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62 | GEOSPATIAL STRATEGY ESSENTIALS FOR MANAGERS VOLUME 2 standards unique to handling geospatial data. This can include imagery acquisition practices, field data collection tools, data models and schemas for foundational data layers, and attribute-level data access standards. At the same time, core data standards or policies regarding records retention, data privacy and data dissemination should be adhered to as closely as possible by default. These areas are usually tightly governed, and only rare exceptions will be accommodated. The geospatial strategy implements geospatial- specific data science technologies and learning models that support descriptive, diagnostic, predictive and prescriptive data analysis. Analytics strategy. The complement to a data handling strategy is an analytics strategy which focuses on implementing data science technologies and models to enhance business decision making. On the whole, geospatial technology is an analytics technology—it's simply the extension of data-driven analysis into the geographic realm. That means that to align your geospatial strategy with the goals of your analytics strategy, you need to implement geospatial tools and capabilities that bring the necessary geospatial context to any analytics question that needs it. Often this becomes a battle over tools. The analytics program wants to use its tools for analysis, while the geospatial team wants everyone to use theirs. Assuming the insights derived are the same, this is more a matter of philosophy and preference than anything. The key is whether you're accessing a common, authoritative data source. If not, a priority of your geospatial strategy should be to create a shared data source for spatial analysis purposes that's accessible by multiple systems. Digital transformation strategy. A goal for many organizations is to leverage digital technology to not only improve how they do business, but to fundamentally transform how the organization runs, engages customers and delivers its products and services. For your geospatial strategy to align, you need to bring the unique capabilities of geospatial technology to bear on these transformation efforts. That means connecting new digital workflows and experiences to geospatial data, analysis and visualizations. For example, imagine a utility company in the process of transforming the customer experience by delivering personalized mobile updates in the event of a power outage. The location of a customer's impacted properties is imperative to showing where the outage has occurred, affected areas, restored areas and even estimated restore time. This is where geospatial data and technology's unique value help drive the transformation effort. Your goal in aligning your geospatial strategy is to identify where geospatial technology can add value and build the capabilities necessary to deliver it. In practice, you often see organizations tackle digital transformation through the creation of digital innovation programs. These are incubators for the research and development of new digital experiences. Programs like these can be an excellent vehicle for ensuring better geospatial integration. Work with these program owners to incorporate geospatial analysis and capabilities into the design and proof of concept process. That way, geospatial thinking will be front and centre during digital ideation as opposed to an afterthought. Workforce strategy. A workforce strategy aims to ensure that people with the right skills and competencies are staffed and developed through an ongoing set of human resource and professional development practices and programs. Resourcing and developing geospatial talent is no different. The goal for your geospatial strategy should be to identify gaps in geospatial literacy across the staff complement in your organization and then work to address them within the bounds of the programs. To align your geospatial strategy, look at your organization's programs related to recruiting, skills training, professional development,

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