How to Put Critical Questions When Analyzing Skills

I don’t remember who made the quote: “People Make Companies”, but it is well said and goes straight to the point. Before discussing about the detailed skills of the personnel, we have to touch the subject of company assets, but very briefly.  Companies take good care of their funds and because of that use sophisticated financial reporting for visualising the sources of their incoming and outgoing money flows, hoping for positive results, as required by the management.  

”Required by the management” means, that somebody in the organisation has set the targets, because the targets display the performance needs of the organisation and the company has to follow these guidelines in their operations.  Data management follows similar guidelines and in this writing we focus on systematically deploying HR training data by drilling deep into measuring learning issues. 

Ensuring good learning results in companies requires in the long run a systematic approach to ambitious target setting of learning results and full utilisation of collected training scores in Human resources.  By doing so, great opportunities open for companies. Putting all this into practise requires only a few simple procedures for collecting, treating and analysing the gathered training scores.  It is worth doing this, because of the big benefit – a possibility to increase product sales by systematic and targeted training of the employees.

As discussed above, HR training data is comparable to the company’s financial assets, accumulating from various sources.  Data, gathered from training courses designed by different content providers, can be compounded easily in a structured way, without endless work.  The real challenge is in making the training scores commensurate and comparable.  To be able to conclude this, you need correct tools or a toolbox for making scientifically solid comparisons between present, historical datasets giving you a possibility to make valid forecasts. These tools are available in the Boudin Analytics software.

One key element in the commensurate toolbox is a company specific baseline data for training scores, against which all comparisons are made. The personnel needs to have a certain level of skills, for being able to operate efficiently and to be able to bring the business home.  In this exercise both sample data and base line data have to be commensurate for compounding.  There are also strict requirements for base line data quality, which has to be solid in every respect and thoroughly verifiable. In other words, you have to rely on solid base line data for making training score results of different trainings comparable with each other. 

Let’s continue by starting to analyse training score results and observing, how the benefits can be extracted from the massive amounts of data. A comparison of test scores against the company´s base line data helps us to discover in which product, product line, business, or business location the skills of the personnel are not yet in line with set targets. This analysis can be done on a continuous basis, or when required, or needed, as ad-hoc analysis. 

All this is based on company specific, tailored dashboard views, which show you the status of product related skills in every business location with a granularity, which is in sync with your normal financial reporting.  Those locations, where the skills of the personnel are statistically different from the base line data are subjects for further analysis to clarify the reasons for this.  Getting this kind of alerts very early about locations where measures, like some extra training is needed, helps significantly training professionals to provide financially important results. Insights of skills are handled according to the same reporting structure, which is normal in the company’s product sales reporting.  The value of the analysis arises from wrapping of the products with the skills of your personnel.  Training your personnel with a clear product focus in mind for targeting improved product skill scores, results in significant possibilities to increase sales. 

There are many ways to proceed in this process.  We start by asking questions for getting unequivocal answers which ensure possible business benefits.  We like to see increased sales through improved product skills.  To be able to achieve this we have to understand the relationship between the product skills and the product sales.  When searching for relationships between these we can run what-if analyses in our skills pools to find out, how different skills are related with financial results.   When we know the relationships between skills and sales, we can see following valuable benefits arising from our databases by asking following questions:

  • What is the status of skills in the sales organization?
  • Where to make training investments for getting increased sales?
  • What are the estimated increased sales?
  • What is the rate of saturation in training?
  • How does the law of diminishing returns affect the training for different products and   locations?

After going through these critical questions shown above and taking the proposed actions, we can be sure that the sales are not restricted by lack of skills, or lack of training. The sales management doesn’t have to listen to the eternal allegations of training deficits and can concentrate in managing increased sales.

Written by Antti Kurki, Sales, Boudin Oy

Sharpen The Skills

Boudin Analytics Services are designed to enables intuitive monitoring of the skills in your workforce for your Human Resources- and specially for your training professionals. The solution has parameter driven index values for easy setting and adjusting of learning targets for maintaining, developing and keeping track of the skills of your employees. 

The beautifully visualised analytics results give you tailored insights about the current status and possible development scenarios of the skills of your workforce.  You can easily drill down to get all relevant skills related information for your personnel accurate to the different levels of your monthly reporting.  You have also liberal possibilities to make comparisons of your wish of skills related data.

The system also provides you on daily basis with predictions about future training needs for the personnel broken down by different products, product groups, locations, courses, languages, dates etc. on person-based levels.  The automated monitoring system is very helpful for keeping all positions stuffed with qualified professionals all the time. This is very important when we deal with a huge number of sales- and customer service professionals.  These positions are exposed to relatively high churn numbers and it is important to keep these vacancies filled with properly trained employees.  Because you need qualified people with adequate training on continuous basis, you have to be well prepared in advance.

Data visualisation is the graphical representation of information and data. By using intuitive chairs and graphs along with heat maps always showing the data with the granularity of the subtotals of the monthly reporting. The visualisation tools provide an easy and accessible way to see and understand trends, outliers, and patterns in data.  The stochastic analysis gives mainly answers to what – type of questions and the HR – marketing – and sales professionals need to act according to the messages of the gained results.

Today, visualization of data is a key property of analytics to make sense of the millions of data points generated on monthly basis about the product skills development in a company. It helps personnel to see insights on skills by curating data into a form easier to understand, highlighting current scores, seeing the trends and spotting outliers. You can’t stress enough the importance of proper visualisation when planning how to bring the status and the all the different key components of skills development to the forefront of your daily reporting.

Tailored visualisations meeting the needs of individual customers telling those stories that they need to listen to.  This is achieved by removing the noise from the otherwise cluttered data and highlighting the information which is useful for all the involved parties.  However, it’s not simply as easy as just dressing up a graph to make it look better or creating flashy infographics. Effective data visualization is a delicate balancing act between form and function.  

The graphs should be clear and fresh for encouraging the readers of the reports to catch notice of the important issues and act when this is needed.  Graphs have to make powerful points alive for conveying the right messages to the right persons for correct actions.  These persons need to focus for uncovering all the difficult why questions.  The data and the visuals need to work together, and only in close cooperation with the users of the analytics we can create the right analytics visuals to tell the stories intended just for them.

Training Insights service is designed in a way that with a few glances you can understand standing with skills. The visuals are business driven which means that they are product specific ones, and follow the same reporting structures that product financials. The products of your company define which skills your personnel needs for selling their products optimally. The level of product specific skills can be illustrated in many ways. With the help of heat maps and traffic lights it is easy to drill down to the importance of individual skills parameters for sales results on sales outlet, country-, territory-, or sales channel levels on continuous basis. 

It is necessary to be able to forecast the suitability and quality of training materials, and of the training. The quality of the used training content is often not an objective issue.  Many different individuals with their own agendas make daily decisions, what training courses should be used for providing wanted skills for the personnel.  For some functions in the company, like in sales or customer service, the quality of training content can be measured by linking the measured training results with relevant Key Performance Indicators.

Finding a solution for the effect of training and training materials on their functional causality has been quite challenging for a long time.  We use stochastic analytics for analysing the relationships between wanted outcomes and the used training materials. The suitability of the content for its use is tested with a small number of test persons and usable results are at hand immediately after the test population has concluded their tests.  The results are reliable regardless of the distribution of the test scores and there is no need for adding more test objects for reception of a significant result.  Normally, when you look at sales training, you have to wait for some time for the preliminary sales results to appear into the reports.  Now, when analysing the test results with the Content Master service, you can have as immediate report for the test scores for example that the use of the tested learning material for the training of your sales force will increase the sales of a certain product by for example 5% with 85% probability. This makes a   comparison of the quality of different training contents unequivocal and fast. These analytics tools can be effectively used in the content design process to find a compelling training content very fast. 

Written by Kari Hartikainen, Sales, Boudin Oy

When Skills Matter – Keep Them Updated

Today you can evaluate the skills of your personnel objectively by using a math-infused method that looks at the different product related skills using a new approach based on a new set of metrics.

Each product in the company’s selection requires that the personnel has successfully passed several product specific training courses.  Tracking the validity of course results is complicated, because often several individual courses need to be accomplished, before sufficient product skills are present.  The time value of these courses is limited, because they have a predefined validity period.  We have to calculate for each course score their present time values because the learned substance today is less actual, than it was at the time of its complement and some details of the learnings have been forgotten.  

Several course results and their residual values are interdependent but the impacts of the skills on KPIs are independent.  When you Include all these necessary elements into your calculations, this can easily lead to huge number of data points to be actively monitored.

The data-driven approach has revealed dimensions in skills that always have been present in all workplaces but have been well hidden in the complexity of captured learning- and skills metrics in the databases of Human Resources.  

The simple question of: ”What is the level of personnel’s skills?” can reliably be answered only with a data driven approach. This simple sounding question becomes immediately more complex, when you drill down to multiple segments, like, what is the level of product skills in different markets, countries or sales offices.  Multiply these with different language groups, product groups and most important individual key products and you arrive at – reality. Complex reality is the space where we all live. What you need to know changes, whom you need to know changes, and so does what you need to study to prepare for professional life.

Statistical analyses force people to reconsider their instincts.  Through skills data, this becomes even more essential.  The learning specialists have to cooperate closely with their colleagues who are competent in statistics and analytics. They will find new ways of doing their work by giving free speech to the data relying on stochastic correlations without prejudgements and prejudice, confident that the aggregated data will reveal its hidden truths.

For example, the online education company Coursera uses data on what sections of learning material may have been unclear and feeds the information back to teachers so they can improve.  Other companies use analytics to define what is the effect of different course alternatives to work related outcomes, like increased sales or other KPI. 

Yet expertise is appropriate for a conventional world where one never has enough information, or the right information, and thus has to rely on intuition and experience for decision making.  In such a world, experience plays a critical role.  The long accumulation of latent knowledge – knowledge that one can’t transmit easily or learn from a book enables traditionally one to make smarter decisions.

On the other hand, when your company has lots of data at their disposal which you can tap to be used for analytics, you can make better, and more objective decisions.  Thus, those who can analyse their under-utilised data pools better, may see past the superstitions and conventional thinking not because they are smarter, but because they have the data, and they use the data.  

Dr. Erik Brynjolson, a business professor at MIT’s Sloan School of Management and his colleagues have evaluated productivity levels and performances at companies with different decision-making styles and have benchmarked them against competition.  They found out that data-driven decision-making gave the data-guided firms clear advantages.  When this philosophy is adopted into improvement of the personnel’s skills advantages will undoubtedly surface.

With cloud based solutions firms can today easily adjust their amount of computing horsepower and storage to fit actual demand.  Because previous fixed cost have transformed into variable ones, the advantages of scale based on technical infrastructure can be enjoyed by all of us.  What counts today is scale in data.  It is possible to hold and analyse large pools of data and it is realistic to capture ever more of it with ease.  Data holders will flourish as they gather and store more of the raw material of their business, which they can reuse to create additional value also in the field of learning analytics.

Smart and nimble small players can today with SaaS solutions enjoy and offer the benefits of so called ”scale without mass solutions”.  They can have a large virtual presence without hefty physical resources, and can diffuse innovations broadly at acceptable cost.  You just need to be able to enjoy the services based on fresh and innovative ideas and run the analytics on cloud computing platforms. 

Companies, presently using learning data for improved skills based results, have a strong incentive to keep adding and analysing more granular training data, since doing so provides greater benefits and the cost for substantially improved results is only marginal, because of following reasons:

First, they already have the infrastructure in place, in terms of storage and processing.

Second, there is a high value in combining existing datasets processed with new algorithms.

Third, using known data sources in an innovative way, simplifies life for data users.

Using data-driven learning analytics is easy and rewarding.  It gives insight in the value of your company’s learning results data.  Slice and dice the information in a way benefitting you the most.  Bring out the effects of your learning results that many in your organisation have assumed to exist, but only a few have dared to request. Taking the first of five easy steps to learning analytics is gratifying, fun and very interesting. The steps lead you to a new level of skills utilisation.

Written by Kari Hartikainen, Sales, Boudin Oy