A recent study of Australian businesses by the Melbourne Business School and A.T. Kearney, found that Australian enterprises are falling short of their international counterparts in leveraging data analytics to improve business performance, profitability and decision making. A lack of appropriate skilled in-house resource and lack of leadership in the area, cited as the main contributing factors.
The Analytics Impact Index, is a study of more than 400 businesses with an average revenue of $1 billion across 34 countries, of which 50 were Australian. The benchmarking study was conducted by Melbourne Business School & A.T. Kearney between January and July 2018 to determine the impact analytics can have on a company's profitability, while also identifying any areas that show the most opportunity for improvement, according to the authors of the study. The study categorised participants into four stages of analytics maturity and excellence. Which were:
- Laggards. Analytics is limited to descriptive analysis of the data, and generally backward-looking reporting on performance. These companies do not yet have a clearly defined analytics strategy and lack the culture needed to move forward.
- Followers. Analytics is used to diagnose what drives business outcomes, especially cost and revenue. However, analytics is not used strategically to optimise business decisions, and there is no broad analytics culture driven by top management.
- Explorers. Analytics is used to optimise business performance by diagnosing and predicting business outcomes. Although there is an analytics strategy, the analytics culture is not well-developed across the organisation.
- Leaders. The biggest difference between leaders and laggards is the C-suite commitment, the strategic alignment between the business and the analytics strategy, and the right culture. Leaders integrate analytics into all decisions to generate foresight about relevant trends and fuel successful business outcomes. Real-time analytics help drive innovation and create a competitive advantage.
Why are Australian Businesses Not Making The Most of Analytics?
According to the study, only 8% of businesses surveyed met the criteria to be Leaders in analytics, with Chinese businesses coming out on top. Australian businesses ranked as “Laggards” in both the maturity and impact of their data and analytics capabilities. Currently extracting 12% less value from analytics than the rest of the world, while being 14% less mature than their overseas counterparts. The main reasons cited point to a lack of appropriate skilled in-house analytics resources as well as lack of leadership and clearly defined analytics strategy.
It’s Time To Skill Up In Analytics
Deloitte’s Global Perspectives for Private Companies Report released in 2018, showed that over 40% of Australian private companies were planning to invest in business intelligence and data analytics this year and looking to a more flexible workforce to achieve this. The problem is that data analytics spans such a wide gamut of capabilities (data integration, data management, data warehouse, machine learning, data modelling, application design etc) that building out a strong in-house analytics team can prove extremely costly, especially when there is a distinct lack of specialist analytics resources as we move into the territory of advanced analytics.
This is why more Australian businesses are now looking to complement their inhouse resource with specialist data and analytics resources from a BI consulting partner. Remember, it’s not the data but the people who can interpret and leverage data who are the real assets. Often the best choice may be a combination of applying internal teams alongside hired analytics specialists, whereby the inhouse teams manage the day-to-day work and you bring in external analytics specialists for the big projects, to manage workloads or to compliment internal skills gaps. You can explore the pros and cons of an outsourced vs inhouse approach to analytics teams in our previous article.
Building A Data Driven Enterprise
Mining the full value of analytics requires more than a financial investment. Building a data-driven enterprise is not just about encouraging the use of data in decision making. Data and analytics leaders must lead development of the correct competencies and rebalance work to be consistent with their enterprise’s ambitions for generating information value according to Gartner. This involves:
- Identifying and prioritising information-based outcomes and improving decision making capabilities through data analytics
- Working with enterprise executives to clarify expectations and justify a data and analytics leadership role
- Creating a plan that accounts for data and analytics competency gaps
Becoming an analytics Leader is a lengthy process but has its benefits. The Analytics Impact Index showed that analytics Leaders (only 8% of companies) see 60% more profits than laggards do. Analytics maturity can be measured in four dimensions - strategy & leadership, culture & governance, talent & skills and the data ecosystem. Laggards tend to focus on the data ecosystem ie. about having the right technological infrastructure and data management framework, often neglecting the domain of the Leaders which is strategy & leadership which looks at who within the company is driving analytics and how this aligns to the strategic roadmap of the business.
It isn’t easy to create a data-driven culture. Each oragnisation will need to find its own path, but by placing a high value on information sharing, not hoarding data and analytics, building a data capability that encourages use and is relevant and perhaps most importantly, implementing a data-driven culture with buy-in from the top; without that little will change. If you’d like to know more about how to build a data-driven enterprise download the Gartner report below.
