- Søren Kold, Senior Analyst, Ennova



Professional Services


Deployment country:


Business Analytics, Business Intelligence, Predictive Analytics



Ennova is a leading Nordic consultancy company, which delivers fact-based advice to its clients based on the results of large-scale surveys of employees and customers. Founded in 1988, the company has achieved fast growth and now has 80 employees and operations across Scandinavia, making Ennova one of the largest consultancy firms in the region.


Business need:
Ennova needs to perform deep analyses of huge sets of data to provide its clients with valuable insights into their businesses.


For several years, Ennova has relied on IBM® SPSS® Statistics software to prepare survey data for analysis, and to drill down into the results for deeper insights into the engagement and satisfaction levels of departments, teams, and even individual employees.


Enables deep analysis of data to identify hidden trends and assess the effects of employee engagement and satisfaction on important business metrics such as employee turnover, absences and performance. Provides a flexible set of analytical tools that enables Ennova to tailor its services to each client's unique business requirements. Reduces time spent training new Ennova analysts because the IBM SPSS interface is so intuitive and easy to use.


Case Study

Ennova is a leading Nordic consultancy company, which delivers fact-based advice to its clients based on the results of large-scale surveys of employees and customers. Founded in 1988, the company has achieved fast growth and now has 80 employees and operations across Scandinavia, making Ennova one of the largest consultancy firms in the region.

When companies consult Ennova about assessing the engagement and satisfaction of their employees, the Ennova consultants work closely with the client team to develop highly tailored questionnaires. Ennova then conducts large-scale employee surveys, analyses the results, and provides recommendations to its clients' executives on how to increase employee satisfaction within their businesses.


Analysing huge sets of data
At the end of the data collection stage of an employee survey, Ennova receives the survey results from all participants. Since Ennova has many large companies in its client portfolio, including Danske Bank and Nordea, the company must analyse many thousands of questionnaires. In addition to projects for individual clients, Ennova also conducts an annual European Employee Index study, which incorporates data collected from 30,000 participants across 25 countries. The company must perform a deep analysis of this data to reveal hidden patterns within the survey results. Ennova needs to gain a thorough understanding of the data to identify areas of low satisfaction and develop a set of recommendations for its clients.

To manage and analyse all this data effectively, Ennova relies on a suite of analytics tools which combines IBM SPSS Statistics software with a custom analytics solution which the company has developed in-house. The IBM SPSS software is used to prepare the data for analysis, differentiating employees and assigning them to specific pre-defined categories, based primarily on the main factors that motivate them in the workplace.

"Different people have different motivations for going to work," explains Søren Kold, Senior Analyst at Ennova. "For example, some people draw satisfaction from the social interaction they find in the workplace; some are motivated by the opportunity for personal development; some are driven by remuneration or other benefits; some simply find meaning in the work itself; and there are several other common types. SPSS helps us understand which of these broad categories each employee falls into, and this is key to the success of the main analysis phase."


Using deep analysis of data to provide excellent customer service
Søren Kold explains why the IBM SPSS platform is so valuable to the company: "IBM SPSS Statistics is a powerful analytical tool. It reveals hidden trends in the data and highlights areas which require further analysis." Deep analyses enable Ennova to provide valuable insights into the behaviour of its clients' employees and customers, such as strong correlations between employee satisfaction and factors that affect corporate financial results, such as employee turnover, absenteeism and poor job performance. Ennova's analyses highlight the importance of addressing these issues and encourage clients to implement the plans of remedial action that the Ennova consultants recommend.

The powerful data analysis performed by IBM SPSS Statistics enables Ennova to offer a tailored solution to each of its clients. This tailored service is essential to Ennova's success, since there are often stark contrasts between the findings from companies in different industries or different countries. Even within a single company, different departments or business units can have very different priorities, and attract employees with widely diverging types of motivation. These differences are specific to each company, so it is vital to be able to address them in a sophisticated and detailed manner. The deep analysis provided by the IBM SPSS platform enables Ennova to drill down into the data and provide recommendations specific to each business unit and team. Factors such as age, seniority and gender can all be used to understand the behaviour of different groups of people.


Søren Kold explains, "IBM SPSS does not just give us an overview of employee satisfaction in each client's company – it divides the survey participants into different profiles based on their responses. Once we have identified the different types of people within an organisation, we can start to understand them better and work with our clients to design policies that will help to boost their engagement."


Ennova benefits from the software's ease of management. "IBM SPSS has a very intuitive interface, which makes it easy to use and enables us to train new employees very quickly," remarks Søren Kold. In addition, the IBM SPSS platform is widely used by statisticians, analysts and researchers in a broad range of fields. Ennova has found that many new employees are already familiar with the software from previous jobs, or even from their time at university.


The IBM SPSS solution enables Ennova to identify and understand its clients' employees and customers in a very detailed way – not just by company or department, but down to the level of teams and even individuals. As a result, Ennova can help its clients to adapt their business practices to raise engagement where it is lowest and increase the success of their companies.


"If a department achieves an overall employee engagement score of 80, that might be considered very good," explains Søren Kold. "But it could mean that the majority of the people in the department are actually scoring 90, while a small but significant minority are only scoring 30 or 40. The ability to drill down into the data with SPSS and identify the variation provide us with input to identify, target and resolve problems at all levels of our client's organisation."


This reaps valuable benefits, because studies show that more satisfied employees tend to produce better quality work and are absent less frequently. In turn, companies with high employee engagement tend to have more satisfied customers and generate higher revenues.

Boosting employee engagement is also vital to reducing employee turnover, which in turn saves time, effort and resources on training new employees. A recent study for one of Ennova's clients showed that over a four-month period there was a clear relationship between low employee engagement and voluntary employee turnover.


"SPSS enables us to quantify the effect that an increase in employee engagement will have on voluntary turnover," explains Søren Kold. "Imagine a company that has a turnover rate of 10 percent and an employee engagement score of 40. If SPSS determines that the relationship between the two factors has an elasticity of -1.6 (as it did in our recent study), then a 10 percent increase in engagement will reduce the turnover rate to 8 percent. The result is a 20 percent saving in the total cost of turnover for the organisation – and that's the kind of statistic that really gets our clients' attention!"


He concludes: "The results vary from industry to industry and from company to company, but our clients are often surprised that the correlations between employee engagement and financial results are so strong. SPSS helps us show them how important this issue is, and gives them the evidence they need to commit to improvement initiatives. Happier employees tend to create more successful businesses with happier customers – so over the long term, everyone benefits from this approach."


About IBM Business Analytics
IBM Business Analytics software delivers data-driven insights that help organisations work smarter and outperform their peers. This comprehensive portfolio includes solutions for business intelligence, predictive analytics and decision management, performance management, and risk management. Business Analytics solutions enable companies to identify and visualise trends and patterns in areas, such as customer analytics, that can have a profound effect on business performance. They can compare scenarios, anticipate potential threats and opportunities, better plan, budget and forecast resources, balance risks against expected returns and work to meet regulatory requirements. By making analytics widely available, organisations can align tactical and strategic decision-making to achieve business goals.


For more information
For further information please visit ibm.com/business-analytics


Request a call
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ComponentsIBM products and services that were used in this case study.


SPSS Statistics

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