How to - Part III: What Engagement Business Execs Need to Know About Analytics
By Andrew Mazer
ESM Staff Writer
Sponsored by:
- Leveraging the Data
- The Human Capital Dilemma
- Data is Not a Four-Letter Word
- Getting Started With Analytics
- Looking Forward
- It’s All About the Data
- Innovations in Technology
- DIY or Use Experts?
- Some Guiding Principles
How often are you faced with having to make a business decision without the information you need? We know that information today is abundant and cheap, but that’s almost beside the point. The challenge is developing a way to analyze and interpret data to make informed decisions that enhance business performance, whether in sales, marketing, human resources, or operations. The consequences of decisions made in any of these areas obviously can have a major impact on a company’s finances as well.
Savvy organizations invest real money in developing, training and compensating employees, and on focusing on the needs of customers and distribution partners, but they often lack insight into how their investments are paying off or how they could make better decisions regarding people. Reorganizations, new technologies or systems, mergers and acquisitions, regulatory changes and more can profoundly impact business performance. But how can you assess the risk or qualify the potential impact in advance so you can better prepare?
Analytics enables managers and executives to better assess the risks and benefits of impending changes or current programs in order to develop a strategic plan to optimize business outcomes. An analytics initiative measures, tracks and predicts how the human characteristics (knowledge, skills, behavior and attitudes) of employees, customers and other groups can affect your company’s performance.
Analytics is hot these days, as organizations become more aware of the costs of employee and customer turnover, the uncertainties of mergers and acquisitions and the need to ensure that compensation and incentives align with business goals.
By leveraging the data that often sits on your servers, human analytics provides execs with the insights they need to optimize their most valuable resource – human capital and talent. It’s not simply about employees, but customers and distribution partners too.
Analytics requires three capabilities:
- a method for collecting and storing information about employees and customers
- a reporting interface
- statistical analysis tools
- people with the expertise to translate data into actionable insights.
When properly implemented, analytics can calculate return-on-investment (ROI) on programs and initiatives, provide evidence-based advice on how to employ people to drive business and demonstrate how marketing or human resources activities impact the bottom line.
Savvy organizations understand how crucial it is to invest in their customers and employees. In virtually every industry, keeping competitive requires engaged customers and knowledgeable and motivated staff who are attuned to customers and committed to their company’s success. Yet despite spending large sums on customer loyalty and other marketing programs, development, training and employee benefits, many – if not most – organizations remain almost clueless in measuring how effective their external or internal programs are at engaging customers and employees. Furthermore, silos between sales, marketing and HR often stand in the way of better cross-analysis of data to find more meaningful solutions.
The right data needs to be interpreted to gain this insight. Fortunately, most companies are likely already collecting and storing the data that managers need to make confident decisions. As marketing and HR groups are tasked with managing attrition, pricing, compensation programs and strategic initiatives, using this data to improve business practices is an opportunity that can’t be ignored.
In today’s age of Big Data, it’s not surprising that companies look to the big online players like Google, Apple and Amazon and start believing that you have to be a huge entity and perhaps violate privacy to garner meaningful insights into customer behavior or employee turnover. But analytics isn’t inherently large-scale or intrusive. Today’s analytics are simply an evolution of a process that started with employee and customer surveys.
Whereas surveys measure people’s subjective feelings or thoughts, analytics measures and interprets objective metrics regarding behaviors and performance. When done correctly, human analytics demonstrates the effect of people on important business outcomes in a measurable way.
This data can be applied to customers and employees to assess issues such as engagement, service or job satisfaction, likely turnover, the effectiveness of pricing, compensation and incentive programs. Analytics can be used to gain insight into customers and both website and intranet traffic to assess loyalty, satisfaction, levels of interest in corporate messaging and engagement. Analytics can also help HR execs identify the employee initiatives that generate the biggest bang for the buck and deliver tangible, measurable benefits – even identifying employees in terms of temperament, skills, experience, etc. for particular positions.
As your company begins applying human analytics, it’s smart to set simple and modest goals. A full-blown analytics program begins with benchmarking and reporting, then extends to predictive modeling, social analytics and behavioral analytics. When you focus on an issue such as customer or employee attrition, the ability to report on current levels is obviously necessary, but the real business benefits are being able to predict customer or employee turnover based on different factors and variables.
Again, start with simple goals to achieve initial success quickly. Identify a project that can provide a business benefit or deliver an important strategic insight. Initially, if possible, focus on improving a business process rather than some ambitious business transformation. Make sure that the answers to your questions have the potential to improve a business outcome. That will support the business case for deriving a clear value from analytics.
Perhaps you want to see if your customer loyalty, referral programs, or other promotions are yielding tangible goals. Is your training is paying dividends? Do your company’s incentive, recognition, or compensation program relate to performance? Are your recruiting efforts successful in finding the right people? Has your company’s recent investment in technology improved productivity or profitability? If your company promotes managers based on technical proficiency, is that strategy delivering good results? Is your top talent at risk of leaving, and if so, why?
The great promise of analytics is to make better decisions related to such major investments as:
• mergers and acquisitions to ensure that key decisions enhance rather than detract from the engagement of valued customers, distribution partners, employees, vendors and communities
• reorganizations to ensure that the end-result improves rather than undermines performance
• technology investments to ensure they have high levels of adoption.
This emerging arena, known as “predictive analytics,” enables organizations to run what-if scenarios to simulate the impact of various options.
To put analytics into action, you need to access critical data. If your company is small, the data might reside down the hall or with a cloud-based service. In larger organizations, data could be sitting on multiple systems in various formats and require restructuring in order to be interpreted. A bigger challenge is data that is inconsistent or of poor quality. Or, there are times when there simply isn’t enough data, or a sufficiently large pool of participant data, to accurately predict specific outcomes.
While you can’t expect that all data will be perfect, it’s important to determine how accurate and accessible your data is before you launch an analytics program. Without reasonably accurate or relevant data, your analytics initiative will be unsuccessful, or even potentially misleading.
Until recently, companies seeking to employ human analytics would have to invest in a data warehouse to obtain a single view across different data sources. This can be a costly and complex project, requiring standardizing and cleaning data, building a data schema and creating ETL (extraction, transformation, and loading) processes.
Fortunately, cloud-based services have reduced or even eliminated the need for companies to make large up-front investments in a data warehouse. Software-as-a-Service (SaaS) analytics vendors can upload, clean and format company data to the cloud, dramatically reducing implementation costs and deployment times. These services also automate rules and processes to keep data updated and accessible for use on a recurring basis for multiple projects.
Analytics cloud services often employ cognitive computing to enable business managers to use natural language to ask questions like “What is the attrition rate of our sales managers by product line?” Artificial intelligence, which enables analytics systems to learn the relationships of various data points, further enables cloud-based analytics services to deliver results that are responsive to these questions.
Unless your organization is large with a depth of talented analysts, you will likely want to outsource at least part of your analytics program. For example, marketing, sales management, or human resources executives could focus on prioritizing the business issues and specific questions for the initiative. An analytics consulting company could add value by providing statistical modeling and behavioral science expertise, as well as the ability to clean and format data.
A human capital analytics firm can also help optimize your program by bringing a sound technical methodology that’s backed by experience and knowledge of current research methods. With good listening skills and a well-rounded knowledge of organizations and how they can best take advantage of human analytic insights, the specialized firms can help ensure your program is successful.
Note that some analytics firms draw upon multiple technologies or solutions to address specific client needs, while others bring proprietary platforms that enable large companies to rapidly and effectively extract usable insights.
As your company undertakes a human analytics program with the goal of turning raw data into ROI, here are some important tenets to keep in mind:
- Develop a culture that actively uses analytics and data to show who or what is performing or not.
- Begin every analytics program with a clear understanding of what you want to measure and what decisions you want to support.
- Experiment and test to develop data that supports decisions, especially in spending.
- Start modestly to gain simple but useful insights. Then build incrementally to more advanced capability, such as predictive modeling.
- Avoid confusing correlation with causation. Employee satisfaction may correlate with customer satisfaction, but the former doesn’t necessarily cause the latter. You’ll want to test questionable findings by manipulating one variable (while controlling for other variables) and testing its impact on the second.
- Use data to develop actionable plans to drive the right behaviors or actions.
Human analytics delivers value by enabling executives to make informed decisions about where to invest in human capital initiatives. These initiatives should deliver a positive benefit to the bottom line by identifying where investments pay off best, which strategies most reduce employee turnover, or which customer-centric measures deliver the greatest loyalty and satisfaction.
As human resources groups assume an increasingly greater strategic role in organizations, exploiting the benefits of human analytics offers HR a way to gain credibility and visibility by answering core workforce questions in a timely, accurate and confident manner.
Sponsored by:
Engage your employees in a smarter way.
Reward Genius | Point Recognition
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