagram 1) it assumes that an organization puts tools in place to improve efficiencies in integrating new sources of data to standard reports.
Diagram 3: Reflects adjustments made to improve data integration
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Hours to Weeks + Good Efficiency
This diagram illustrates the effects of moderate improvements in data integration capabilities enabled by automation of integration tasks and a model driven architecture. As the improvements are the result of a business model driving the majority of warehousing and integration tasks the results are sustainable and continue to accrue over time.