Structure your content and data to make enterprise smarter, faster, and more profitable.
Many organizations are turning to artificial intelligence to make up for their past sins in poor data and information hygiene. Unfortunately, this strategy is not effective. AI needs good quality data. Intranets, collaboration tools, knowledge bases and document repositories need time and attention to keep them clean, up to date, and well organized. When teams and departments are unable to find the content, resources, tools, support materials and experts they need, the entire organization is impacted. Outside attention, energy, and expertise can help organizations get back on track to meet their employees’ needs and, at the same time, prepare their content for AI.
Business intelligence requires a look at both structured data (to provide accurate and relevant analysis) and unstructured content (to find, reuse and apply the insights from BI reports). A consistent information architecture can solve many standard reporting challenges as well as prepare the organization for advances leveraging machine learning for predictive and prescriptive analytics.
Most organizations are struggling to make search work. EIS varied methodologies solve search issues, from employee needs and customer journeys to conversational AI, all of which rely on effective search.
Knowledge management is undergoing a re-emergence with the advent of conversational artificial intelligence and other AI-related applications. AI tools need to be “trained,” and they are trained with curated and structured knowledge. Our approach to knowledge management is focused on measurable outcomes and change management processes that work in the real world.
Today’s marketing technology ecosystems leverage content, but the content needs to be structured so that it can be used across the numerous systems that are used to support the customer lifecycle. We can help design the information architecture for your content, and then evaluate your marketing technology stack to improve the effectiveness of content operations.
Read our case study about Applied Materials and find out how we did it.
Digital transformations are data transformations, and EIS can assess the data and architecture needed to support your digital transformation in the context of your current capabilities, organizational maturity and short- and long-term objectives.
Information architecture (IA) can be complex and nuanced, but its most important function is to support people as they interact with your organization, to reduce the cognitive load on users and improve efficiencies across the entire value chain.
EIS can help you evaluate your current stack of tools to determine how well your company is leveraging them, identify gaps and redundant functionality, build a remediation plan and execute on that plan to provide a solid foundation for these advanced technologies.
Digital commerce is comprised entirely of data, and if the data is not managed well the entire digital commerce experience can be disrupted.. EIS can help you streamline all of the data and information flows and fine tune the tools that your employees and customers depend on.
Information managers need to be able to quantify the value of information curation, because otherwise justifying its cost can be difficult.
One of the barriers to launching an initiative to develop an enterprise ontology may be concern about how to staff such an initiative.
There was a time when digital transformation was considered a strategic vision for how organizations evolve from a traditional model of customer engagement to the new digitally enabled and data driven go-to-market paradigm.