Data entry and capture. Torough iden- tification and capture of authoritative, appropriate data is the key to success in the first tier of the domain. Te goal for initial data entry is to automate the collection of data as it is being generated at the work- ing level. At most, users will enter data once and it will be pulled into a central data repository, which will allow access for many other people and organizations based on their responsibilities. Te key to making data entry efficient and authori- tative will be identification and adoption of tools that help those at the working level to conduct daily business and satisfy requirements.
Data management system (DMS). Tis second tier will link different datasets across functions, weapon systems and phases of an acquisition program life cycle. It will capture, store and manage data from program conception to divestiture. Te creation of the DMS is the boldest and most complex portion of this vision. Te various Army programs and systems begin generating data as the concept is born and continue through development, produc- tion and sustainment up to divestment.
Within each phase of the life cycle, there are different data subdomains such as
At present, there is no efficient and effective way to store and share the data that leaders need when they need it. We are changing that.
A THREE-PHASED PLAN
Army acquisition needs a plan to implement a holistic data life cycle, with three major phases: data collection, data integration and interpretation, and data maintenance. (Image by sorbetto/Getty Images)
finances, schedules, performance specifica- tions, requirements and logistics. Program interdependencies will require the DMS to identify and link the cost, schedule and performance requirements between the programs. Once these datasets have been developed and linked, Army leaders will be able to use analytical tools to make better decisions.
Data-driven decisions. Te third tier will require the identification and devel- opment of data analysis tools to assist leaders with decision-making and resource planning. Te tools will likely use tech- nologies such as artificial intelligence and machine learning to identify life cycle red flags early—like overspending and production delays. Learning about those indicators early will help program manag- ers deliver quality products on time and
on budget, and will allow senior leaders to make better decisions on current and future modernization programs.
CONCLUSION Effective data management will be the key to efficient business operations in the future. Tis is another case where we bene- fit by looking to industry and emulating their success. If we use all the resources at our disposal, such as artificial intelli- gence and industry’s example of effective data management, we can ensure a future acquisition enterprise in which business processes are truly streamlined, with programs and products practically always guaranteed to be delivered on time and on budget. In the end, our Soldiers will be the beneficiaries.
https://asc.ar my.mil
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