\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"intechopen-signs-new-contract-with-cepiec-china-for-distribution-of-open-access-books-20210319",title:"IntechOpen Signs New Contract with CEPIEC, China for Distribution of Open Access Books"},{slug:"150-million-downloads-and-counting-20210316",title:"150 Million Downloads and Counting"},{slug:"intechopen-secures-indefinite-content-preservation-with-clockss-20210309",title:"IntechOpen Secures Indefinite Content Preservation with CLOCKSS"},{slug:"intechopen-expands-to-all-global-amazon-channels-with-full-catalog-of-books-20210308",title:"IntechOpen Expands to All Global Amazon Channels with Full Catalog of Books"},{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"}]},book:{item:{type:"book",id:"23",leadTitle:null,fullTitle:"Modern Pacemakers - Present and Future",title:"Modern Pacemakers",subtitle:"Present and Future",reviewType:"peer-reviewed",abstract:"The book focuses upon clinical as well as engineering aspects of modern cardiac pacemakers. Modern pacemaker functions, implant techniques, various complications related to implant and complications during follow-up are covered. The issue of interaction between magnetic resonance imaging and pacemakers are well discussed. Chapters are also included discussing the role of pacemakers in congenital and acquired conduction disease. Apart from pacing for bradycardia, the role of pacemakers in cardiac resynchronization therapy has been an important aspect of management of advanced heart failure. The book provides an excellent overview of implantation techniques as well as benefits and limitations of cardiac resynchronization therapy. Pacemaker follow-up with remote monitoring is getting more and more acceptance in clinical practice; therefore, chapters related to various aspects of remote monitoring are also incorporated in the book. The current aspect of cardiac pacemaker physiology and role of cardiac ion channels, as well as the present and future of biopacemakers are included to glimpse into the future management of conductions system diseases. We have also included chapters regarding gut pacemakers as well as pacemaker mechanisms of neural networks.\nTherefore, the book covers the entire spectrum of modern pacemaker therapy including implant techniques, device related complications, interactions, limitations, and benefits (including the role of pacing role in heart failure), as well as future prospects of cardiac pacing.",isbn:null,printIsbn:"978-953-307-214-2",pdfIsbn:"978-953-51-6423-4",doi:"10.5772/556",price:159,priceEur:175,priceUsd:205,slug:"modern-pacemakers-present-and-future",numberOfPages:626,isOpenForSubmission:!1,isInWos:1,hash:null,bookSignature:"Mithilesh Kumar Das",publishedDate:"February 14th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/23.jpg",numberOfDownloads:348596,numberOfWosCitations:52,numberOfCrossrefCitations:24,numberOfDimensionsCitations:87,hasAltmetrics:1,numberOfTotalCitations:163,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 13th 2010",dateEndSecondStepPublish:"May 11th 2010",dateEndThirdStepPublish:"September 15th 2010",dateEndFourthStepPublish:"October 15th 2010",dateEndFifthStepPublish:"December 14th 2010",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,editors:[{id:"61931",title:"Prof.",name:"Mithilesh",middleName:"Kuma",surname:"M Das",slug:"mithilesh-m-das",fullName:"Mithilesh M Das",profilePictureURL:"https://mts.intechopen.com/storage/users/61931/images/1618_n.jpg",biography:"Associate Professor of Clinical Medicine\nKrannert Institute of Cardiology, Indiana University School of Medicine Director, Cardiac Electrophysiology Service, Roudebush VA Medical Center Program Director of Cardiac Electrophysiology Fellowship, VA Medical 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Semen analysis, as a standard laboratory test, gives basic information on spermatogenesis, secretory activity of the gonads and patency of the male genital tract [2]. The results obtained during the semen sample analysis could point out absence of spermatozoa, severe or mild deviation in sperm parameters or normal values for semen volume, sperm count and concentration, motility and morphology of the spermatozoa. Over the years many reproductive specialists have been constantly debating, suggesting and remodeling the frame values of the semen in reference to male fertility. Since 1987, there are several updates in different editions of World Health Organization (WHO) manuals defining the optimal sperm parameters with reference to pregnancy outcomes. The last (fifth) edition of the manual, published in 2010, defines serious decrease in cutoff values for sperm parameters related to chances of achieving pregnancy and thus its significance was widely discussed [3, 4]. One of the strong limitations of semen analysis and the defined fertility potential references in the last WHO edition is the lack of correlation with the female age, as only 30% of infertility in couples is due to male factors alone [5, 6]. The sixth edition of WHO is in discussion as some of the directions of changes would be: semen analysis references including the Asian population for reference establishment; additional separate chapters for sperm morphology and computer assisted sperm analysis (CASA); importance of microbiological assessment. Some of the inapplicable tests at the modern andrology lab tests, e.g., postcoital test, capillary tube, Hamster test, counting in glass chambers will be excluded from the manual. New techniques such as sperm DNA fragmentation tests, aneuploidy screening, acrosome reaction assay, motile sperm organelle morphology examination (MSOME), Calcium ionophore activation, Catsper channels activity examination, influence of epigenetics and miRNA will be described [7].
\nSemen sample parameters could be influenced by various factors such as sexual abstinence periods [8, 9], gonadal activity [10], abnormal hormonal levels [11], testicle size [12], body mass index (BMI) [13, 14, 15], urogenital infections and antibiotics or anabolic substances intake [16, 17, 18], individual diet regiment [19, 20, 21], working environment and lifestyle [22, 23, 24]. Sperm parameters have a leading role both in natural conception and assisted reproduction technologies (ART) outcomes. In order to establish male fertility potential, at least two to three sperm samples in a 3-month period should be analyzed [25]. Attention to intraindividual variability in parameters has to be considered. Reports in various studies show fluctuation in sperm volume and count, concentration, motility and morphology in one individual [26, 27, 28, 29]. There are limitations to semen analysis depending on the patient specificity and the use of good laboratory practice protocols. Only this analysis by itself has a contradictory clinical value and might not be a stand-alone predictor for male fertility [30, 31]. In conditions such as azoospermia, globozoospermia or necrozoospermia, exceptions are made and male infertility could be stated [32].
\nWhen there are no sperm cells detected through microscope observations (azoospermia), the condition needs further investigation. Performing at least two separate semen analysis is needed. Centrifugation of the whole ejaculated volume is necessary in order to detect specific conditions [33]. When several or sporadic sperm cells are routed out in the sediment of the centrifuged sample the definition would be cryptozoospermia [34].
\nApproximately 10–15% of all infertile men are diagnosed with azoospermia. When according to laboratory test a patient is diagnosed with azoospermia, further hormonal and genetic tests along with andrology, urology, genetic consultation and ultrasound scan are needed [35].
\n\n
\n
\n
Sperm cell morphology is strongly correlated to male reproduction. Abnormalities might affect sperm motility, sperm fertilize ability and conception. Some conditions such as globozoospermia or stunted tail sperm defects could lead to inability to father biological children as a consequence of natural conception [56, 57, 58].
\nRecently, the intact human flagellum has been studied using cryo-electron microscopy and tomography [59]. A novel structure—tail axoneme intra-lumenal spiral (TAILS)—was reviled and described [60]. This new discovery suggests the need of further exploration and observation of sperm structures—not only in order to connect them to sperm function but also to clarify their significance. As previous studies reported, abnormal tail structure is correlated to sperm motility disorders, as nonspecific flagellar anomalies (NSFAs) are found to be the most frequent flagellar pathology in severe asthenozoospermia, and thus reduces the chance for natural conception [61]. According to the new data revealing TAILS, the explanation to some cases considered as unexplained infertility might be reviled.
\nLink between sperm morphology and numerical or structural chromosome abnormalities are suggested and investigated [62, 63, 64]. In fertile men, who have different translocations the frequencies of sperm chromosomal abnormalities were high (33–92%) in comparison to those with normal karyotype [65].
\nPost-radiotherapy treatments also show in altered number of structural and numerical chromosome aneuploidies (from 6 to 67% respectively [65]. Studies on infertile men with teratozoospermia (<14% normal forms), globozoospermia and macrocephalic, multinucleated or multiflagellate spermatozoa show an increased incidence of sperm aneuploidy up to 50% [65, 66]. Sperm with normal chromosome constitutions can be exhibited in men with normal or abnormal sperm parameters [67, 68].
\nInvestigating male fertility potential initially is based on routine semen analysis. Establishment of certain values for semen in order to predict chances of conception generates the need of references for male fertility. Requirement for semen analysis and semen parameters have been set as recommended in successive editions of WHO in 1980, 1987, 1992, 1999 and 2010 [1]. The following table [69] represents changes for cut off values for semen parameters according consecutive WHO manuals:
\nSperm sample evaluation in a modern andrology lab might be measured by the means of CASA. The use of computer aid does not exclude additional evaluation by the human eye [70, 71]. For sperm morphology evaluation, WHO [72] recommends criteria by strict morphology [73].
\nRecently, DNA fragmentation tests have been widely incorporated in laboratory practice. DNA integrity and sperm hereditary information are essential to the offspring as male gametes has major contribution to the fertilization processes, embryo quality and embryo development even in early gestational stages [74, 75, 76]. Sperm contains almost 3000 different kinds of mRNA coded for proteins that are active in the early embryo development period. There are also some others still unknown and with no equivalent in the oocyte [77, 78].
\nSince the introduction of ICSI as routine procedure, the significance of standard semen analysis was neglected, as sperm concentration and motility have no longer such importance, since a single sperm cell has to be injected. When standard ICSI procedure under a Hoffman modulation contrast microscope, or Nomarski optics at magnification ×400 is performed visualization and assessment of sperm head (size and shape) mid-piece and tail are possible, but detailed ultrastructural morphology examination is limited [79, 80]. When conventional ICSI is performed, it would be difficult to evaluate and select morphologically normal sperm based on its detailed structural portrait: vacuolization, membrane invaginations, mid-piece thickness or deformity, etc. It is controversial whether high vacuolization in the sperm head is associated with higher DNA fragmentation and aneuploidy rate [81, 82] that may have adverse effect on embryo quality and postimplantation development and higher frequency of pregnancy loss at early gestational stages. Still, for some couples detailed sperm examination prior ICSI is preferable [83, 84].
\nIntracytoplasmic morphologically selected sperm injection (IMSI) is the cornerstone to sperm morphology evaluation. Based on the examination of motile sperm organelle morphology (MSOME) IMSI is the only real-time, unstained method used for selection of motile and morphologically normal spermatozoa for intracytoplasmic injection. IMSI was first introduced by Baratoov et al. [85]. MSOME selection is made under inverted light emitting microscope with Differential interference contrast or Nomarski differential interference contrast optics and digital camera at high magnification ranging from ×6600 to ×13,000. Using MSOME criteria, the motile sperm fraction and each cell malformation is evaluated according to the morphological status of six organelles comprising the acrosome, post-acrosomal lamina, neck, mitochondria, tail and nucleus. Only 33% of spermatozoa from the examined samples appeared morphologically normal according to these criteria [86].
\nDefects defined for each area are:
\nacrosomal area—lack, partial or vesiculated;
\npost-acrosomal lamina—lack or vesiculated;
\nneck—abaxial, cytoplasmic droplet.
\nmitochondria—lack, partial, disorganization;
\ntail—lack, coiled, broken, multi, short;
\nnucleus—small or large oval, narrow, wide or short, regional disorder, vacuoles occupying more than 4% of the nuclear area [87, 88]. However, evaluation of motile spermatozoa might differently be determined by various scientists [89].
\nWhat seems to be the most important in the observation of motile spermatozoa under high magnification in real time is evaluating the presence of vacuoles in the head of the sperm cell—number, size and location. The precise origin of the vacuoles is still unknown, but different hypothesis suggest they derived from early stages of spermatogenesis during sperm maturation and their number increase on account of vacuole area [90]. Other studies suggest that vacuoles formation in spermatozoa starts in incubation and capacitation period after ejaculation [91]. Nevertheless, high vacuolization or the presence of large vacuoles in the sperm head might be associated with increased DNA fragmentation rates and increased level of chromatin immaturity and could influence fertilization and pregnancy rates [92, 93, 94].
\nSperm morphology evaluation could be based on the Cassuto and Barak Score as a precise rate system for sperm selection [94]. For the establishment of the score six parameters of the spermatozoon were taken into account: head, acrosome, vacuole, basis, insertion, and cytoplasmic droplet (“HAVBIC”). Head, vacuole, and basis were considered as major criteria for abnormalities, and acrosome, insertion, and cytoplasmic droplet are minor criteria for sperm evaluation. The following equation was developed:
\nBased on the formula, sperm cells score could vary between 0 and up to 6, and in relation to the quality three groups were differentiated:
\nClass 1
Class 2
Class 3
Since its introduction and based on the first articles demonstrating increase in the pregnancy rates using IMSI compared to ICSI [85, 87] the method became widely incorporated in laboratory practice despite it is a time-consuming technique.
\nEvaluation of motile spermatozoa under high magnification is suitable for patients with high levels of DNA fragmentation sperm aneuploidy, severe oligo- or oligoasthenozoospermia and/or teratozoospermia, recurrent implantation failures or history of repeated early miscarriages, advanced female age and advanced male age [80]. Subsequent studies provided further analysis and information for the importance of the new method evaluating sperm morphology for obtaining better results in patients with male factor infertility.
\nThere are still controversial study conclusions for the impact of IMSI procedure on
Y-chromosome deletion is associated with azoospermia, oligozoospermia (low sperm count) or abnormal sperm morphology and motility [96, 97]. When AZFa and AZFb deletions are detected, testicular sperm retrieval would be ineffective [98], but it is successful option for most males with AZFc deletions [99, 100, 101]. There is a case [102] reporting natural conception and Y-microdeletion passing. When diagnosed, and considering that Y chromosome infertility is inherited in a Y-linked manner, the patients should discuss and consult the specific genetic condition with genetics specialists as this could lead to infertility in the next generations [103].
\nAnother gene that could be investigated in order to obtain the option for TESE is the Testis expressed gene 11 (TEX 11). Studies show that
Congenital bilateral absence of vas deferens (CBAVD) and the lack of sperm cells in the ejaculate are superable using microsurgical TESE or PESA followed by ICSI [107]. As CBAVD has been associated with mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene [108, 109] investigating the condition and genetic testing and consultation prior the procedures should be provided as there is a risk for the couple to have a child with cystic fibrosis [110].
\nIn conclusion, genetic counseling as well as prenatal genetic diagnosis (PGD) or preimplantation genetic screening (PGS) should be offered as part of the fertility treatment [111, 112].
\nCancer healing by chemo- or radiation- therapy may disturb hormone production, ejaculation and spermatogenesis for long period of time or even permanently. These aggressive treatments could lead also to higher DNA sperm fragmentation [113, 114]. For cancer patients with assigned therapy, freezing one or several semen samples prior the start of any medicaments and manipulations (including operation, X-ray for additional diagnostics) is an option for further fertility preservation. Although cryopreservation of sperm does not guarantee preserving fertility or achieving pregnancy, it is substantial to consult and encourage the patient/couple to do it. Still, in patients with terminal loss of spermatogenesis due to cancer treatment, frozen samples are the only chance of hope to father a biological child. When a female partner is involved, counseling should consider the fact that female age is a leading factor in conception and postponing the ART or natural conception, could seriously decrease the chances of having a baby [115, 116, 117, 118, 119].
\nDespite the advances of modern science and reproductive medicine, for some men, the only chance to father a child is through donated sperm [120]. In cases when after thorough examination male sterility was diagnosed [121]; severe hereditary conditions are established, or a couple with male factor infertility had numerous in vitro cycles [122] with no positive results, using donated sperm is an option. Employing donor spermatozoa in the fertility treatment could influence the couple’s psychological state, the relationship between the partners and their relatives [123, 124]. In order to perceive infertility and take informed choice for further fertility treatment psychological support could be of help [125].
\nSuperoxide anion (O2−), hydrogen peroxide (H2O2), hypochlorite (OHCl), and hydroxyl radical (OH) are highly reactive oxygen species (ROS) and their production occurs during normal metabolism of the cell. In semen ROS are produced mostly by the leukocytes and immature spermatozoa and are related to acrosome reaction, capacitation, mitochondrial stability, and fusion with oocyte. Imbalance between the formation of ROS and the inability of the antioxidants to neutralize the excessive production of ROS is defined as oxidative stress (OS). As seminal plasma contains antioxidants and has natural antioxidant capacity, it sustains the free radicals balance in the sperm; overproduction of ROS and OS results in lipid peroxidation, protein changes, DNA damage and sperm death, and this may affect male fertility [126, 127].
\nHigh concentrations of ROS as potential cause of male infertility have been studied since 1943 [128]. Potential internal yield of excess ROS could be consequence to damaged or abnormal spermatozoa, varicocele, cryptorchism, testicular torsion, infection, inflammation and aging. Some external factors such as exposure to toxins (toluene, methoxyethanol, sulfur dioxide), metals (cadmium) chemotherapy and ionizing radiation (cancer treatment) may also influence ROS levels and form OS.
\nStudies demonstrate association between elevated ROS levels and abnormal sperm concentration, motility, morphology, higher DNA damage and apoptosis. Comparison between infertile men and donors showed that excess ROS values had a sensitivity of 68.8% and specificity of 93.8% in correlation with poor semen parameters and could result in infertility [129, 130].
\nIt is important to understand the physiological role of ROS as they are relevant to sperm capacitation, hyperactivation and sperm-egg fusion formation. ROS are involved in intracellular cyclic adenosine monophosphate (cAMP) increase followed by protein Kinase A activation and elevation of tyrosine phosphorylation. These changes lead to sperm capacitation and hyperactivation, sperm membrane becomes unstable and initiates acrosome reaction (releasing enzymes contained in the acrosome—nonzymogen acrosin, proacrosin, inhibitor-bound acrosin, hyaluronidase, acid phosphatase, beta-glucuronidase, beta-glucosidase, beta-N-acetylglucosaminidase, beta-galactosidase and beta-N-acetylgalactosaminidase) which allows the binding of sperm cell to oocytes zona pellucida (ZP) [131].
\nImbalanced ROS levels could compromise semen quality and functions and keeping them in normal concentration is considered essential to fertility. Oxidative stress and nutritional status are of importance to every person as antioxidant deficiency and malnutrition may alter the health in general. ROS are also related to various respiratory and cardiovascular diseases, neurodegenerative, digestive disorders and even cancer. The clinical importance of OS in relation to fertility is thoroughly studied. The clinical awareness of nutritional balance in disease occurrence, progression and outcome is still limited, but the need of balanced diet nutrients and antioxidants is urged and necessary [132, 133].
\nThe ability of a men to become biological father is not only a consequence of normal sperm count but is also linked to the normal function of the male reproductive tract and sperm activity. Failure in sperm production or low sperm count and motility, poor morphology, disturbance in sperm movement and progressive passage through the cervical mucus, uterus, ampulla of the oviducts, capacitation and acrosome reaction, binding zona peluccida, etc. can result in male infertility.
\nTo overcome male infertility in ART different protocols for sperm processing have been developed. There are still many debates on the exact influence of specific techniques used for sperm processing and their benefit to achieve pregnancy. Selecting a proper technique must be strongly individual according the couple’s infertility history and ART treatment plan along with semen quality. Isolating an optimal fraction (higher count with progressive movement, morphologically normal rates) of spermatozoa gives the opportunity for selection and usage of the spermatozoa with a better fertilizability and higher chances to contribute for a viable fetus, for intrauterine insemination (IUI), IVF or ICSI.
\nTwo of the most explored methods for sperm processing in ART—density gradient centrifugation (DGS) and swim-up (SU)—are investigated in details. Compared to fresh sample, the processed one has lower DNA fragmentation rates [134, 135] and lower concentration of ROS regardless which method was used [136, 137].
\nAs there are studies exploring telomere length in reproductive cells (oocytes and spermatozoa) and their connection to infertility, shorter telomeres in spermatozoa might be assumed as a factor causing idiopathic infertility [138]. Truncated telomeres and altered DNA integrity in sperm could negatively influence fertilization, pronuclei formation, embryo morphology and quality and thus could compromise blastocyst formation and implantation. Spermatozoa obtained by either DGC or SU have longer telomeres compared sperm cells in the raw semen [139].
\nSome substances such as pentoxifylline (methylxanthine derivate primarily used in intermittent claudication and other vascular disorders treatment) might enhance the motility and quantity of motile sperm after processing. By using pentoxifylline primarily on samples with poor quality increased sperm viability in infertile men with oligoasthenozoospermia, was observed. Samples obtained by PESA or TESE could also be improved by implementing this xanthine derivative in cultural media and thus improve sperm motility [140].
\nSperm preparation methods along with technical advantages of MSOME allow the selection of sperm cells, with best predictive values, for ART treatments. There are some limitations related to each method used and that is now an open field to research and establish new noninvasive protocols for sperm selection in the routine practice.
\nSpermatogenesis is a complexed process of division and formation of male reproductive cells. It is highly sensitive to various internal (hormonal regulation, transmitters, growth factors) and external (nutritive substances, therapeutics, drugs, hormones and their metabolites, different toxic substances or X-radiation, increased temperature) factors [141]. Given that the time frame for formation of every new generation of spermatozoa takes approximately 3 months, it should be considered that unfavorable effects purge would be the consequence to time consuming treatment or lifestyle changes.
\nModern day society—environment, lifestyle and diet are suspected to be harmful to different processes in the organism such as spermatogenesis and could negatively affect the quality and quantity of life through human lifespan including the ability to reproduce. Considering that sex formation takes place during early fetal development attention to mother’s nocuous habits, lifestyle, and environmental specifics should be advert. Events during pregnancy could also influence male fertility later in life [142]. In some specific cases, when there was a long exposure to high dosage of toxins, chemotherapy or radiotherapy, spermatogenesis regeneration would most probably take years or may never be restored. Healthy life style along with regular medical check and tests could indicate on time and even prevent urological or fertility problems.
\nThe authors wish to thank their IVF unit colleagues at Ob/Gyn Hospital “Dr. Shterev” for most helpful discussions while summarizing this chapter.
\nThe authors report no financial or commercial conflicts of interest.
advanced maternal age
\nassisted reproduction technology
\nbody mass index
\ncomputer assisted sperm analysis
\ncyclic adenosine monophosphate
\ncongenital bilateral absence of vas deferens
\ncystic fibrosis transmembrane conductance regulator gene
\ndensity gradient centrifugation
\nintracytoplasmic sperm injection
\nintracytoplasmic morphologically selected sperm injection
\nintrauterine insemination
\nin vitro fertilization
\nmicrosurgical epididymal sperm aspiration
\nmotile sperm organelle morphology examination
\nnonobstructive oligoasthenozoospermia
\noligoasthenozoospermia
\noxidative stress
\npercutaneous epididymal sperm aspiration
\npreimplantation genetic diagnosis
\npreimplantation genetic screening extraction
\nreactive oxygen species
\nsperm aneuploidy test
\nswim up
\ntail axoneme intra-lumenal spital
\ntesticular sperm
\ntestis expressed gene
\nWorld Health Organization
\nzona pellucida
\nhydrogen peroxide
\nsuperoxide anion
\nhypochlorite
\nhydroxyl radical
\nIn 2016, the digital economy worldwide was worth US$11.5 trillion, or 15.5 percent of global GDP. The outstanding performance of the digital economy is mainly attributable to the development of a consumer-driven Internet. By 2025, the industrial Internet is predicted to experience massive growth, with industries across the board seeing high levels of digitalization and intelligence. By then, the digital economy is expected to grow further, to 24.3 percent of global GDP. This rise, even taking into account the fact that the value of digital offerings is underrepresented in GDP figures [1], if it happens will come about largely through innovation. The digital economy, and particularly its service elements, in this sense is the fastest changing sector the world has ever seen.
In some countries, the economy is already dominated by services rather than products. Recognition that customers want the functions that products deliver but do not necessarily want to own the product is the primary driver behind this trend. Customers receive all the upside of being able to perform the jobs they wish to get done (mobility, communication, eating, laundry, learning, managing their finances, etc), without all of the downside of initial capital outlay, maintenance, or eventual replacement of the products required to deliver the required functions. This product-to-service shift represents a vital step towards a more sustainable society. Prior to their shift to a ‘power-by-the-hour’ functional sales model, for example, the jet-engine industry had a strong imperative to make engines that required frequent overhaul and replacement. When customers receive ‘free’ engines that they only pay for when they are being used, however, the engine manufacturers quickly recognised a strong incentive to design engines that lasted a lot longer and required less maintenance. Such transitions, in many cases, only become possible thanks to the benefits attributable to digital technologies…
…in parallel with the product-to-service evolution trend there is a pattern of evolution that sees ‘mechanical’ technologies evolving towards electronic and digital solutions. The mechanical keypads found on the first mobile phones have evolved to become digital touch-screens; the 35 mm film used to record photographic images has become digital; the physical money traditionally carried in people’s pockets, is increasingly becoming ‘e-cash’. People used to visit shops and now increasingly shop online. There are literally thousands of examples of such physical-to-virtual transitions [2]. The common factor – that it is easier to move electrons rather than atoms – again delivers inherent environmental benefits as well as being better able to serve customer needs. As such digitalisation looks set to be a trend that will also continue for the foreseeable future.
The rise in the importance of innovation offers up another highly visible evolution trend. This trend is driven by the convergence of a host of other societal trend patterns. Globalisation, the transparency emerging through social media, rising populations, climate change, finite natural resources combine to create, firstly, an imperative to find better ways of doing things, and, secondly, an increasing likelihood that if incumbent organisations fail to meet shifting customer needs, someone else will step in.
‘Innovate or die’ has been a commonly used aphorism for close to two decades now. More often than not, however, it becomes ‘innovate
Second is the definition of the word innovation. Over 90% of authors using the word use or imply a definition that equates innovation to either ‘new ideas’ or, more commonly, ‘new ideas that are launched onto the market’. Neither of these definitions, however, makes any kind of sense from the perspective of enabling better understanding of how to innovate. By either measure, e-service providers like Uber count as innovation, but, at this point in time, the Company has lost and continues to lose vast amounts of money. To the point, many investors are beginning to believe that they will never become cash positive. Any prospective innovator taking organisations like Uber as models for their own projects is only likely to fall into the same financial black-hole. The only innovation definition that makes sense is one that includes a success metric. For most enterprises this metric will be financial in nature – achieving a net positive ROI for example, or customer value, or profit – while for others it will be measured in other ways – patient life expectancy or quality of life. Whatever the chosen success metrics are, a new idea only becomes an innovation once they are met. The primary importance of using this definition is that it is the only one that enables a possibility of acquiring and sharing repeatable best practice…
…much of the 98% failure rate found in Innovation World comes from the fact that innovating is difficult. It demands that innovators embrace the innate complexities of the world. It demands they are willing to venture into the unknown. And that they are willing to persevere through the many false-starts, insurmountable obstacles and dead-ends, through the maze of mis-information, mis-interpretation, confusion, stress, and sleepless nights. In many ways, the 2% were first and foremost lucky. They prevailed predominantly by trial and error. Perhaps ironically, the digital world has been lucky enough to stumble upon ‘methodologies’ like Agile and Scrum, and has evolved the concept of the hackathon in order to increase the speed trial-and-error iterations are able to be performed. The irony being that, even though consistent with working in complex environments, the rapid-trial-and-error strategies of many in the digital world have had little or no impact on the overall innovation statistics. 98% of all innovation attempts fail; 98% of e-service innovation attempts fail.
The big idea underpinning ‘systematic’ centres around the removal of the trial-and-error randomness from the e-service innovation process. In effect it becomes, like its TRIZ forerunner [4], a programme of research to decode and reveal the ‘DNA’ of the 2% of successful attempts. When dealing with complex systems, as we inevitably are when it comes to innovation, such a task is fraught with difficulties. Not least of the reasons being that it is never possible to ‘step in the same river twice’. Just because an innovation team replicates all of the steps of a previously successful innovation project does not guarantee their success. In fact, given the general speed of change in the world, the surrounding context and environment of any previously successful project is inevitably different in today’s project. Many prospective innovators, unfortunately, have been taught that ‘doing the same tomorrow as you did yesterday and expecting a different outcome’ is one of the first signs of madness. Such an aphorism might have made sense in simpler times, but it carries little if any relevance in a complex world. To the extent that the 423 Fortune 500 companies from the original 1950s list that no longer exist could all be said to have fallen precisely into the trap of continuing to do what they’d always done and expecting to get the same money-making results.
‘Systematic’ and ‘complex’, in other words, do not traditionally make for good companions. ‘For every complex problem there is an answer that is clear, simple and wrong’, says another dangerous aphorism. It is an aphorism that might today be extended to say that every complex problem has
The results of this analysis – which to date has incorporated over 11 million case studies – is that when innovation attempts go wrong, they go wrong for a very small number of reasons. When it comes to e-service attempt failures, that number, as shown in Figure 1, is effectively three:
Three primary sources of e-service innovation attempt failure.
Which can be elaborated upon as follows:
Jumping off the cliff with the wrong parachute – most e-service innovation attempts in effect fail on their first day because they have misunderstood the customer need. They have, in other words, started with the wrong problem. They have listened to a ‘Voice of the Customer’ that was never there. Or was wrong. Or partial. There are two ironies here. The first is that listening to the customer’s Voice has long been an established norm. While it makes sense in Operational Excellence context, sadly, it makes no sense at all in Innovation World. Customers know that they want faster, cheaper, etc., but they usually have no idea at all about what might be possible. This is especially the case when it comes to the emotion-related aspects of a prospective innovation opportunity. Many customers would like to be ‘cool’ for example, but that is something they are highly unlikely to even covertly specify in the catalogue of requirements that eventually finds its way to the e-service development team. Much of the ‘real’ customer need is unspoken and unwritten. As if this were not bad enough, the second irony is that while the rapid iteration processes that come with Agile, Scrum, etc. are in theory all about going regularly going back to the customer with prototypes to obtain their feedback, project teams still do not uncover the real innovation opportunities. ‘The Wrong Parachute’ means in effect that the majority of innovation teams do not know how to find the ‘right’ problem, and, even if they accidentally did find it, still would not know they’d found it.
Failing to solve the Ordeal. One of the key first-principle differences between the 98% of failed innovation attempts and the 2% successful ones is that the 2% almost invariably identified and resolved one or more contradictions. The 98% continued the Operational Excellence derived belief that the only way to deal with trade-offs, compromises, conundrums, paradoxes, chicken-and-egg problems, and whatever other terms get used a synonym for contradiction, is ‘optimisation’. Innovators solve contradictions. Contradictions are the ‘David-versus-Goliath’ challenges that are inevitably attached to any step-change situation. Again, in theory iterative Agile processes, given enough designers and design iterations, should in theory eventually stumble upon contradiction-solving solutions. In practice, however, because almost no designers have been taught that contradictions can be solved, what happens is that Agile and Scrum devolve into trade-off merry-go-rounds which simply transfer the trade-offs from one design parameter to another, until eventually the team ends up, whack-a-mole like back where they began.
Failing to find the Road Back. The third problem concerns execution of the innovation project and what might be seen as a failure of perseverance. This is the part of a project where using the wrong definition of ‘innovation’ comes into play. It is one thing to find ‘the solution’ to a customer need, it is quite another to turn it into money. A big part of the innovator’s challenge here is that large parts of the digital investor world has become too enamoured of so-called ‘unicorns’. The digital world has become quite adept at creating companies that are able to attract billion dollar valuations. But attracting a billion dollar valuation and generating more than a billion dollars of new revenue are most definitely not the same thing. The investor ethos seems to hold the irrational belief that what happened with digital Goliaths like Amazon, Facebook, Baidu, Tencent, Alibaba and Google, will also happen to them. And that the game is merely about keeping the enterprise going long enough that the profits will begin to appear. Time, alas, is not the only factor at play, start-up enterprises, need ‘innovation DNA’ to find the right customer problems and solutions, but they then need to be able to integrate that way of thinking with Operational Excellence World thinking in order to work out how to make money from those solutions. Innovation and Operational Excellence, per earlier comments, may be polar opposites of one another, but any successful enterprise needs to be able to master both sets of skills and bring the requisite ones together at the right places and times. Very few digital start-ups get to master this integration challenge before the last in the chain of investors decide to call time.
Mention of ‘jumping off cliffs’, ‘Ordeal’s and ‘Roads Back’ offer a nod to first-principle thinker, Joseph Campbell. Campbell devoted much of his life to studying the world’s literature in order to, in a manner analogous to the TRIZ and Systematic Innovation research, decode the reasons why most literature (not coincidentally, around 98%) ends up as pulp, and a small percentage become enduring classics. His primary answer was published as The Hero With A Thousand Faces [6]. Although he did not understand the dynamics of what the business world now recognises as s-curves, Campbell’s ‘Hero’s Journey describes how successful literature always passes through the same stages that will be experienced by innovators as they make the shift from one solution paradigm to the next. Figure 2 illustrates these generic stages as they relate to the innovator’s journey between s-curves [7].
The Hero’s journey As S-curve transition.
The vertical axis on any S-curve picture may be plotted to show any and all of the attributes of a system that might wish to be improved. From an e-service perspective, the axis might be plotting customer related parameters such as benefits delivered, satisfaction, adoption rates, or, from the innovator’s perspective, such business parameters as number of customers, turnover, risk-reduction, profit, or ROI. At more granular service levels, the axis might be plotting performance parameters like speed, accuracy, consistency, privacy, etc. Oftentimes, all of these attributes can be integrated together so that the curve plots ‘value’. The horizontal axis is usually plotted as time, or, in more enlightened environments, improvement effort expended.
Looking at the s-curve itself, the shallow gradient start of the S-curve is usually associated with the inevitable struggle that occurs when a new service paradigm appears. Eventually, assuming a critical mass of ‘early-adopter’ customers are willing to pay enough for the ‘poor’ initial manifestations of the solution, this early revenue will pay for the continuing development of the offering. At some point, there will be some form of internally-controlled production-related Eureka moment – a new delivery technology, for example, or a new pricing model – that will allow the curve to follow a much steeper upward trajectory. This ‘stride’ portion of the curve is the joyous stage of an enterprise when life is easy – easy sales, easy improvements and easy knowledge creation and sharing. But then, sooner rather than later, comes the law of diminishing returns top part of the curve; the ‘stuck’ portion. This is where contradictions begin to emerge: whatever it is that the service provider is trying to improve, ‘something’ increasingly comes to prevent the achievement of those improvements. After ‘Crossing The Threshold’ (i.e. jumping off the cliff), the brave innovator is exected to endure a series of tests, allies and enemies before, eventually reaching a pont where they have no choice but to confront The Ordeal – i.e. the contradiction. Assuming they prevail and achieve ‘The Reward’, the beginning of a new S-curve begins to emerge. Then, assuming the ‘right’ new solution is appropriate, comes the Road Back – the transition from novel service idea to a service offering that is (commercially) successful.
Having revealed the universal nature of the inter-s-curve journey, the original TRIZ researchers shifted their attention to the contradiction part of the story, and began mapping all of the attributes of solutions that customers wanted to improve, and all of the other attributes that emerged to impede those improvements. The resulting list of parameters was very finite. In a technical context, the latest Contradiction mapping tool identifies just fifty relevant attributes [8]. When the Systematic Innovation research extended the same contradiction attribute search into the world of business, the eventual list comprised forty-five parameters [9]. In the IT world, the list is currently twenty-one parameters [10]. The e-Service world, then, effectively becomes a combination of the latter two parameter lists. Because the primary research underpinning all three tools begins from empirical grounds, there is always the likelihood that more parameters will be revealed in the future. The job in this context is to keep looking, and, more specifically, keep looking for exceptions rather than confirmation that the lists might already be complete.
What this research has then gone on to reveal, having identified the existence of pairs of conflicting parameter, are the strategies that the 2% innovators have used to successfully resolve the Ordeal conflicts. Here the most surprising finding is that the list of possible strategies – whether for technical, business or e-service (or, for that matter, architecture, biology, literature, music, and all other domains of human endeavour) - is even more finite. Since the mid-1970s, in fact, the list has remained static at forty [8, 9, 10]. This, again, is not to say that this will be the eventual final total, but rather that, at this this point in time, these are the only forty strategies that prospective innovators need to have in their Ordeal-solving armoury. Figure 3 illustrates an example of the Business version of the contradiction solving tool, showing how conflicting parameters are mapped onto the relevant rows and columns of the Matrix so that users can then be provided with a ranked list of the forty Principles used in the past to resolve similar contradictions.
Example mapping of e-service ordeal onto the business contradiction matrix [
In some ways, these Matrix tools and the list of forty ‘Inventive Principles’ form the foundation of ‘systematic’. In others, stepping back to look at other first-principle characteristics of the 2%, it also becomes clear that while the principle of contradiction-solving is a necessary component of success, it is by no means sufficient. In order to reach sufficiency, it is necessary to connect three other elements to the Hero’s Journey. The next concerns directionality…
…any road will take you there. Why do the solutions offered to customers occasionally make jumps? Is digital ‘better’ than physical? Is service ‘better’ than product? According to the next big finding of the TRIZ research, they are indeed ultimately better because the top of the new s-curve sits further up the y-axis of Figure 2 than the top of the previous curve. The y-axis, as discussed earlier, could be any of a host of different parameters. It could also be defined to include
…in the same way we need a compass to point innovators in the direction of future success, Figure 1 suggests that the most common reason for failure in the e-service domain is that the project team does not know where it is starting from. Projects get launched, and the team jumps off a cliff (‘Crosses The Threshold’ in Hero’s Journey terms) with a mistaken understanding of where their customers are. The heart of the problem here, from a first principle perspective, is that humans have two brains. A fast brain and a slow one [12]. The fast (limbic) brain makes near instant, emotion-based decisions about what a person wants, and the slow (prefrontal cortex) one rationalises those decisions. The fast brain provides the ‘real’ reasons a person wants something; the slow brain provides the ‘good’ reasons. Both of these need to be present if the customer is going to make a decision to hire our novel e-service solution. By far the easiest of the two for providers to deal with are the rationalisable, ‘good’ reasons. These are all the things that get written into the service offering descriptions and pricing information on the website. All the information, in fact, that the myriad competitors will also have on their website. Which in turn why there are so many e-service price comparison sites. Unfortunately, few if any of these offerings has anything to say about the information the customer’s fast brain is looking for. There’s a frequently used saying in China: ‘when all else is equal, we buy from our friends. When all else is unequal, we still buy from our friends’. Friendship, in other words, very easily trumps the tangible offerings made by most e-service providers. The problem this gives innovators, unfortunately, is that amorphous concepts like ‘friendship’ are very difficult to measure. The same goes for a host of other emotion-related parameters such as trust, empathy, anxiety or confidence. But just because a parameter is difficult to measure, does not excuse a choice to go and measure something simpler instead. The next important question then becomes, what were the first-principle ‘real’ reason parameters the 2% focused their attention. The answer is shown in Figure 4. On the left hand side are the four parameters that form the ‘decision-making’ foundations of the limbic brain [13]. On the right-hand side are the six parameters that form the equivalent core of the human moral decision making process [14].
First-principle human emotion and morality drivers.
Having recognised the fundamental nature of these ten parameters comes the recognition that a good way to help ensure an e-service innovation attempt ends up in the 2% category is to find ways to measure each of them. This, in fact, has been the rationale and focus of PanSensic since it’s inception fifteen years ago [15].
So much for measuring the fast-brain/real-reason information required to inform innovation projects. This might be the more difficult of the two types of measurement required, but it is also safe to say that only a small proportion of innovation attempts get the easier part right either. It may indeed be easier to formulate a specification describing the tangible parameters that will motivate customers to hire a provider’s service solution, but unless the search incorporates contradiction-finding, then the heart of a potential innovation opportunity will have been missed. What usually happens here is customers are surveyed to establish what attributes they want, and then, finally, how much they are prepared to pay for them. One of the benefits of shifting to digital services is that it becomes very easy to conduct experiments that will help innovators to establish price elasticity. This is something readily observable on many online retail websites in the form of occasional ‘personalised’ special offers, or, more generally, prices that are made highly dynamic. Dynamic pricing in this sense may be called an innovation, but its an innovation more for the provider than the customer. And, moreover, such models completely fail to identify the main customer innovation opportunities. In complex systems, it is not so much the attributes of a system that drive purchase so much as the relationship
Finally, from a first-principles perspective, is the ‘failing to find the Road Back’ part of the innovation challenge. Solving a customer contradiction might offer innovators their ‘Reward’ solution, but having a solution is invention not innovation. In Campbell’s terms, the innovation team is still in the ‘Special World’ limbo space between the old and intended new s-curves. Innovation means successfully transitioning out of that Special World back into the real (‘Ordinary’) world. And, as shown in Figure 2, that transition involves a ‘Death & Resurrection’ stage in the innovator’s Journey. What this should effectively say to the innovator is that – fundamentally – something needs to ‘die’. This generally means one of three things: 1) the innovator needs to remove themselves from the equation (especially relevant in academic-lead university spin-outs), 2) the service provider needs to ‘unlearn’ a previous way of doing things, or, most difficult to engineer, and therefore, usually the most challenging, 3) the customer needs to ‘unlearn’ one or more of their previous habits or behaviours. In being the more challenging of the three, the third option, perhaps not surprisingly, tends to be the one most likely to give the biggest breakthrough. Call that a meta-contradiction.
Revealing the ‘DNA’ of the 2% successful e-service innovation attempts offers a step closer to a systematic innovation capability, but a knowledge of How, is not the same as understanding the What of the innovation process itself. Making that transition demands an understanding of the different stages and types of challenge that an innovation project is likely to encounter. The critical factor, here, concerns the levels of complexity present at different stages of a project.
Figure 5 presents a simplified outline of what the archetypal innovator’s Journey looks like when plotted onto a Complexity Landscape Model (CLM) [16]. The CLM requires innovators to define two complexity states – one relating to their system, and the other to the surrounding environment. On each dimension, there are four distinctly different levels of complexity: Simple, Complicated, Complex and Chaotic. Each of the four demands different ways of making progress. Hence, by plotting a typical Hero’s Journey s-curve transition onto the Landscape – as seen in the 1-to-5 stages included in the Figure – will demand multiple different ways and means of progressing from one stage to the next. Importantly, when a project is in Campbell’s ‘Special World’ (Stage 4), almost inevitably there will be a period of Chaos. There are several reasons why this phenomenon is ‘inevitable’, but from an e-service perspective, the most pertinent is that organisational change only really occurs in the presence of Chaos. Prior to chaos, the human mind tends to continue applying existing rules and protocols. Only when chaos arrives does it become clear that those rules and protocols no longer apply. Innovation in this sense is about breaking rules. Something that the last forty years of Operational Excellence has taught successive generations of business leader to avoid. Operational excellence, in other words, has been about getting to Stage 3 by making sure employees follow ever more rigorous, ever simpler rules in order to maximise efficiency. Here’s another example of ‘best practice’ leading to unexpected organisational fragility, and, thus another meta-contradiction.
Complexity landscape model and discontinuous change.
In reality, the 1–5 loop is an ‘idealised’ road map. In that, given the fact that the majority of the time, a project is likely to be progressed in and environment that is Complex or Chaotic, there can be no such thing as the ‘right’ answer, and more likely than not, so such thing as the ‘right’ problem either. Which is to say that the only effective means of making progress involves use of cyclical processes. Processes that, in effect, mean that a project will likely take several circuits around the 1–5 loop.
If this is beginning to sound rather vague and un-systematic, hopefully the next section will demonstrate that, by utilising a process built around the first-principles introduced in the previous section, it is possible to accommodate enormous amounts of uncertainty and variation and nevertheless still be confident that a project will fundamentally continue to advance in the right direction.
Every e-service problem is inherently complex and so from a CLM perspective, smart innovators are well advised to build processes and protocols that acknowledge this complexity. Project resilience in this context often means operating as much as possible above the CLM ‘Ashby Line’, which means, per Ashby’s Law, that ‘only variety can absorb variety’ [17], it is better to have excess capability in the project system than that required to deal with the level of complexity present in the surrounding environment. The best place of all to be on the CLM is the ‘Golden Triangle’ [18]. The COBRA+ process was designed with this scenario in mind. It too ensures problem solvers tackle the issues they are trying to address back at the first principles level. Figure 6 describes the basic steps of the process.
COBRA+ process.
The process is also template-based in order to swiftly enable problem solvers to work through a logical complexity-embracing sequence of steps without a long learning curve [19]. The overall process forms a cycle, and as such, allows a problem solver to undertake as many iterations as might be necessary to achieve an ‘appropriate’ solution.
The detailed tests for what might be classed as ‘appropriate’ are contained within the process, but essentially focus on achieving ‘solutions’ that a team is happy enough about to consider exposing to prospective customers to receive their feedback. Having obtained such feedback, more likely than not, a team is likely to find themselves passing around the COBRA+ sequence again. And again. One of the biggest difficulties, indeed, when dealing with this kind of customer-change complexity is knowing when to stop. The closest thing to a heuristic that exists to date is that the most likely (2%) winners will be the ones most capable of working through the cycle more swiftly and effectively than their competitors.
Which then leads to a final discussion around the meaning of the word ‘effectively’. Systematic here needs to mean something better than trial and error iteration. The overall evolution trajectory towards an eventual ‘Ideal Final Result’ outcome is one way of helping to assure this happens. The next comes from recognising that each loop around the COBRA+ process forces project teams to identify and find solutions to at least one Contradiction. The final, and perhaps most important one emerges via another piece of long-term research. This time looking at the meta-level evolution of industries with the aim of revealing repeatable patterns of success. Which, thanks to the contradiction-solving DNA effectively means looking for patterns of contradictions and their resolution. This is in effect another strand of the TRIZ research philosophy. Where – probably more by luck than judgement – it was found that by removing the 98% noise of coming from failed innovation attempts, what would normally looked like a host of random evolution trajectories, actually became a series of very clear step-change patterns. Patterns that, once innovators are aware of them, effectively provide a road-map to reliable and repeatable success, irrespective of prevailing societal and/or market turbulence.
As industries make their inexorable transition towards Ideal Final Result ‘perfection’, the journey involves a succession of discontinuous s-curve jumps. As one customer solution matures and hits its ‘stuck’ plateau, eventually along will come an innovator with a contradiction-solving solution to start a new s-curve. Almost invariably, the start of this new s-curve will present customers with a solution that is ‘inferior’ in many ways to the incumbent solution, but offers some form of advantage to certain niche situations. Preferably these niche situations will be high value customers prepared to pay a premium for the privilege of their niche advantage (think about the first mobile phones for an iconic example of this dynamic in action). If innovators are able to find such customers, the early revenue they produce, will pay for further developments of the solution that will make it progressively more attractive to a wider variety of customers. And by this means, the new solution will gradually begin to climb its s-curve, until such times as it too becomes stuck. If the innovator has chosen their new solution well, the ideality of their new solution will be higher than the peak ideality of the previous incumbent solution – Figure 7.
Evolution trends as roadmaps to the ideal final result.
Such is the way of the world of discontinuous innovation: things will tend to get worse before they get better. This is another challenge for Operational Excellence dominated industries – where KPIs that acknowledge things may get worse for a period of time are virtually non-existent. The problem is not so big in the e-service sector, because the rate of s-curve jumps tends to be much higher than in most (non-digital) industries), and investors are more accustomed to the s-curve rollercoaster ride.
The relative speed of the e-Service sector jumps, once the noise associated with failed jump attempts is removed so only the successful ones remain, turn out to be one of the best ways to reveal just how clear the road-map to success actually are. Figure 8 illustrates one of the most vivid and important of these patterns. One that was first revealed in the work of Gilmore & Pine [20], and is now generally know as the ‘Customer Expectation’ Trend.
‘Customer expectation’ evolution trend.
Each stage of the Trend in effect represents an s-curve, and the direction of travel occurs from left to right. The e-Service sector in effect emerges thanks to the jump from the second (‘Product’) stage of the Trend to the third (‘Service’). One of the implications of which is that innovators looking for innovation opportunities would do well to look at industries and sectors that are still at the Product stage, and, preferably, are at the mature end of their current s-curve.
This Customer Expectation Trend was one of the first business evolution patterns to be uncovered. To date, the research has now uncovered over thirty other discontinuous evolution Trend patterns [21]. Lack of space here prevents examination of all of them. What follows, however, are what might be thought of as the next four in a ‘Top Five’ evolution roadmaps for e-Service businesses:
Figure 9 illustrates the ‘Segmentation’ Trend. It applies both to the internal structures of a business, but mainly, in the e-service context, to the segmentation of customers. The left-to-right trend trajectory effectively tells a story of customization and personalization of services. By the time a service has evolved to the next-to-last ‘Segments of One’ stage, the business has recognised that every customer is different to every other one, and is able to tune the service to suit each individual customer need. The final stage of the Trend takes things one step further and sees service providers acknowledging that not only is every customer unique, but that they are also unique as their moods shift dynamically. In many ways, this Trend is the polar opposite of the core Operational Excellence drive for standardisation, a standardised solution being the one that traditionally delivers the best profit margin. This standardised
‘Segmentation’ evolution trend.
…and that in turn has been made possible thanks to the next Trend, ‘Reducing Human Involvement’, illustrated in Figure 10.
‘Reducing Human Involvement’ evolution trend.
The reason customisation of solutions costs providers money is because delivering a customised service means having large numbers of highly capable and therefore expensive, staff. By replacing these staff with intelligent and increasingly emotionally aware digital equivalents, service providers will ultimately achieve the best of both worlds. How quickly this replacement will occur depends to a large extent on how quickly and how effectively the emotion-related first principles described in Figure 4 can be absorbed into the software. On this front, the immediate good news is that we know what the job to be done is.
As ever, of course, any kind of progress inevitable generates some form of collateral damage. In this case it looks like the collateral damage will come in the form of swathes of service jobs being displaced. A partial answer to this contradiction may be seen in the next Trend. A Trend showing innovators that in addition to the ‘things get worse before they get better’ characteristic of s-curve jumps things, as a solution evolves along its s-curve there is a clear pattern of increasing-followed-by-decreasing complexity.
During the initial ‘increasing-complexity’ portion of this curve, the e-service world is likely to see a host of integrated solutions (in which multiple services are combined into ‘one-stop-shop’, end-to-end offerings) and hybrid solutions in which human service providers are assisted by data-providing digital assistants. It is already established in the insurance industry, for example, that AI algorithms are already capable of making better loss-adjustment decisions and, in a smaller number of cases, fraud-detection decisions than the average employee, but, in order to ensure the emotional needs of claimants are also met, the average employee is still, for the most part, much more capable than even the best ‘emotion-equipped’ AI.
In the final analysis, however, the decreasing-complexity portion of the Figure 11 Trend sees the contradictions of these kinds of human-computer hybrid service solutions being solved such that the customer receives all of the benefits they desire from a service without any of the attendant complexity. This is not to say that the complexity has disappeared per se, but rather that it has been subsumed into the algorithms and is therefore hidden from the customer’s view.
‘Increasing-decreasing complexity’ evolution trend.
Fifth in the Top Five e-Service Trends is the Customer Purchase Focus Trend reproduced in Figure 12. This Trend works a little differently from the previous four. At least in so far as implications for service providers. The step-changes described in this Trend examine the non-linear shifts in focus of customer attention as their relationship with services evolves. Initially, on the left-hand-side of the Trend, customer purchase decisions are largely based on their need for performance. As these needs become satisfied, performance thresholds will emerge, beyond which, customers will be no happier and no more likely to purchase the service should providers continue to increase them further (many Microsoft solutions crossed these thresholds some time ago – the majority of Word users, for example, do not use 90 + % of the available functionality of the software, and compatibility issues aside, would be quite happy with the capabilities provided in Word 2). When customers perceive they have achieved enough performance, their primary purchase attention shifts to reliability. And then, when they have enough of this, their attention shifts again, this time to convenience. Finally – bad news for providers – when customers have enough performance, reliability and convenience, their purchase decisions are made solely on price. Which effectively means that the service offering has become commoditised.
‘Customer purchase focus’ evolution trend.
The job of providers when service offerings approach or reach this final stage is to innovate in such a way that they are able to shift customer attention to new measures of performance. One likely candidate in this regard, to return briefly to Figure 4 one more time, is that ‘meaning’ will become a generically applicable new performance delivery opportunity. One that the Covid-19 pandemic, again as discussed earlier, seems likely to play a significant role in bringing to the front of many e-service customers’ minds.
The commonly held advice about making predictions of the future is to avoid having to do it if at all possible. No-one can predict the future beyond the next 400 days [22]. In the turbulent times triggered by the fall of the pandemic domino, this number is becoming lower, and with every additional falling societal domino, is tending to become lower still.
What the TRIZ and Systematic Innovation research has shown, however, is that just because we cannot predict everything about the future does not mean we are not able to predict anything. If nothing else, the Trends of Evolution described in the previous section are a good way of informing innovators that, while it might be difficult/impossible to know
First Principles knowledge, meanwhile, is remarkably stable [23]. The laws of physics are essentially just that: laws. As mankind’s understanding of these laws evolves, the ‘first principles’ will evolve too, but their half-life generally speaking is measurable in decades or centuries. More subtle, but the TRIZ-originated innovation-DNA research has also revealed the relative stability of knowledge pertaining to the emergence and resolution of contradictions. Innovation – the successful transition from one S-curve to another – is in effect driven by this contradiction story. Innovation, to all intents and purposes, is contradiction solving. Knowledge pertaining to how contradictions are solved will thus inevitably become one of the critical factors in the e-Service innovation story. If organisations are not managing the contradictions in their e-Service business, they are placing their future on a path with a 98% likelihood of failure.
Supporting women in scientific research and encouraging more women to pursue careers in STEM fields has been an issue on the global agenda for many years. But there is still much to be done. And IntechOpen wants to help.
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