Innovatively incorporating digital analytics for CEO’s, CTOs and other C-Suite members can gain a competitive edge, according to Google Cloud Leaders who came together to pen an article on data trends to take business forward in 2021. The number one priority for businesses in 2021, as stated in this article, is to drive digital transformation through data and analytics. Survey data shows that a whopping 66% of Boards of Directors listed digital technology initiatives as their top priority in 2021.
The question that has come up daily by our clients holding senior management roles in the last week: what do we recommend that they put in place to leverage digital analytics and data insights in order to keep them in line with the trends that can propel their business forward in 2021? The primary lesson learnt grappling with the ramifications of COVID-19 is the importance of technology. Digital technologies, now more than ever, is helping to deal with another upcoming year of unexpected change and events as we all prepare for a move to post COVID normal.
The biggest impediment to business progress isn’t the lack of understanding that data, digital analytics and AI (D&A) are the need of the hour. Rather, it’s the lack of a culture and process that values data and analytics, preventing their integration into business culture. According to Gartner, Boards of Directors and CEOs believe data and analytics is the revolutionary technology emerging from the COVID-19 crisis that is now considered the No. 1 priority for 2021. Hence integrating digital analytics for CEO’s and CTO’s to leverage insights for business decision is critical.
Although the path is fraught with challenges in this year, the top two concerns include:
- Nurturing a culture of D&A in the organization
- Incorporating D&A into decision making
Top three foundational steps to building a data and digital analytics culture
1. Understanding the difference between Data Science (Business Intelligence) vs Digital Analytics
For a company to build a strong D&A culture, which incorporates the data into the decision making, clarity and communication of the difference between data science, business intelligence and digital analytics must be understood from the top. Let me compare this to the setup of a finance department. A finance department has a mix of bookkeepers, accountants, controllers, chartered accountants and financial directors. Without the inputs from the book keepers, a CFA can’t run financial tax reports. So if you only hire a certified tax accountant you may not get preparation of yearly budgeting plans. This is the same for data and analytics. Think of business intelligence and data teams as the builders of data models.
Data scientists design and construct new processes for data modeling and production using prototypes, algorithms, predictive models, and custom analysis.
Digital analysts examine large data sets, both qualitative and quantitative, to identify trends, develop visualizations, and create visual presentations to help businesses make more strategic decisions and drive continual improvement both online and offline. Understanding this difference can possibly save a company hundreds of thousands of dollars on consulting.
2. Understand the play of Digital Analytics toward business decision making
Continuing with the finance department analogy, non-financial C-suite members have learned key financial terms and order of operations to confidently place value of financial data toward business decision making. The same thought process should be applied to data and analytics to truly reap its benefits.
For example, we all understand that bookkeeping is a day-to-day activity and required as a foundational part of accounting, yet accounting and finance, which are both residing in a financial department, are separate but dependent. The outputs of each are different based on the level of detail required toward business decision making.
Fundamentally, the outputs from digital analytics is to answer questions such as why digital sales dropped in a certain quarter, why marketing fared better in certain markets, how attrition affects revenue. In short, digital analytics should be viewed as your first line reporting and analysis and is key source data to provide to data scientist.
Digital analytics teams dive into well defined data, using varying sets of tools to draw meaningful insights that influence business challenge fixes or propose business opportunities. However, we often see larger companies request insights and reports that are standard digital analytics outputs from the data science team hence a key impact of this misdirected inquiry is that it can take weeks for a data team to produce a report that a digital analytics team can create in a day.
When you need real time sales activity reports, ask a member of your digital analytics team.
When you need data model creation of correlated data sets for long term forecasting, ask your data scientist.
Understanding this difference can save your hundreds of thousands of dollars in capital and revenue expenditures involved in incorrect department set up, wrong hiring of people and unused expensive enterprise technology tools.
3. Through-lining digital analytics with company and division goals
The ultimate goal of any business is to drive leads and conversions. Set up your digital analytics for CEOs and C-Suite framework first. By setting up the right framework for D&A, you access real-time data, utilize dashboards that actually tell you something of value, and have the team able to report up to the gold standard of leveraging predictive and AI. For example, predictive measures is truly the golden nugget that can be effective for any CEO or CDO in gaining an edge over competitors. Your company must have the appropriate digital analytics set up to delivers standard reporting and is required set you up for more advanced use like predictive measures and audience building through machine learning.
In Google’s recent new data model upgrade for digital analytics called Google Analytics 4 (GA4), they are touting three new predictive measures that is derived directly from your digital analytics. These include:
- Purchase probability
- Churn probability
- Revenue prediction
With these predictive capabilities, you can identify the users or actions that are most likely to lead to a conversion. This can help drive real results and influence decision making by helping you find more users who are most likely to make a purchase within the next 7 days. But these golden nuggets can’t be realized unless the C-Suite aligns on and cascades guiding principles, purpose and process to educate and incorporate a D&A vision within each department.
Clearly understanding the role of digital analytics for CEO’s first must be established. Only then can setting the strategic course for departments to through-line their division objectives, department goals and campaign KPI’s with digital analytics can yield unprecedented cross-department collaboration – in short it’s just plan good culture move that everyone can see the results.
A D&A culture is imperative, and not just helpful, for organizations. Developing a strong D&A culture begins with foundational understanding of the opportunities of digital analytics and integrating digital analytics for CEO’s, CMO’s and CTO’s. With its advanced and real-time data reporting, companies can focus on user engagement resulting in higher revenue, sound technology investment and happier staff and customers.