Positively busy at the moment at work and in winter sports, I am happy about rich snow this winter. I come from Lapland, close to the see, from Keminmaa. In professional life, my biggest interest is innovation, and Metropolia University of Applied Sciences helped on sharpen my focus. Here, in response to my alma mater’s request, I tell a story of my search and discovery.

The Start of the Career

After graduation as a Bachelor in IT from Turku University of Applied Sciences, I worked some time for Teleste Oyj in Turku. My history in Teleste started with a Bachelor’s thesis, which I successfully completed and continued my work for the company. After the company cost cutting and organizational change, I started looking for work in Telecom and very specifically in Ericsson. At that time, my friend who studied with me in Turku was working for Ericsson. He told such exciting stories about his assignments at Ericsson that I started to be envious. In 2009, I got a position in Ericsson. That was not an easy time to get an IT job. Wide networking with professionals, previous experience, and practical engineering knowledge helped to land my dream job.

In Ericsson, we were building a 3G network. Our team delivered a very successful project that offered our customers early access to technology which for that time achieved massive data rates. At that time, our team within Ericsson was one of the first to work with this technology, and I was a Service Engineer. I traveled the world and worked for 9 years in this position, continuing as a Solution Architect. After 9 years, I decided to educate myself. I heard many of my colleagues talking of a Master’s degree in Metropolia, saying nice things, so I decided to look more precisely at this option.

Studying Master’s Degree Program

In daily work, I am closely working with innovation and innovation framework in Ericsson, as it is my ticket to something really interesting. Before I could make a decision if it would be best to work fully with innovation, or I can use a few hours every week, I decided to look for education. After googling all types of programs, my search always brought me the Master’s program in Industrial Management at Metropolia for studies in innovation. After reading a detailed description of the program, it was easy to decide. It explained well what this degree is about, where, who for, and what to do; even what the school day will be. When I looked at the content of the studies, I was very excited and decided to take this very program. It was precisely the thing!

Before the Industrial Management curriculum, I was not sure if I should pursue a management role. But after my Metropolia classes, I realized that it is very interesting and something for me.

Using my Networks to Test my Interest in Management Role

The studies were tougher that I expected, in a demanding way; but I love challenge, it is very good for me as a person. After my Master’s graduation, I started to apply to the management roles inside Ericsson. At the time, I was the sports club chairman at Ericsson Finland as well as a company management employee representative in our local organization. So, I used my network to discuss this role. My activities help me to look at different angles at the business that I am working in: employee management, health and safety, sports clubs management, the company hobby clubs with social activities, etc.

I went to my network and discussed with them that I am now interested and feel ready for a management role, and I am very serious about it. Soon after, we had a mentoring session with the top management in Finland, and after a while, they announced a position in Service Management. I got it. In this role, I have a wide responsibility in services delivery including budget, first hand customer negotiations, and developing customer experience and customer satisfaction. I can master all these areas (taught to us in Metropolia). This is a great leverage of many different types of positions.

For Innovation You Need to Know the Substance

As my next step, I need to maintain and develop the innovation understands and skills, and work on the substance. For innovation, if you discuss it with our instructor Thomas Rohweder, you need to know the substance. No matter how creative you are, a firm professional ground and understanding of real life is needed. In other words, you need to bring your own professional skills into innovation – it could be IT, machine learning, anything related to industrial mega-trends. Importantly, you also need to understand business and finance. So, before my next step upon the managerial ladder, I decided to develop operations excellence, take responsibility over the finances, and master the substance – all these efforts will bring results.

When I started in Service Management, I remember how I was surprised with my service contracts. What is this service? How many customers do we have for it? It was a surprise to hear that this service exists for only one customer, and it was especially developed for this one customer, co-designed, co-created – through innovation, value creation, customer experience – all the topics from my studies! (Some departments, e.g. Sales, at that time did not even realize these concepts, but just made it happen). Now it is one of the foundations for successful service. That area is critically important to make customer dreams and wishes happen.

On the personal side, since I came from Lapland, it is common there to go camping and hiking. This is simply my passion to go hiking, being in the nature. My other hobbies are sports and music. Before the engineering career, I was very excited about music. So, when I first heard about innovations, it sparked my interest. I realized this is the field where I can be creative to combine applied sciences, practice, engineering – and creation. In the past, it was common to combine science and creativity; the people of Renaissance all loved music, science and arts.

Combining Innovation and Development

I am interested in a role that allows a big degree of creativity and freedom to innovate. However, if it is purely innovation, such as full-time innovation coach, it creates a lot of costs. In any traditional company it is ‘no-no’, and it is tricky to have such position. So, I want to focus on combining innovation and development. Here, freedom to innovate is super important. It allows to think and create clever efficiency gains such as with automation or create value with targeted investments by validated innovation ideas. I believe that one can cut costs only within limits but with systematic innovation create value where only sky is your limit. In service delivery organization, we need to innovate on everything, even in Sales, as we need to sell good things. If there is an innovative idea, we make it happen.

My dream job is to innovate and coach young professionals, as I was coaching PhD students from Aalto, it was wonderful, and PhD students from Stockholm in Ericsson Innovation Awards competition. I would also like to have a role in innovation management, and link innovation routinely to real life operational challenges, and make it work, and make good business out of it. There is a lot of creativity in this – very exciting!

The Next Step?

One more thing. All my instructors – Zinaida, Thomas, James – all suggested that I should go for a PhD. This is something that I am still thinking about. However, as I am very clear about what I want, innovation is my passion and an innovation management role is my focus. This is what truly makes me tick.

 

 

Photos by Zinaida Grabovskaia

Juho Vieruaho is currently a Service Delivery Manager at Ericsson who graduated as a Master’s of Engineering in Industrial Management from Metropolia University of Applied Sciences in 2018.

Mikä on palveluyrityksen tärkein resurssi? Prosessit, joilla palvelua tuotetaan? Työvälineet, joilla palvelua voidaan tarjota asiakkaille? Palvelukonsepti itsessään? Palvelu on prosessi, joka koostuu lukuisista eri tekijöistä ja usein monimutkaisesta palveluekosysteemistä. Palveluntarjoaja voi palvelunhallinnan, toisin sanoen erilaisten prosessien ja toimintojen avulla varmistaa, että sen tarjoamat palvelut todella tuottavat arvoa asiakkaille. Kuitenkin, koska palvelu syntyy useimmiten ihmisten välisenä toimintana, on palvelutuotannossa merkittävässä roolissa palvelua tuottavat ihmiset. Yritys voi panostaa vaikka kuinka paljon prosesseihin ja julistaa toimivansa asiakaskeskeisesti, mutta jos se unohtaa palvelua tuottavat ihmiset, tärkeimmän resurssinsa, jää yrityksen menestys puolitiehen.

Tyytyväiset työntekijät, jotka asennoituvat työhönsä innostuneesti, tuottavat tutkitusti parempaa palvelua kuin työhönsä leipiintyneet kollegansa. Hyvä asiakaskokemus taas lisää asiakasuskollisuutta, mikä vuorostaan näkyy positiivisena tuloksena viivan alla. Asiakaskokemuksesta huolehtiminen on toki palvelualoilla oleellista, mutta oman henkilöstön hyvinvoinnista huolehtiminen on kriittistä.

Juha Tuulaniemi korostaa myös ihmisten merkitystä palvelukokemuksen muodostumisessa kirjassaan Palvelumuotoilu (Talentum 2011). Tuulaniemen mukaan ”asiakaspalvelu on vaikuttavin näyttö siitä, miten brändi kohtelee sinua”. Toisin sanoen brändi ei pelkästään näy, vaan se koetaan ja tämän takia olisi ensiarvoisen tärkeää huolehtia, että työntekijöillä on edellytykset palvella asiakkaita hyvin. Miten siis varmistaa, että työntekijöillä on edellytykset menestyä työssään?

Suorituskyvyn edellytyksille ei ole olemassa mitään tyhjentävää määrittelyä, mutta sen voidaan katsoa olevan taso, millä työntekijät kokevat työtehtävässä menestymisen edellytysten olevan, ja miten työhyvinvointi koetaan. Kaikessa yksikertaisuudessaan, työn mielekkääksi kokemiseen vaikuttaa valtavasti työn sujuminen arjessa. Kun työntekijät ymmärtävät oman työnsä merkityksen osana kokonaisuutta ja saavat mahdollisuuden kehittää osaamistaan ja työtapojaan, ollaan jo pitkällä.

Harvard Business Review’n artikkelin mukaan työssä erinomaisesti menestyvien työntekijöiden loiston taustalta löytyy kaksi tekijää: elinvoimaisuus ja oppiminen. Työntekijät, jotka kokevat olevansa elossa, intohimoisia ja innostuneita aikaansaavat energiaa itsessään ja toisissa. Ihmiset, jotka kehittävät osaamistaan, uskovat myös todennäköisesti enemmän omiin kasvumahdollisuuksiinsa.

Työn mielekkyyttä voi itse systemaattisesti pyrkiä kasvattamaan, mutta mielekkyys, kuten ei myöskään hyvä palvelu, koskaan synny tyhjiössä, vaan on aina osana ympäristöä, työyhteisöä ja työtehtäviä. Keskittymällä työntekijöiden suorituskyvyn edellytysten parantamiseen ja innostuksen ruokkimiseen, yritys voi vaikuttaa positiivisesti myös palvelutuotannon laatuun sekä asiakastyytyväisyyteen.

Tämän ei pitäisi olla mikään yllätys, mutta silti yllättävän harva yritys aidosti panostaa henkilöstönsä suorituskyvyn edellytyksiin. Henkilöstökustannukset palvelualoilla ovat yrityksen isoin kuluerä, joten miksi et huolehtisi, että suurin sijoituksesi tuottaa parhaalla mahdollisella tavalla? Panosta siis henkilöstökokemukseen ja tee työntekijöistäsi suurimpia fanejasi. Tunteet tarttuvat, joten avain erinomaiseen asiakaskokemukseen ja kasvavaan kassavirtaan piilee innostuneissa työntekijöissä.

Silja Saviranta

Kirjoittaja on valmistunut Metropolian Liiketoiminnan kehittämisen YAMK-tutkinto-ohjelmasta.

“The dark side of statistics may become a trap, if the subject is not used professionally. Among the current wide use of data analytics and popularization of statistical tools, we need to know more about statistics and understand it deeper. It will help to avoid its dark side”, believes Prof. Dr. Patrick Planing from Stuttgart Hochschule für Technik, a partner University of Metropolia. He shared his views with the students of Master’s program in Business Informatics in a guest visit to Metropolia University of Applied Sciences.

Traps of Statistics Typical of Media: Miscalculations

Statistics has gained a lot of credibility is society over the years. Readers of newspapers and popular journals are used to reading unusual, sometimes shocking news, and get easily convinced as soon as statistics is mentioned. In practice, however, a sloppy use of statics can lead to even fake news, when the concussions are drawn superficially, but positioned as if based on careful statistical analysis.

Consider this claim:

“The proportion of suicides in all deaths is highest among the people under 20 years with 25%, compared with 10% among 30-40 year olds, and less that 2% among over 70 year olds”.

Conclusion (wrong):

“So, the decision to commit a suicide decreases more and more with the age”.

Can we agree with this claim? If we look at it closer, there are many flows in this claim. First, there are no absolute numbers, which makes it unknown how many actually died in every age group. As a result, the current proportion cannot be correct since the death numbers in each groups are different. Also, there are no reasons indicated for the other deaths (they may be due to traffic accidents, diseases, etc), which makes the picture distorted, as there may be a growing number of other reasons for death in older age groups.

If such news are published in press, they look scientific, but the public should not be deceived. If we read this claim slowly, think of the context, and consider if this is possible at all, we can see that it cannot be correct, and does not allow to judge reliably about the behaviors of different age groups.

More Traps for Media: Misinterpretations

There are many of such false news. One very famous example originated from a study conducted by Denmark, universities, that investigated which students complete and which drop their studies. The drop rate was up to 40% over the first year, so it was important to explore the reasons for this. The research group discovered a surprising and rather confusing result. They found a negative correlation between the drop rates and the drinking habits of students. But it was not the conclusions that comes immediately to mind (that drinking habits lead to drop outs), but the opposite. The surprise was that the regularly drinking students dropped less!

All world media shared these unbelievable news: the more you drink, the more successful you are in your studies! “Sober students are more likely to drop off” were the headings in many media. But could we really draw such a conclusion form this statistical study? No, we cannot.

First of all, this cannot be a conclusion but a hypothesis, as there may be other variables interfering into this correlation. In other words, it is not that “X correlates with Y”, but “X correlates with Z (a third variable), which correlates with Y”, and other variables may be missing from the analysis. For example, social occasions may contribute to completing the studies. Maybe, it is the active social life that helps success in the studies (the students, who did well, and did not drop, did not fear the exam, probably because they socialized with others). Since this statistical study did not look deeper into the habits, we just do not know. As statistics professionals know, correlation does not indicate any causality. In other words, the most likely explanation may not be the truth. True reasons may be many. A simple answer is to check carefully before making claims.

Traps of Statistics for Professional Science: In Significance Level and Data Openness

However, even the correct process of interpreting the data can lead to wrong results that are seemingly based on correct statistics. If we look beyond popular media, there are still many underlying reasons (not only the fake news) why statistics can be “lying with the numbers”. It may happens, for example, if someone is trying to make sense of statistics – in any science, in biology, chemistry, economy etc. – without awareness of specific flaws that may be awaiting.

One of the reasons of flawed results in science, especially in the past, is the way how we do science. It often dictates wrong conclusions.

The current statistical rates of measuring the acceptability of science results started in 1925, with the British statistician Ronald Fisher offered a cup of tea with milk to his colleague, Muriel Bristol. Muriel refused this cup saying that Fisher poured tea first and milk second into her cup, while she likes it the other way round. She also claimed that she can see it at a glance which liquid was poured first. Fisher arrange a special experiment for her, to check how many times she could correctly make such a prediction. Fisher concluded that ”Bristol divined correctly more than enough of those cups into which tea had been poured first to prove her case”.

But how many cups are enough? Since Fisher’s influential 125 books, the statistical significance was accepted at the rate of 5% for scientific results to prove “true”. In 1925, Fisher’s believed that 6-8 cups were “well enough” (starting from Fisher’s statistical book), and since then a significance rate of 5% has been accepted by science as “well enough” for many disciplines, and often continues till now.

In practice, however, statistical significance does is not equal to a real life significance. If we have a significantly large size of sample, even the smallest effect can be calculated as a significant result!

By now, enough evidence is collected by statistics that argue against a blind adoption of the 5% significance level (and this is still the rate to get published in medicine, for example!) reliable results cannot be obtained. In 1925 it was probably ok, but it cannot be accepted any more, although it still happens today. If someone tests a new drug against 5% significance level, it simply does not make sense, as the significance level alone does not tell us anything about the effect of the drug.. This is clear to all who know statistics and its behavior.

This is where “bad science” comes from that has come into light in recent years. The answer is to have a significant difference, and do not accept low levels with 5% of proof. This is not any more acceptable and there is a lot of discussion around it nowadays.

How to Avoid These Traps in Science and Business?

Therefore, good science needs to have, first of all, to pay attention to the significance levels and the size of the sample group. Next, good science will also absolutely necessary analyze the difference, measuring the true effect size. Good science should check all the factors carefully, by testing the same correlation in random groups, the bigger the groups, the better the ground! At the same time, professional scientists cannot rely only on correlation. The problem with correlation is that is does not say anything, it does not prove any causality. This is why there is a need to establish experiments. A good reading here is the book “Designing experiment” Fisher, 1943.

My message to students is do not be fooled by media or “poor” science who do not understand the dark side of statistics. Also, for professional scientists, it is important to stop use “null” hypothesis tests, or testing the opposite instead of testing the actual phenomena. Such “null” tests lead to a lot of confusion (like in patient statistics developed in 19th century, instead of using significance testing). But the main issue for science is the absolute necessity to publish the data (instead of a 5-page note about conclusions, which can be drawn incorrectly). Give the raw data, show it, tell how much and what was measured; or if not publish, demonstrate the data to experts, similar to the practice in referenced journals. This initiative is called “Open data initiative”, there still could be flawed data, but this openness about the simple will increase reliability of science results.

Management of organizations should also be aware of these effects. Management needs more educations in order to use the statistics produced by consultants and own staff more effectively. This is especially evident for Marketing research. There was a big discussion in “Spiegel” magazine recently, and some professionals even claim that all marketing research is flowed since consultants are not educated in statistical methods. This discussion shows that deeper knowledge of statistical methods is needed for professional in all fields, journalists, politicians, even scientists. A wide society also need to be more demanding and create pressure to prove the grounds for conclusions based on statistics. Without a careful check of the utilized data samples, the data analysis process and interpretation, no reliable conclusions are possible, even from such a precise discipline as statistics.

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Prof. Dr. Patrick Planing – a guest speaker from Stuttgart Hochschule für Technik teaching Statistics and Statistics Models for big data. His interested include business psychology, future thinking, predictions, strategy scenarios, and many other interesting topics related to data.

Zinaida Grabovskaia, PhL – a lecturer and Head of Business Informatics Master’s Program at Metropolia University of Applied Sciences. Zinaida is interested in inviting the latest and most important topics to professional discussion with Metropolia Master’s students.