Unlock the data, make difference with Machine Learning!

Taking data driven decisions is securing the competitive advantage and corporate success. Companies started collecting data but understanding it and using it for value creation is a challenge. Expertise in handling data is a key requirement for gaining insights from the data.

Timmer (mid-size manufacturer of pumps and dosing technology from Germany) prevented half of the production downtimes due to real-time analysis of machine data. Hero (internationally operating food company from Switzerland) forecasted 5% of total expenditure for a year of using strategic sourcing software. LEGO have been developing product for over a decade using market research and secondary data, which made then world’s top-selling toy manufacturer and annual growth of 12%.

3 key aspects to be considered:

• Organizations must select the most relevant and valuable data from multiple sources: data collection and research, data preparation and management processes are leading to a consistent quality and consolidated data sets.
• Sustainable internal competence development is essential from competitiveness cross all industries.
• External data service providers are strong partners who can complement limited internal capacities (time, personnel, know-how).

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Statista Q made research among 1200 managers in Germany, UK and USA. Following are the key findings and challenges they have identified.

Status Quo

Data is important: 7 out of 10 executives consider themselves to be part of a company with high data relevance. Data is highly relevant for transport sector. For example, mobility-as-a-service-providers use data structures, data streams, and interfaces to bundle access to mobility services in one centralized platform. They are digital ecosystems that securely connect and market previously isolated data. That’s how they are using data for creating external value.

Data shapes decisions: In Germany, 60% of executives often make data driven decisions, 30% exclusively. In US- 40% are making decisions only based on data. This is confirming that such decisions are more reliable than spontaneous, intuitive once. Data is also used for saving identification, to improve performance, and to meet financial goals. For example it can be used for comparative returns to decide investment profitability opportunities. It can be used for market and competition analysis (market size, shares, customer segments, demand intensity) and internal corporate communication. Some companies are using data for analysis of brand awareness.

Type and number of data sources are diverse: One of the challenges is analyze large amount of data collected from many different sources. The bigger is the company, the bigger is collected data. Data is a mix from internal, market research and tracking tools, publicly accessible or fee-based databases, studies, reports.?

Data is valuable: 8 out of 10 executives are responding that they are exploiting the potential of their data, which doesn’t directly lead to utilization of high value. The majority of the companies expect that from more effective use of data will lead to 10-40% lower costs and 10-50% sales increase, along with reduction of the effort to utilize the data.?

The challenges

Data literacy is essential: Data research, surveys, analysis are executives’ key areas of competence, while data and result processing are considerate as less relevant to success.

“A quarter of the companies mainly use complex methods such as self-learning algorithms or internally conducted market research. Interestingly, this group includes only slightly more companies from the US than from Germany and the UK. US executives thus lower the bar or overestimate the data literacy of their employees by rating them as “very good” even if the method complexity is rather average.” concludes Statista Q .?

Data usage is expensive: With well-trained employees and a company-wide data strategy, companies can use the potential of their data efficiently and holistically. One thing prevents them from doing so: a lack of time. As per the research results, half of the companies managed to reach limited use of the existing data potential compared with the related time investment. In one third of the companies the staff shortage and lack of know-how limits the use of data. Strategically decisive data as analysis of existing data (sales figures, costs, internal KPI), collection of primary data and research of secondary data are describing the market or competition. Around 30% of the executives disapprove of the quality and topicality of data, especially secondary data (often incomplete, partially applicable, poorly documented, outdated).?

The solutions

Dealing with challenges: Usually to handle data related problems, employees are seeking help from colleagues, supplementary free access sources, using partially the data. Competence development is one of the measures taken, along with Internal training and self-study. Along with this one third of the companies are investing in data or data services.?

Need for data services: 30% of the companies are outsourcing data-related processes. Above all, executives see a need in the areas with the most significant relevance to success: data analysis, data surveys, and data research. For them working with external data service providers can be crucial to transform business models and generate market persistence.

Spending on data and data services: half of the companies are spending at least $5?000 annually (from 12?000 to 100?000). The cheapest are fees for data management, data processing tools and access to database.?