Whiteboard Wednesday – Actionable Profitability Analytics

Whiteboard Wednesday – Actionable Profitability Analytics

Profitability analytics should not only tell a story on financial performance, but provide users credible information to write the next chapter.

With the release of my new book Actionable Profitability Analytics, I have had many conversations with thought leaders and professionals discussing the use of analytics to generate more profitable business behaviors. In each of these conversations a common question is asked; “What are actionable analytics?”. My first response is usually to read the first chapter of the book. But to simplify, I did this whiteboard Wednesday video to illustrate the different types of analytics, their purpose, information value, and intended action.

 

Decision Ready Analytics?

Decision Ready Analytics?

A recent Gartner report found that only 18% of business decision makers believe their company’s performance data is decision ready, worse yet is only 22% of finance leaders believed it either.

Finance functions are facing a credibility problem with business leaders in their organizations.  Large complex companies are composed of many departments and divisions that deal with a dizzying array of products and services sold across multiple channels to a variety of customer segments.  Precisely calculating the profitability across all of these data dimensions is a challenge, and deploying these analytics in a manner that drives more profitable behaviors can be overwhelming.  But, the effort is top of mind for CFO’s wanting to provide more expansive performance reporting than just the corporate income statement, and their stakeholders have an insatiable appetite for insights that help them improve the profitability of their businesses.

Aggregated financial reporting, such as the income statement at the company level, only tells the story of what happened.  Those reports only provide an evaluation of performance of the current business model.  The mysteries of why it happened are buried deep within that data.  Business leaders want the answers to vexing questions such as:  Who are our most and least profitable customers?  What lines of business should we focus onto remain competitive? What business lines should we exit?  What products and services require re-pricing to account for increased costs? How do we better manage the primary levers of profitable growth?.   The rear view mirror of past performance reporting is failing to provide them with insights into the economics of their business in order to improve the future business model.

The arduousness of undertaking these types of finance analytics initiatives is not easily evident.  Slick presentations of ‘silver bullet’ analytics applications, ‘eye candy’ charts and visualizations, are usually a company’s first introduction to the field.  But the hard challenging work goes far deeper than the implementation of any technology application.  Success requires a collaboration from across all stakeholders in defining how methodology, data, and technology will come together to provide Actionable Profitability Analytics throughout the organization.  Failure is a likely outcome for the under-prepared and under-informed.  But with only 1 in 5 business leaders believing their current performance reporting is decision ready, the biggest failure would be a ‘failure to launch’, because the strategic demand for better analytics from finance is undeniable.

Armada, IBM and Fifth Third Bank host webinar on Profitability Analytics

Armada, IBM and Fifth Third Bank host webinar on Profitability Analytics

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Financial Services companies around the world are being challenged to identify areas to improve expense ratios and profit margins without sacrificing customer service.  In order to achieve this, they should be evaluating investment and expense management strategies that align to their profitability objectives.

Our team challenges you to look at how your organization is measuring profitability today and to ask yourself whether you are maximizing that opportunity to its fullest potential.

Fifth Third Bank did just that. Recognizing it needed to improve measuring and calculating their client’s profitability to the bank, Fifth Third Bank transformed its processes and systems to provide greater insight into individual client profitability.

During this webcast, Matt Curoe, Director of Corporate Finance and Optimization for Fifth Third Bank, will share his experience overseeing this transformation and the impact these changes have had on their business and decision making process.
If you have any doubt, curiosity, or question abut how you are measuring profitability, please join us for an industry point of view lead by Armada on the importance of having a detailed understanding of your organization’s profitability.

To view the on-demand version of this webinar Click Here

How social media data impacts Retail Bank profitability

How social media data impacts Retail Bank profitability

Banks are beginning to enhance the understanding of customer needs and ultimately improve profitability by leveraging local market social media data.

Retail Bankers have for years completed ad-hoc analysis to determine where they should open a new Branch or sales office or conversely consolidate locations.  They typically worked with their colleague in marketing who assisted with local marketing campaigns and customer outreach across the Bank’s retail business footprint to complete the analysis.  These isolated ad-hoc analytics unfortunately don’t normally jive with the current on-going formal monthly measurement of the existing Branch network and the projected financial plans and forecasts produced by Finance for each location.  As part of their analysis many retail bankers have viewed customers as a part of a large segment and end up treating all customers in that segment the same way.   This provides limited value and is not necessarily the best approach.

Retail bankers understand it’s no longer acceptable to evaluate and forecast branch performance and profit potential based only on existing internal customer data. External data such as local market information available via social media sources is required for true understanding of the profit and growth potential of any branch location or sales office.

Examples of this critical external data include local market competition, population density, median age, median income level, customer social preferences, channel usage preferences, unemployment statistics and number of households—to name just a few. This information must be monitored continually because the local market doesn’t remain static and absolutely affects the profit potential of any branch.  Additionally through the use of social media data the bank is able to understand customers on an individual basis versus in a large grouping thus enhancing each customer interaction by addressing financial product needs based on that customers specific preferences.

Some of the keys to enhancing branch performance and profitability is the ability of a bank branch to acquire deposits, generate revenue, retain customers, and operate efficiently and each of these is at the core of retail banking success. Obviously a more comprehensive understanding of customers by leveraging social data provides key insights for Retail Bankers to optimize marketing campaigns in addition to optimizing each customer interaction.

Incorporating this local market data and combining it with the bank’s internal data provides insight that enables the bank to provide customer facing employees the best information for optimal experiences with their customers.   Banks are also combining both the external data with internal data and applying predictive analytics to enhance their marketing campaigns by targeting the right customer with the appropriate offer at the right time.   This has enabled Banks to deliver more efficient local marketing campaigns that are targeted to the individual driving up the offer acceptance ratios and new account acquisition.

This combination of data also provide a bank’s retail management team with the comprehensive performance view of branches/channels enhancing overall decision-making and strategic management. Many executives have used external data to support branch expansion projects in the past, but unfortunately many have not used this same information to monitor the performance and profit potential of their existing branches.  Developing this discipline as a normal practice can significantly enhance profitability as a direct result of leveraging the external data captured through social media sources.

Is your social media presence based on facts or instinct?

Is your social media presence based on facts or instinct?

Millennials have now overtaken the baby boomers as the largest generation in America. As millennials mature and become the next generation of banking customers, it’s inevitable that banks adapt to their technology needs. Social media engagement and mobile banking are already quickly becoming the standard and not the exception.
Knowing your customer is one of the key components of profitability. Understanding their behavioral tendencies allows you to better service their needs. Equally important is having insight into who your most valuable and least valuable customers are. Differentiating your services and offerings in relation to a customer’s value is key to maximizing profitability. Without this insight you may be mis-allocating resources and under-serving valuable customers while over-serving non-valuable ones.
Today, social media provides banks with a direct line to customers. You can gauge their interest in new services, receive feedback on customer service, and educate them on industry changes. The challenge, of course, is identifying your most valuable customers. Only then can you leverage social media to identify new potentially profitable customers like them.

While it’s easy to tout the numerous benefits of integrating social media into CRM, it’s important to carefully consider costs and risks associated with doing so. Obviously, additional resources will be required to manage content creation, customer engagement and social event coordination. These instantly become additional expenses associated with servicing customers. In addition, we’ve all seen the social backlash a poorly implemented social media plan can have. Just as effective messaging can improve customer retention and acquisition, poorly presented messages can be misinterpreted and enrage the social community resulting in a loss of valuable customers.
The ultimate goal, of course, is to gain valuable insight which maximizes resource allocations, attracts new high value customers and lowers the costs of other customer service activities.

This is why it’s so important to have a cost management system in place that allows a bank to effectively analyze the impact of social media on their cost structure. Customer profitability analytics must exist to properly assess budget allocations, resource allocations, and develop a strategic approach to social customer engagement. Remember, a social media profitability initiative should be based on facts, not instinct.

How to improve the power of cost data with BI

How to improve the power of cost data with BI

BI, or business intelligence, started out as a term that was broad and hard to define but has come to mean tools like Tableau, Qlikview, or even PowerPivot (Microsoft’s pivot tables on steroids) used to crunch big data into pretty reports or dashboards. Every industry is benefiting from these tools thanks to their ability to rapidly sift through huge sets of data from social media outlets like Facebook or Twitter using keywords and hashtags, the cloud, publicly-available sources, and proprietary corporate servers. You can drag and drop BI dashboards almost like you’re making a playlist to see exactly what you need on-the-fly. It was not that long ago that reporting meant waiting for IT to run an overnight batch. Systems would spit out reports that were static and standard with no flexibility. If you wanted something custom, you had better be prepared to wait awhile. And nevermind aesthetics back then.

For as long as Activity-based Costing has existed there has been a power struggle between complexity vs “directional accuracy”, the tradeoff in optimal cost model design required to ensure sustainability and the ability to actually use output data. Despite best efforts to keep complexity in check, costing projects consistently end up producing models with data sets much larger than the likes of Excel can handle. Without tools to easily distribute or interact with the data, often it is not leveraged to its fullest. Horror stories of months and sometimes years long projects to produce data that sits around unused are common. Meanwhile, cost management decisions that could benefit from this treasure trove of data are being made based on misleading or irrelevant existing data, heuristics, or worse: gut feel.

Why has this been happening? Because up until recently, cost modeling tools produced big data, but big data reporting tools didn’t exist.

But with today’s BI tools we can shift that frustration and difficulty with delivering ABC data to successful cost information deployment. This is where BI shines. These mountains of data can now become useful reports and dashboards that are actively used by stakeholders. The information can actually do what it was intended to do 30 years ago. That is to drive change within an organization and help manage costs in an effective way and put an end to the haphazard targeting of the largest expenses in the GL for cuts, the knee-jerk reaction hiring freezes, or less than strategic reductions in force. Keep in mind, getting the full value out of this data will require some information consumer education and an embrace of a proper cost management culture. Accessibility and interactivity improvements delivered through BI will make that task much easier than it has been in the past though.

Information must be accessible to drive wide-scale change. Partnering these two concepts of BI and ABC make that possible. Activity-based Costing had great promise when it was devised, but it wasn’t until recently in the BI lifecycle that it has become possible for cost management to reach its potential.