Interview with Ross Macinante (NetConsulting) data quality Competitive Intelligence marketing needs data updated and objective, in order to heal the relationship with customers, define new bidding strategies, study competitors. Since then it has certainly intensified the demand for computer systems tailored to the needs of marketing specialists, a need that is common to the various business functions. What was the "answer" IT? We know that in the last 5 years many organizations have invested in solutions for data profiling (to treat analysis of data and ensure their standardization), data monitoring (to check the data over time through continuous monitoring and possibly automated), and that such investments are added to the "traditional" systems of data cleansing (the solutions used to correct the data). But the results were always up to expectations? And the organizations were able to exploit appropriate tools for data management, raising the efficiency of the analytic process?
Marketing Intelligence has interviewed Dr. Ross Macinante, Practice Leader of the company
NetConsulting , who recently oversaw a survey published by the magazine
ZeroUno on the quality of data ("Customer Intelligence
knowledge to 360 degrees "). The survey was conducted through a web survey, sponsored by the company SAS, and was attended by the sample of 97 Italian companies. The
Research has shown that "more and more data quality is critical to the success of business initiatives and business intelligence is therefore the need to avoid conflicting information, inconsistent or inaccurate." The survey has revealed the presence of instruments of Data Quality, Data Integration and Master Data Management for data management and business information to support business: survey showed an average, for these solutions, 33% areas with more "advanced" as the Retail and Services (both with a presence of data quality solutions for over 40%), while the industry has only 22.7% of cases of these applicativi.
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quali sono alcune conclusioni della survey ? Il mercato delle soluzioni di data quality non è maturo dal punto di vista dell’adozione, è evidente che l’attenzione alla qualità dei dati è in aumento, ma abbastanza lentamente rispetto al mondo anglosassone. L’indagine evidenzia come la data quality sia una tematica di interesse, con numerose prospettive di sviluppo. La survey ha confermato l’interesse da parte delle organizzazioni verso le soluzioni di data integration da più fonti (Crm, Scm, Erp, Dw, Business Intelligence, Portali Web), e lo sviluppo di una certa attenzione verso i progetti di Master Data Management (gestione reference data only).
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which sectors are most interested in data quality? Certainly the Finance sector is more attentive and willing to invest to position itself as better than others, because risk analysis is becoming more important. In the recent period, even large-scale distribution has started some projects, including quite complex, while manufacturing companies today are still not interested in the quality of the data.
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what are the reasons that lead to data quality? The survey did not want to understand the motivations of organizations to ensure the quality of data, analyzing the contributions made by participants, however, showed that some vertical industries have developed a fairly good demand, such as the banking industry to adopt various solutions for data quality, because it certainly induced by the pressure of regulatory compliance. Banking & Finance for the quality of information is essential to monitor the progress of the main risk parameters and indicators linked to the performance of the business. This has been further enhanced by the integration processes that have characterized this field and have made it imperative requirement for investment banks to ensure the uniqueness of the data. In general, however, la survey ha confermato che le organizzazioni sono impegnate nel migliorare le procedure di archiviazione e consultazione dei dati, specialmente di quelli relativi alla clientela. È indubbio che, per un’azienda, disporre di dati utili a comprendere la clientela ed a studiare i mercati impatta sulla competitività dell’azienda stessa. Investire in data quality può significare potenziare le analisi della customer base, specialmente quando questa è finalizzata a nuovi prodotti/servizi.
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l’indagine ha mostrato anche aspetti trascurati ? Non direttamente, anche perché la survey voleva solo osservare la diffusione delle soluzioni di data quality. Posso affermare che are still a few companies that use data quality solutions, likely underestimated the aspect of safeguarding information assets, together with that of their better exploitation. In business, in the past, investments were directed to the SCM and ERP platforms, has not always tried to integrate the different systems, some problems are now afloat. The data quality is mentioned in some circumstances in complex situations, almost unmanageable, for example, when an error or a difference may affect the results of the analysis. In recent years it has increased the presence of tools for integrating data from different sources, but remains quite low adoption di soluzioni per l’ottimizzazione della “qualità” dei dati.
5> le cito alcuni “slogan” del passato, cioè alcuni attributi di valore dei progetti IT indicati come utili a governare i dati: visione olistica, knowledge management, customer insight, semplificazione del reporting, analisi d’insieme, dashboard e score card per misurare la customer satisfaction e la customer loyalty.
Come mai, dopo diversi anni, si parla ancora di data quality come obiettivo da raggiungere ? In realtà non si può parlare di arretratezza in modo generalizzato, in quanto sicuramente le banche sono più avanti delle aziende di altri settori e in particolare industrial companies. This is probably also due to the higher value assumes that the data for the banks than it is imputed by companies in the industry sector. In industrial companies, especially those in small to medium, in fact, in many cases lack the culture of data and information and the value it assumes for the development of business strategies. This is especially true in companies where there is no management managerial approach. I think these factors have led to neglect of data quality projects, giving priority to other projects with a more immediate impact and become more visible to top management.
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are still "unresolved" Some issues, such as the problem of functional analysis , or the problem of the analysis of unstructured data (the contents of the email, or those produced in the areas of the Web 2.0).
What might be other answers? The company can not sit still, he should still think of innovation, even in times of crisis, a company must think about their future, to plan the future. The forms of IT innovation adoption might be the best platform for business intelligence and performance analysis. Especially the performance measurement systems can give interesting answers to the manager.
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how to ensure the success IT projects for the exploitation of corporate data?
The answer from knowledge that I developed through further analysis, because this aspect was not drawn from ZeroUno. To set a strategy for enhancing the assets of an organization's information assets, it must involve the business from the outset. Often, the business has its own budget "independent", in many circumstances it is the business that chooses the solution directly, as in the case of business intelligence tools, which are chosen by the business because their users will interact with the data for rework them, study them. Returning to the previous question, that the responses, I can say that innovate business intelligence systems during the rationalization of information systems is certainly a challenge, but also give management a greater control of their business, and help us make decisions more detailed. In this context, are rightly the issue of data quality, the accuracy of which can provide analysis and forecasts on the basis of corporate strategies.
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who wants the strengthening of business intelligence? Press
especially in business, primarily the chief executive officer, undoubtedly the director of marketing, the marketing director. The motivations are different: the marketing acting on the development of new products and services, and then expects the business intelligence to aid the simulation scenarios, and the sales function can use the tool to build scenarios and understand or correct the pricing. The CEO uses business intelligence to control the company. We talk to companies, however, end "high", ie companies sufficiently organized, in which it is clear the organization of functions and responsibilities are distributed. As mentioned earlier, in these contexts may increase the space for the culture of data quality, and may propose new applications for business intelligence. The problem is firms still poorly structured, or in which virtually no one is able to direct managerial innovation and change throughout the organization.
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is considered as the data quality in CRM projects? The question is posed by those who, with a sort of skepticism, some CRM projects considered as "dangerous" because of their inherent complexity.
CRM systems concentrating large amounts of data, so they are definitely linked to the quality of information they handle, such as to allow accurate analysis of customer segmentation, to enable study of customer satisfaction and the quality of their relationship with the company. Some prejudices about CRM, which probably did not provide answers immediately effective - it is still difficult and challenging projects - have been swept away in the utilities, which in recent months have invested in CRM and BI solutions. In the future banks will be back to invest in new tools to analyze data on customers.
10> last question,
Web 2.0 and enterprise data, where do we stand? As evidenced by the survey, the ability to analyze user activity on the corporate Web site and through social networks is still an area where few companies hanno già investito. Non basta implementare gli strumenti del web 2.0, un’impresa se vuole tracciare il comportamento dei clienti e correlare le informazioni sul cliente, deve impostare un cambiamento organizzativo: all’interno dell’azienda ravviso la necessità di funzioni dedicate, dovranno essere presenti delle strutture capaci di valorizzare questi nuovi patrimoni informativi. In realtà non si tratta di una problematica tecnologica, ma piuttosto di un problema di carattere organizzativo, dal momento che si richiede un cambiamento anche nella cultura aziendale e la definizione di nuove figure che abbiano il compito di gestire questi dati.
