Analyzing the future available options strains every individual. “Strategic Analytics – the Insights You Need” takes the strategy at the next level. Curated and assembled by editors and authors from Harvard Business Review, “Strategic Analytics” puts together a pretty rounded picture on the hot topic of summarizing your organizational possibilities.
Analyzing the strategic options and their implementation results for a company is exponentially more difficult. Most organisations decide themselves on embarking on a data journey, yet the resources (hardware, software and people) are not there. And even if you arranged all your resources properly, many companies fail to deliver results at the right pace.
What are the usual ingredients for a successful strategic analytics implementation?:
** Data and technology
Whilst usually data is there, organizations need to put in place processes to make sense of it. Every transaction with a customer is an opportunity to learn how to better serve the needs
** The right talent and skill-set
Analysing and transforming the terrabites of customer and market data takes talent and experience. They are hard to find and need usually serious nurturing.
** A data-driven culture
You have probably seen this before – if the management does not take the data seriously or is not raising the expectations to the right level, it will be difficult.
Once you established the critical success factors, you must roll-up the sleeves and start digging.
“Strategic Analytics – the Insights You Need” gets it nicely – it structures the analytics development in three main areas:
I Understanding Analytics Basics
This is essentially the classical methodology establishment step. Like it or not, bricks need laying: establishing goals, priorities and allocating resources to understand the treasure you are sitting on is essential.
II Becoming an Analytics Data-Driven Organization
Transforming your business model into an interactive, customer-focused organisation, is an arduous journey. Companies need time to explore the data troves they have on customers or operations.
III Applying Data Analytics
This is the point where the fun starts – based on deriving insights with a combination of marketing and data science tools, companies start unearthing valuable insights.
My favorite chapter springs from the 3rd and (in my view) most important part: “What AI-Driven Decision Making Looks Like”. I know the title sounds a bit dry and theoretical. Yet, it lays a very nice picture on how organizations can shift their decision-making processes from:
** Limited data transformed via human judgement
** AI-supported and transformed data, advanced analytics AND the human judgement layer at the end.
The difference goes beyond semantics. As the business practice showed all over again, human judgement delivers superior results when it operates with transformed data. In the modern Business Intelligence tools data-speak, “shaping” the data increases the accuracy of interpretation. Managers become closer to customer thinking and organizations deliver better suited products when we simply enlarge the customer data pool. Customers recognize faster products and services that speak directly to their needs. And last but not least, operations require less troubleshooting, as the obvious problems are semi-automatically eliminated.
So, is “Strategic Analytic” worth the time? Definitely yes – but with a pinch of salt: the reader should take in ints messages gradually…