Companies have more and more data at their disposal. At the same time, technological progress in data storage or technologies such as analytics and artificial intelligence (AI) are helping make better use of this data. Sounds easy, so why do (according to the IBM Institute for Business Value) „90% of AI initiatives have yet to move beyond the test stages as companies struggle with scaling their AI across the enterprise”?
That is not revealing, but I risk the thesis that organizations can only improve their speed and quality of decision-making to gain a competitive advantage if they implement solutions where people and machines work together.
Mature organizations benefit from AI and analytics
Let’s look at the market and figures. Deloitte’s survey of more than 1,000 prominent company executives (over 500 employees) who interact, create, or use analytics as part of their work shows that 82% of them exceed business goals if all employees are accountable for analytical insights.
Companies still have the path to AI success and maturity ahead of them. Forrester’s research shows that 62% of enterprises are just starting to develop their capabilities in the context of AI. But here, too, the numbers speak for themselves. Companies that have successfully scaled AI are market leaders in their industries, and they are up to seven times more likely to increase their revenues than the companies that have not.
Results are impressive, but why it does not happen broadly? Companies often do not have enough talents and knowledge to design repeatable systems that can support their business processes by providing consistent information and delivering it to the right people at the right time. That is why businesses need to overcome some challenges to reap the real benefits of AI. Data complexity, talent shortage, and a lack of trust in AI systems are the biggest ones.
Analytics and AI in the business reality
Since the use of analytics gives such promising results, let’s take a look at what the Deloitte study says about the situation in companies. One of the survey’s goals was to determine how many people believe that their company is on the two highest levels of the maturity scale, i. e. they can say that they are an Analytical Company (level 4) or an Analytical Competitor (level 5).
Analytics Companies combine data from multiple sources into meaningful content and new ideas. Analytical Competitors rely on analytics to manage performance create new products and sources of value while adapting to rapid technological changes.
The survey shows that only 37% of respondents put their companies in the two best categories of the maturity scale. In comparison, the remaining 63% are aware of the benefits of analytics but point to the lack of appropriate infrastructure.
At the same time, three-quarters of respondents said that the analytical maturity of their organization has increased over the past year, and almost 70% expects that the business analyses will be more critical in the next three years than that is now. Moreover, business analytics is expected to be as prioritized over the next few years as other critical business value factors like risk management, reputation management, product/service, innovation, and managing growth expectations.
Why does analytics help exceed business goals?
There are many reasons why companies with the highest analytical maturity gain a competitive position. Research shows that analytics supports many strategic areas. The most important of these are improving business processes and customer experiences.
The respondents also indicated such essential areas as managing the company’s strategy or monitoring performance indicators, which is not surprising. Analytics is about making more informed decisions based on complex data. It is also a potential for continuous improvement.
The results correlate well with the Forrester research. For example, 62% of respondents point out better customer experiences, 60% underlines increased revenue growth, and 58% noticed the increased profitability. Companies also see more efficient data management (64%) and improved analytic efficiency (59%).
C-level managers have to support data-driven culture
Deloitte’s survey showed some more interesting insights. It turns out that creating a data-driven culture is much more complex than just implementing the right tools or hiring the right specialists. Therefore, the best results companies achieve if the C-level managers are advocates of the change.
But is it enough? Not. To become a data-driven company, you have to step further.
- Hire or promote leaders with intense strategic and analytical skills.
- Educate employees at all levels about the role of analytics in making business decisions.
- Make KPIs linked with analytics
- Encourage leaders to show positive examples of using data to make business decisions (cases)
- Make it easier for employees to access data analysis tools
- Use Social Proof – get inspired by discussing how other companies do it.
- Get an executive sponsor, preferably a CEO, to strongly advocate for data-driven decisions.
Analytics helps companies, but to achieve the best results, you have to reach a high level of maturity. That means implementing appropriate technologies and analytical tools and correlating it with the distribution of responsibility for analytics throughout the enterprise, i. e. involving all teams.
Buying and using analytical tools is not difficult. But, you have to change the behaviour when thinking about a data-driven company.
- Picture 1. Deloitte’s 2019 Becoming an Insight-Driven Organization survey
- Picture 2. A commissioned study conducted by Forrester Consulting on behalf of IBM , October 2019
- Picture 3. Delloite analysis
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- Picture 5. Deloitte’s 2019 Becoming an Insight-Driven Organization survey
- Picture 6. Deloitte’s 2019 Becoming an Insight-Driven Organization survey
- Picture 7. A commissioned study conducted by Forrester Consulting on behalf of IBM , October 2019
- Advancing AI ethics beyond compliance: From principles to practice, IBM Institute for Business Value, April 2020
- Overcome Obstacles to Get to AI at Scale, Forrester Consulting Thought Leadership Paper, January 2020