“Water, water everywhere, Nor any drop to drink”. Immortal line from “The Rime of the Ancient Mariner” by Samuel Taylor Coleridge. The speaker is a sailor on a stranded ship who bemoans the lack of drinking water despite being surrounded by seawater. This timeless statement has been extended to apply to any situation where deriving value from a plentiful asset is frustrated or well nigh impossible.
In this day and age, there might not be a greater truth spoken about data!
The Modern Data Dilemma
Since the advent of the Industrial Revolution, when efficient throughput through automation was the order of the day, business leaders have been focused on leveraging data and metrics for continuous improvement and optimisation. Books were written about the subject and buzzwords like Kanban and Kaizen all permeated our vocabularies as organisations looked towards improved margins through removing waste. All of this was based on data, meticulously collected and painfully analysed data, followed by rigid implementation of insights and recommendations.
Over time, manual time-and-motion studies gave way to automated instrumentation and control systems, which in turn matured into industrial Internet of things (IIOT) sensors as intelligence moved onto the edge (from the cloud). All the while, more and more data was getting easier to collect – not always to analyse.
The Rise of Dark Data
Other business sectors followed suit as our need for and ability to create data soared. The consumerisation of IT brought billions of connected devices to the world, each of which has the ability to create its own sets of data about people and things. Increasing and ubiquitous connectivity in the era of digital natives (people born into the information / digital age) has turned social media into active listening posts for consumer sentiment and preferences.
As known markets saturated, businesses became increasingly in need of new products and markets. Enter the hyper-scalers who have led the way in translating online services into hyper-granular “market of 1” intelligence. More and more data is being created by consumers as they go about their daily scrolling, listening or posting.
Organisations have also continued to create masses of data to the point where studies have confirmed that up to as much as 90% of organisational data is “dark” meaning it is created and stored without any plan to be used in any form of mainstream analysis and decision making. Large chunks of this could be because of compliance or even machine logs. In our Location Intelligence line of work, we continuously come across organisations of all sizes that create high volumes of data just by running their business. Most of these organisations do not know what the value of this data could be to themselves or others. Whilst this data isn’t technically dark – it’s in the same realm of existing data without a specific value-added purpose. We consider this dark data.
Whilst all this data continues to be created, the need for competitive intelligence, differentiated products and unique value propositions also continues to rise. Digitisation has lowered barriers to entry in most markets so competitive forces are at an all-time high across sectors.
The Need for Competitive Intelligence
Consultants and other innovators have continued to build entire businesses out of helping organisations make more sense of their data. We have progressed through the eras of executive information systems into business intelligence, analytics, advanced analytics, predictive analytics and even the promise of cognitive analytics. We are well and truly now enjoying the early stages and excitement of Artificial Intelligence (AI) and geospatial Artificial Intelligence (GeoAI). GeoAI in particular has demonstrated the potential to discover and create data as much as it can guide and augment the analysis of existing data.
All organisations are looking for innovative ways to monetise their data. Some internally to enhance their go-to-market strategies and insights. Others externally to find opportunities to turn their data into alternate/additional revenue streams for their business.
Certain sectors have done extremely well with internal data monetisation whilst most continue to grapple with the latter.
Based on more than 2 decades of working with clients producing high-volume and high-velocity data, we have witnessed a series of amazing and challenging outcomes. Everything from misread market needs to underestimation of product complexity manifests themselves. From this experience, we took a step back and analysed success patterns and where this data has created the greatest business value in the shortest space of time. We’ve distilled the lessons learnt into these 5 critical areas which we believe are of value to any data monetisation exercise – particularly if GeoAI is being employed as part of the solution.
5 Lessons to Better Leverage GeoAI for Business Success
Lesson #1: The Basics still matter and must be done right
Regardless of how new, fancy or sexy the data tools are – the basics of data management and governance simply must be in place. Ideally data governance, data residency and ownership and data cleansing rules should be mature. Garbage-In-Garbage-Out still applies – no matter where the server sits or what groundbreaking tools are used! The death knell is when two business leaders arrive at the same executive meeting with different answers to the same question! If this happens – stop, correct and start again.
Lesson #2: Invest in the right resources
Data management is rapidly becoming a very expensive game. However, incorrect strategic decisions made on compromised or incomplete data could be even more expensive. Trying to prepare, protect and monetise data on a shoestring and as a secondary priority will almost always create rework and unhappy customers (internal or external). Identifying and investing in key tools, platforms, skills and partnerships (generally for skills) is a key part of the risk mitigation actions.
Lesson #3: Expand your (data) horizons
Whilst most large organisations have benefited from the research capabilities of external service providers, these tend to be once off e.g. to inform an annual strategy refresh. Ongoing reporting is generally based on the organisation’s data. We have witnessed that organisations extract the greatest value from their data when it is considered alongside other (relevant) data. For example, consider footfall data derived from mobile devices alongside point-of-sale data to understand how people move to and from your store in a mall if you are a retailer. Or consider demographic and credit data alongside your point-of-sale data to better understand local market preference. At GeoInt, we emphasise bringing multiple, seemingly disparate sources of data together – around a common point of interest – to make relationships between different datasets more evident through visualisation. GeoAI holds promise in finding matches between datasets and seeking location-enabled insights.
Lesson #4: Light up your dark data
At GeoInt, we light up our customer’s data by enriching it with location information. We believe that everything happens somewhere and that lighting up dark data through location will re-imagine the way that all strategic decisions are made and executed. We have seen data “come alive” when the location dimension is accentuated. There are other dimensions to use, but we recommend location being amongst them as inherent in location is movement and therefore physical journeys.
Lesson #5 : Visualise-Strategise-Optimise
Over the years of visualising data for strategic decision-making, we have witnessed CEOs literally cross the floors of boardrooms to interact with a map! A map showing how his customers move (privacy protected) as they visit his stores and those of his competitors. Visualisation of data, augmented by conversational AI’s that can understand questions about location, creates insights that inform strategic assumptions and hence create more implementable strategies. Visualising the impact of the strategy thereafter closes the loop allowing for refined strategic assumptions and a tighter coupling between strategy and execution. Visualisation brings data to life.
Take the Next Step in Data Monetization
We hope this article has added valuable insights to your data monetization journey.
Ready to unlock the full potential of your data?
👉 Contact us at info@geoint.africa👈
Discover how our platforms and services can further support and enhance your strategy.
GeoAI
