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Selling execs on analytics


Top business executives are increasingly concerned about the impact that their companies and strategies will have on corporate results, their employees, the environment, and relationships with key partners. Additionally, pressures from meeting quarterly financial targets, government regulations, and market trends place greater emphasis on informed decision making. That’s where business analytics come in.

Bolstering the importance of analytics to a company’s success, a recent survey from Ernst & Young shows that 81% of companies surveyed believe that data should be at the heart of all decision making, yet only a fraction of those surveyed (23%) have implemented an organization-wide data strategy to enhance decision making. 

Let’s say your company has mastered operational reporting, but believes it’s time to begin investing in predictive or AI projects. Or perhaps your company still integrates data through spreadsheets and hand- coded data movement jobs. In either of these scenarios, investments in people and technology for analytics are sure to create efficiencies, reduce cost, and increase top line revenue.

Despite the proven advantages of being an analytics-driven organization, some companies are hesitant to take the plunge, or do so at a maddeningly slow tempo. When positioning an analytics initiative that requires funding, we have found the following tips to be helpful in making your case with executives who control budgets. 

Understand What Drives Your Boss’ Behavior

Take the time to understand what your boss would most like to achieve with an investment in analytics. Driving revenue is always a goal, but try to identify the metrics that his department or role is responsible for. These could be the things he earns a bonus on.

Revenue is always a solid place to start, but operations people also look at efficiency and cost. For example, we work with an insurance company that was concerned they had too many registered nurses manually reading the medical results and physician notes on every policy application. Using AI and text analytics to automate the reading of the results could reduce the number of people required to slog through every doctor note and test result and reduce policy processing time. 

Focus On ROI

Business objectives that concern senior executives are tied to financial performance. Traditional measures of financial improvement include earnings, profitability percentages, growth of sales, Return on Equity (ROE), and increased shareholder value (for publicly traded companies). In order to successfully engage executive buyers, you must provide a link between your analytics solution and improving business performance. 

Stress That Analytics Tools Can Democratize Data

Management may fear that an analytics initiative will only provide benefits to data scientists or IT developers. 

In one LRS customer success, the customer began first by automating data movement and quality jobs into a single repository, which could then be used for period sales reporting, financial reporting, and supply chain optimization across all lines of business and by all levels of users. The mastering of data was then used for more advanced applications that entailed predictive analytics and AI. But none of that could have occurred without making data available to every knowledge worker who needed access to it for decision making.

Use Language Your Audience Understands

Speak the language of the executive you are trying to promote analytics with. Stay away from technical jargon. Instead, use words and concepts they understand. For instance, if you are pitching your idea to the Chief Financial Officer, frame your discussion around how analytics will help the performance of the office of finance and focus on things like ROE, Cost of Capital, strategic planning, and acquisitions. 

Converting data into insight you can take action on requires a strategy that envelopes your entire organization. Helping our customers with an end-to-end analytics strategy, including where the greatest business value resides, is the LRS sweet spot.

The LRS Big Data and Analytics team has over 20 years of experience in statistics, information management, predictive analytics and AI, and data warehousing. If you are interested in understanding how we can help you find value in your data with advanced analytics, please fill out the form below to request a meeting.


About the author

Steve Cavolick is a Senior Solution Architect with LRS IT Solutions. With over 20 years of experience in enterprise business analytics and information management, Steve is 100% focused on helping customers find value in their data to drive better business outcomes. Using technologies from best-of-breed vendors, he has created solutions for the retail, telco, manufacturing, distribution, financial services, gaming, and insurance industries.