Management

Sleep and Hulland (2019) emphasize the importance of developing an integrated approach between marketing and IT around data management and data analysis.

As customer-centric strategies, data-driven decision-making and big data are currently increasingly important topics, the relationship and cooperation tween chief marketing officer (CMO) and chief information officer (CIO) is be-coming significantly important. According to Harvard Business Review (2015) new technology innovations are progressively moving from IT to marketing.

However, marketing is not necessarily knowledgeable about how to deliver tech-nological IT projects, thus, close cooperation between the two is required in order to successfully manage the new technology innovations.

The cooperation between marketing and IT is likely to drive creating a seamless customer experience (CMO Council, 2010; Sleep & Hulland, 2019). In-teractive marketing, meaning marketing efforts that are targeted and personal-ized through customer behaviour analysis, is strongly dependent on effective business intelligence (BI) operations and the marketing practitioners’ knowledge to execute marketing analytics (Germann, Lilien & Rangaswamy, 2013; Stone &

Woodcock, 2014). As Accenture’s research has shown, the marketing-technology alignment is one of the top priorities for many organizations, as the cooperation evidently enables becoming relevant to consumers across all customer touch points (Hartman, 2014).

Hartman (2014) states, that the collaboration of marketing and IT is a pre-requisite for designing successful customer-experiences. By aligning the insights

and business intelligence that IT is able to provide to the brand knowledge mar-keting has, they are able to provide valuable customer experiences. The capabil-ity to address business intelligence needs and implementing them is a crucial part of connecting and developing the relationship between IT and marketing (Stone

& Woodcock, 2014). Sleep, Hulland and Gooner (2019) further emphasize, that defined roles and responsibilities between marketing and IT regarding new so-lutions is necessitated, as communication between IT and marketing can be in-convenient and hard if the departments do not speak the same language and do not have an interpreter. Therefore, a role that links the technology and marketing knowledge with the right skillset is required to go forward.

Stone & Woodcock (2014) defines business intelligence (BI) as a business function that transforms data into useful insights that support business. BI can be either a separate function or part of IT function in organizations. Marketing commonly utilizes BI especially for reporting, online analytics, past and predic-tive analytics such as NBO or NBA modelling, as well as data and text mining.

Stone & Woodcock (2014) propose three key points, that are particularly im-portant in regards of connecting BI and marketing: (1) Developing a strong data culture; (2) Connecting BI to marketing, sales and customer service; (3) Manage-ment of BI developManage-ment and use.

Sleep, Hulland and Gooner (2019) state, that a collaborative organizational environment with integrated customer-oriented strategy and a single view of the customer, instead of siloed functions, are described as key capabilities for firms evolving to data-oriented culture and decision-making strategy. Further, German, Lilien and Rangaswamy (2013) argue in their study, that high marketing analyt-ics skills have a positive influence on marketing analytanalyt-ics deployment, which can also indirectly positively impact to organizational analytics culture and analytics deployment. Thereafter, marketing teams need to gain modern technology skills in order to become more data oriented. The skill to understand both technology and business side of decision-making and translate the business needs to data scientists and then interpret analytics to marketing managers is required to go forward. (Sleep, Hulland & Gooner, 2019.) The combination enables common language, deducts disagreements with other business departments and creates a valuable link between technology, insights and marketing (Henke et al. 2016).

As BI supports users with tools and data, it has to be appointed who makes sure the data are understood, adopted and used correctly (Stone & Woodcock,

2014). Stone and Woodcock (2014) state, that misunderstandings and limited communication can lead to a situation where BI is demanded to develop new analysis, models and reports only to support the marketing results. The issue can be solved only by the partnership between BI and the users by clearly stating the roles of users, managers and BI.

To sum up, Stone and Woodcock (2014) propose a strategy where central team manage how the data and tools are used, with BI having a control over the content of the dataset. The team should maintain a clear focus on the strategies that require support from BI and ensure, that higher management has a clear view of how BI benefits the whole organization. Thus, the marketing strategies that need BI support have to be clearly defined and prioritized.

Thereafter, it is of high importance that the link between marketing and BI is strong. The role of linking the two together should understand both market-ing issues and opportunities and data science, as this operational model assures the validity of the results across organization. Stone and Woodcock (2014) sug-gest that a strong focus should be kept on the marketing and customer strategies that guide the BI needs to support marketing. When strategy leads the BI needs, it helps avoiding a problem, where the users of BI tools determine BI needs to support marketing without clear focus on strategy, leading to long planning and delivery times and unavailing information. The operational management model is presented in figure 3 which is derived from the article by Stone & Woodcock (2014).

FIGURE 3 The proposed strategy to manage the BI requirements based on the article by Stone and Woodcock (2014).