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1、Copyright 2023 IIA All Rights ReservedDeveloping a Product Orientation for Analytics and AI11.15V2Copyright 2023 IIA All Rights ReservedWhy is a Product Orientation Necessary?There is one primary reason why organizations need to adopt a product focus for analytics and AI:models simply dont get imple
2、mented often enough.Data scientists often focus on model development,but the deployment process is much broader(Fig.1).There are multiple studies indicating that model deployment rates are low(see recent poll from KDNuggets and VentureBeat article).There is some evidencethat deployment rates are imp
3、roving,but continued improvement in deployment rates is necessary to improve the efficacy of analytics and AI projects.2Copyright 2023 IIA All Rights ReservedTasks that may be involved data and analytics product management:Identification of use cases Development of business cases and ROI Overall man
4、agement of development and deployment schedules Stakeholder relationship management Translation to nontechnical stakeholders Data preparation,integration,and curation Model development oversight User interface/experience design Business process redesign Job definition changes Testing Performance tun
5、ing Integration with existing technology architecture and systems User training and reskilling Ongoing model monitoring and retraining3What Needs to be ManagedCopyright 2023 IIA All Rights ReservedManav Misra is the Chief Data and Analytics Officer of Regions Bank,a financial institution with$163 bi
6、llion in assets and one of the nations largest full-service providers of consumer and commercial banking,wealth management,and mortgage products and services.When he accepted the leadership of data and analytics at the bank,he began to develop an approach to successfully building and deploying analy
7、tics and AI products for the various internal business partners at the bank.Misra hired“data product partners”who are each aligned with one of their business or support unit leaders.They initially connect the opportunities of analytics and AI with business needs.Regions has been employing the produc
8、t orientation for three and a half years.It has been quite successful,with over ten revenue-generating/cost-saving products(with incremental impact in eight figures)and several more for internal support functions.4Product Orientation at Regions Bank(1/2)Copyright 2023 IIA All Rights ReservedMisra no
9、tes the important components involved in the success of product management:The goal must be to address a critical business priority for partners,not to develop a cool algorithm Teams should work with agile methods All team members,and especially the data product partners,must always think about the
10、end userand must implement solutions that are engaging and likely to be adopted by them.All stakeholders should understand that a product requires continued care and feeding.Unlike a project,it isnt a“once and done”effort.Remember that youre also in the promotion business.Misras organization publish
11、es an internal quarterly newsletter that is circulated across the bankto help build awareness and drive demand for their partnership.5Product Orientation at Regions Bank(2/2)Copyright 2023 IIA All Rights ReservedKey Assumptions and PrerequisitesAttributes:1.Data products involve a substantial need f
12、or change in business activities as well as technical capabilities in the proposed system.2.The goal of a product is deployment,not just a pilot or proof of concept.As such,its critical that the system be widely adopted and employed by the intended users.Prerequisites:1.The analytics or AI project b
13、eing considered as aproduct involves significant technical capabilities.If it is easily acquired and installed,it may not need an extensive product focus.2.There is a certain scale to the projects:it affects large numbers of users or customers or has a substantial potential impact on the companys fo
14、rtunes.6Copyright 2023 IIA All Rights ReservedKey Capabilities(1/3)Design Thinking:Design thinking should be the primary approach for identifying needed products and attributes from business strategies and needs.Design thinking can be used with a focus on external customers or on internal users.The
15、output of a design thinking exercise can also provide high-level direction for user experience efforts.UX Design:If analytics and AI teams want their products to be used by customers or employees,they need user experience(UX)design capabilities.Just providing an answer or data-based insight is not e
16、nough.The information from analytics or AI models must be easily accessible,with clear explanations of their implications whenever possible.7Copyright 2023 IIA All Rights ReservedKey Capabilities(2/3)Workflow and Job Design:Successful data products often require participative workflow and job design
17、 because analytics and AI systems often lead to changes in business processes and the jobs of employees(or in some cases customers)who use the systems.These changes may involve only incremental change(as in Lean Six Sigma programs)or more dramatic change(as in business process reengineering programs
18、).Experimentation:Experimentation is another important capability of analytics-driven change,even when the systems that contain the models are intended to be fully deployed into production.Most sophisticated organizations have the ability toincorporate A/B and multivariate testing into their models.
19、8Copyright 2023 IIA All Rights ReservedKey Capabilities(3/3)Collaborative Culture:A collaborative culture is essential for successful product management in analytics and AI;product managers are“ministers without portfolios”and rely on influence,communication,and collaboration rather than authority.O
20、rganizations that dont have collaborative cultures are likely to end up with frustrated product managers and unsuccessful data products.Self-Service Offering:Product-oriented organizations also require a self-service offering for less important analytics projects that can be done by their users or b
21、y business analysts.A product orientation implies that the products are important and of substantial value to their organizations.However,there is still a need for ad hoc reporting and small-scale analysis.Analytics and AI groups should offer easy-to-use self-service tools and provide training in th
22、eir use.9Copyright 2023 IIA All Rights ReservedBecome an IIA Client to Access the Full Brief IIA clients get access to the full Developing a Product Orientation for Analytics and AI research brief online and as a PDF which contains more common obstacles and further details warning signs and remedies
23、.Research&Advisory Network(RAN)clients have direct access to the experts that developed this content and framework with on demand inquires.10Copyright 2023 IIA All Rights ReservedDont go in alone.Let IIA guide your |We work with clients to build and grow their analytics organizations.Benefit from our unbiased,unrivaled network of analytics experts,practitioners and thought leaders.11.15V2