Developing Foresight from Alternative KPIs

In our previous installment of this series, we discussed the concept of macro analytics and the importance of key performance indicators (KPIs). We suggested the critical need of keeping the intended audience acquainted with historical and current trends that can inform management and strategic decision-makers about the potential future movement of KPIs. Trend and correlation analysis can provide informative insights into the ability of KPIs to offer predictive foresight.

COVID-19, also known as novel coronavirus, offers a unique case study and presents a new set of challenges where every day is critical. Each day of social distancing and self-isolation helps prevent additional infections while also posing mounting economic challenges to businesses, communities and families that depend on the regular cadence of the economy. It is here that a good mix of wisely chosen alternate KPIs can be forward-looking tools to help position organizations and communities to adapt and proactively respond to a situation before it develops into a crisis.

While most agree that KPIs are important in assessing the health of an organization’s performance, it is still important to understand what is actually causing certain KPIs to divert from optimal performance thresholds. In this article, we will examine the concept of alternative KPIs as a means of enhancing your performance insights and creating additional reference points with which to explain the results and assess forward-looking trends for proactive planning and resolution of identified and emerging issues.

It is important to focus on the topic of horizontal and vertical peer benchmarking and analyze the typical factors that form the basis of such analysis. Peer benchmarking is usually undertaken to analyze the competitive landscape in the industry where the firm operates. This is the horizontal review/benchmarking model. An analysis of upstream suppliers as well as downstream consumers form the basis for vertical analysis and review model. To this end, benchmarking the concentration risk of your suppliers in terms of specific geography versus their peers is an important factor to document and analyze. Most importers of raw material are being forced to re-examine these variables in light of the supply chain disruption caused by the COVID-19 pandemic.

Most competitive analysis centers on quantitative metrics, which includes financial performance, performance ratios and general numeric trends related to locations, revenue per employee, same store sales, etc. With the advancement in recent years in the development of various ways to measure qualitative metrics, there has been an increase in available survey tools at our disposal as well as a few well-designed frameworks, such as net promotor score (NPS), to translate qualitative metrics into measurable quantitative metrics. Leveraging data collection and information generation in this way is highly advantageous as many skill sets are on the verge of becoming commoditized through the application of robotics and/or artificial intelligence (AI).

To further promote the concept of assessing qualitative information, the field of sentiment analysis has matured to the point that we now have adequate data as well as robust algorithms to extract information from qualitative survey components and classify them as either a positive or negative experience for the customer. For instance, natural language processing (NLP) is a field within data science dedicated to extracting rich contextual information from customer feedback to give insights into the satisfaction or dissatisfaction of customers.

This is an important dataset that can help an organization identify and improve operational bottlenecks and modify policies and procedures that have had adverse customer experience impact. The majority of this data comes from internal customer surveys collected during the process of customers’ interaction with the company’s products and/or services. To develop competitive intelligence as well as an alternative KPI that measures the customer sentiment of a company versus its peers, Google Reviews and Yelp ratings provide for an excellent source of information, which can be easily utilized using a suite of web-scraping tools available in the public domain. Social media platforms like Facebook and Twitter also provide an excellent source of feedback inventory.

Competitive sentiment analysis is one alternative KPI that can yield industry insights into best practices. Leveraging NLP has the potential to create a wide array of alternative KPIs, among them being headline risk metrics, which can be devised using web crawlers to capture news about a company, its competitors and overall economy in general to develop reputation risk metrics, innovation index and positive/negative mention ratios. Imagine having a macro headline risk metric on your firm’s risk dashboard that gave your management an advance warning about the emerging COVID-19 crisis, which enabled your organization and potentially your clients to prepare better for it. A few weeks of advance warning can make a difference in surviving versus thriving in a time of crisis. These non-traditional metrics had been non-existent in the last century, but a plethora of data and available technology in the twenty-first century now allow us to view company performance from a wide array of lenses.

These seemingly complex behaviors can be better analyzed through the lens of competitive benchmarking to understand what the competition was doing during the time your campaign was live. Were there any competing headlines, or did any negative news from one part of the industry dampen the uplift impact of your campaign? Perhaps your channel mix was lacking a leading competitor, or there is new innovation in the market that you can observe via headline risk metrics that poses danger to your campaign.

The recent history of the Eastman Kodak Company (Kodak) echoes such implications of what can happen when a company mismanages its handling of disruption and alternative KPIs. By resisting the disruption that digital film caused to the industry, and therefore misunderstanding how quick and widespread such digital disruption would become, the company began to see a decline in their net income in the early 2000s. By 2012, the company filed for Chapter 11 bankruptcy. As it relates to this article, we can hypothesize that if Kodak had utilized some of the aforementioned KPIs, it possibly could have realized any issues with its business model and been able to adjust its investment as a digital business.

Alternative KPIs have the potential to help you utilize a vast array of available information, along with the surplus of data extraction, manipulation, enrichment and classification tools, and potentially provide you with a rich set of valuable metrics for your business.

If you have questions or would like more information about alternative KPIs and their impact to your business, please reach out to us at DataAnalytics@dhg.com.

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