Engage Stakeholders and Align Analytic

By Pacific Northwest Data Analytics Leadership Board members including: Adam Grupp, Amie Bright, Brian Peters, Liz Shepherd, Mark Belvedere, Ro Maneyapanda, Russell Walker, Yvonne Yeung, Paul Kelley, Dave Albano, Thuy Le, and Raj Kumar Singh

March 14, 2023 

Stakeholder and executive engagement are crucial for the success of any data-driven initiative[i]. Without the support and cooperation of the business and its leaders, it is difficult to achieve adoption of analytics in any organization. To ensure positive outcomes, it is important to align analytic use cases with business value. When analytic teams focus too heavily on delivering just the data or analysis requested and don’t pay enough attention to the outcomes that teams are looking to achieve, the analyst team’s work can often be ineffective or even irrelevant. In this paper, we have outlined three best practice strategies that help analytics leaders gain stakeholder buy-in and align analytics to business value:

1. Address business needs by aligning with stakeholders through communication, iteration, and feedback

2. Establish communication channels and organizational structures to foster executive engagement and investment

3. Increase the business acumen of analytics teams

By adopting these strategies, organizations can help ensure that their data-driven initiatives are effective and aligned with the overall business goals.

Address business needs by aligning with stakeholders through communication, iteration, and feedback

Analytics teams often gain only a cursory understanding of business challenges and then spend weeks or months developing a business intelligence or data science solution that then fails to provide the right insights. One of the reasons for this is the lack of communication and a feedback cycle to ensure alignment with business stakeholders on what insights are needed and how to adapt the solution to rapidly evolving business needs. Analytics teams should invest in mechanisms that drive better communication and alignment. These mechanisms can come in the form of stakeholder communication paths, intake forms, and project briefs. Even these methods will fail unless trust is built by meeting the most basic stakeholder requirements around tracking data and reporting before doing more advanced analytics work. The following three case studies show how various companies have successfully implemented best practices that connect analytics to business needs.

A large software company produced a scheduling application for company workforces performing field maintenance activities across various industries. The software company developed AI models to optimize scheduling, however, both the product engineers and customers resisted adopting the new models in the software due to competing priorities. Rajesh Kumar Singh, Data Science Director, sought to address the resistance and drive adoption of the predictive analytics capabilities into the field scheduling product. To help ensure that the algorithms met the needs of multiple customers and scenarios, he fostered strong engagement with both engineering and customers through transparency and communication. Data scientists participated directly in customer sessions to gather use cases and pain points which could inform the scheduling recommendation model development. With enhanced engagement between the data science team with both product engineers and customers, the adoption of the AI models in the product design was a success. To learn more, visit the case study at Raj Singh Technology Case Study (pacnwdataanalytics.net).

A large technology company with a digital advertising platform sought to increase their advertising sales revenue while reducing third party advertiser churn. At first, there was limited adoption of analytic insights by groups like sales, marketing, operations, strategy, and partnerships teams. Ro Maneyapanda, Director of Data Analytics for Advertising, sought to increase adoption of his team’s analytics and insights. The team researched internal customer personas and their business needs which contributed to project briefs that articulated the problems, hypotheses, data signals, solutions, and expected outcomes. By writing the project brief and then getting signoff from the internal customers, both alignment on what was needed and commitment to use the analytics increased. To learn more, visit the case study at Ro Maneyapanda Technology Case Study (pacnwdataanalytics.net)

At an online real-estate marketplace company, stakeholders struggled to identify operational and promotional improvement opportunities. With direction from Thuy Le, Senior Manager of Rental Sales Operations and Analytics, data analysts worked with stakeholders to get more buy-in on the rental property transaction reports they were producing. An intake form was instituted that asked who would use the data, how often, and what actions would be taken based on the insights to drive more thoughtful requests from the business. This helped ensure a connection between the analytics, decisions, and business outcomes like rental revenue growth. The analysts iterated on the dashboards with input from their internal customers to ensure they thought through all the questions that might need to be answered. This process allowed the company to better understand their rental sales, marketing, and operational progress and make decisions and changes with greater confidence. As a result, the group was able to grow their business based on the more trusted insights. To learn more, visit the case study at Thuy Le Real Estate Case Study (pacnwdataanalytics.net).

Sometimes trust needs to be earned before embarking on the highest value-added analytics. At a gaming company, an analytics team was focused on interesting data science work at the expense of projects requested by internal business customers that the analytics team considered to be “vanity metrics”. “Vanity metrics” referred to data and reporting that didn’t appear to directly lead to business decisions and action. The team’s leader, Brian Peters, Senior Director of Growth & Marketing Analytics and Data Science, realized the team had underestimated the value of building trust through basic dashboards and KPI tracking. While the metrics monitored may not have been directly actionable by the business, providing the dashboard built trust and adoption interest that helped with acceptance of future advanced analytics projects. To learn more, visit the case study at Brian Peters Gaming Case Study (pacnwdataanalytics.net).

Establish communication channels and organizational structures to foster executive engagement and investment

Survey research by McKinsey, a consultancy, found that the top-rated reason (25% of respondents) for data analytics effectiveness at high performing companies is senior leader involvement[ii]. However, when analytic teams seek to build a more data-driven future for a company they often face challenges getting executive engagement and investment to fund analytics initiatives. Leaders typically are laser-focused on driving top-line performance outcomes. The inertia of status quo decision-making approaches can often get in the way of analytic investments. To combat these challenges, analytic teams can ramp up their communication channels, for example with executive forums/councils, to help drive alignment on how analytics will serve business needs with a positive return on investment.  When communications aren’t enough to ensure adoption, organization structure redesign may be an opportunity. An optimal structure can help bring the right analytic talent close to the business for maximum context. This can be balanced with the development of a central group to execute large initiatives resulting in a winning combination. The following three case studies show how various companies have successfully implemented best practices that gain executive engagement and investment through better communications and organizational structures.

For an example of engaging executives successfully, at a large high-tech company where decisions were historically made with limited insights from data, there was a need for more investments and changes in behaviors to drive the use of data analytics. Amie Bright, the Regional Vice President of Data Strategy and Insights, set up an Analytics Council to govern data management and analytics activities and investments. The Council kept leaders informed and gained their support for investments in areas such as master data, metadata management, data quality, business intelligence, and data science. With the Council’s support, she made small, initial investments in areas such as customer segmentation for sales targeting. The success of these initiatives led to larger investments leading to a more data-driven future. To learn more, visit the case study at Amie Bright Technology Case Study (pacnwdataanalytics.net).

A large online travel shopping company had a market-based approach led by local managers that rarely utilized data but often left hotel rooms they were selling vacant. Chris Nagano, Director of Data Science, sought to improve bookings by setting up a series of communication touchpoints between his analytics team and executives to improve adoption of analytics. Touchpoints included weekly standups, analytic insight newsletters, and monthly forums that included a readout on key investment areas. The increased communication helped the analytical team focus on the business’s most important metrics, increased overall executive engagement, and led to data-driven decision-making that increased bookings and revenue for both the company and its partners. To learn more, visit the case study at Chris Nagano Online Travel Case Study (pacnwdataanalytics.net)

Not all problems can be solved with collaboration alone, some require larger structural changes. A large technology company sought to grow customer engagement and revenue across consumer products. Their centralized analytics team failed to provide the right value so Adam Grupp, Loyalty Program Director, applied a distributed model that involved embedding analytics practitioners within the teams. This helped, but these smaller groups of practitioners couldn’t complete the bigger analytic initiatives required to scale the business and revenue. This led them to a hybrid approach of embedding analytical members within other teams while maintaining a central analytics group responsible for enterprise-wide experiments. This more flexible hybrid approach improved trust in analytics, enabled them to identify and scale their most successful marketing tactics, and ultimately achieve their profitability goals. To learn more, visit the case study at Adam Grupp Technology Case Study (pacnwdataanalytics.net).

Increase the business acumen of analytics teams

Analytics teams often get caught up with the analysis or report they are building without sufficiently understanding business context. A lack of knowledge about business problems, business drivers or the language of the business often leads to analyses that miss the mark in terms of insights. Analysts can combat this issue by learning about the business model, industry challenges, and how functions like operations, supply chain, finance, sales, and marketing create value and KPIs that drive these functions. Another approach is to change mindsets by embedding analysts into the business on a rotation as a way of increasing business acumen. Analysts can experience the business challenges, language, decisions, and communications of business functional roles. This exposure will help them bring a point of view to their work that understands business goals, constraints, and relevance of their analytics to the business context. The following two case studies show how various companies have successfully implemented improvements in the business acumen of analytics teams.

The payments division of a large marketplace company sought to ensure that analytics better influenced product design, features, and performance. The Head of Global Data Science, Mark Belvedere, addressed the challenge of influencing product design by working with his team to use the Five Whys in stakeholder feedback sessions. The “Five Whys” is an interrogative technique that helps participants explore and uncover underlying problems and needs. The technique involves asking questions about why an insight is needed or why business action should be taken. This helped drive insight and accountability on the analytics teams to solve real challenges that drove value for the product. For example, one of the data scientists on the team worked with the payments group that sought to improve purchase checkout efficiency. The data scientist asked why payments failed initially while a portion of them later went through. By asking and analyzing why customers were able to resolve failed payments themselves he noticed that the successful customers usually simply tried again. To address this opportunity, a machine learning model was implemented that automatically tried payments again when they failed dramatically increasing the overall payment success rate without burdening the customer. To learn more, visit the case study at Mark Belvedere Marketplace Case Study (pacnwdataanalytics.net)

An online travel shopping company sought to improve the analytical capabilities that drive travel provider engagement and loyalty. Analysts often misunderstood the business environment and culture due to myopic focus on data and analytics. The VP of Enterprise Data Platforms and Services, Liz Shepherd, helped to address these challenges through rotations and other skill building. For existing engineers and analysts on the team, she leveraged a Partner Services team that regularly interacted with external partners – providing an environment to hone business and communication skills. She rotated people into the group for three or more months for skill-building and then brought them back onto her analytics team. The newly built communication skills and increased business acumen were essential skills for working with the business more effectively. Their analyses and insights more directly addressed business needs due to the close working relationships and better understanding of the business on a project basis. With more analytics adoption, the business saw increased revenue growth through better targeting and engagement of travel partners. To learn more, visit the case study at Liz Shepherd Online Travel Case Study (pacnwdataanalytics.net).

Through the best practices above, including working with stakeholders to address business needs, establishing the right communications and organizational structure, and increasing business acumen, companies’ analytics teams can better direct investments and optimize the value they deliver.

[i] Role of Executive Sponsors in business analytics success – Understanding their influence domains using Deductive Thematic Analysis: Journal of Decision Systems: Vol 0, No 0 (tandfonline.com)

[ii] The need to lead in data and analytics | McKinsey

Published by

Pacific NW Data Analytics Leadership Board

March 14, 2023 on LinkedIn

Companies across industries face challenges in getting the most out of their data and analytics initiatives. Perhaps you have experienced this yourself. This article is the first of a series of six best practice themes. Here, the Pacific Northwest Data Analytics Leadership Board shares three practices that help analytics leaders gain stakeholder buy-in and align analytics to business value. The are: 

1. Address business needs by aligning with stakeholders through communication, iteration, and feedback

2. Establish communication channels and organizational structures to foster executive engagement and investment

3. Increase the business acumen of analytics teams

Each of the three practices are supported by real case studies lived by our Board members. Read on to learn more! 

P.S. If you are a data analytics leader in the PNW and would like to build your network and expand your expertise by sharing knowledge with other experts, visit the PNW Data Analytics Leadership Board website Contact Us page at https://lnkd.in/gMjen5gX . The Board is hosted by Unify Consulting www.unifyconsulting.com with two events each year.