Data fuelled decision making is the bedrock of every modern business success story. For managers to make the right call on strategic, tactical or operational decisions, they need to have a foundation on facts derived from finely honed data. The importance of data analytics for your business cannot be overstated.
Without data, the intuition and judgments churned out by the human mind can become easily contaminated with bias, prejudices, and mental blindspots leading to suboptimal decisions. Not everyone has the perspicacity of Sherlock Holmes’ dispassionate rationality when he said,
‘Once you eliminate the impossible, whatever remains, no matter how improbable, must be the truth.’
Ideally, decision-makers in an enterprise must be equipped with Sherlock-level reasoning and faith in data in order to make precise business decisions.
The reality, however, is only 20% of business decisions within a company are data-driven and most others are based on vague intuitions and obsolete experiences. Some common excuses are that the data in hand isn’t enough, or that the benefits of data analytics do not apply to them, or that it isn’t processed appropriately to derive decisions from. And this is a classic illustration of the ‘constraint thinking’ mindset.
The Constraints Mindset:
Constraints mindset is commonly the culprit behind limited success of analytics and therefore digital transformation in enterprises. To make things clearer, here are a bunch of common excuses that limit companies and their executives from enjoying the benefits of data analytics.
4 Excuses that companies and their executives come up with when they claim they are not in a position to embrace data analytics in business or data-driven decisions:
Constraint #1: We have very limited datasets/databases
Truth: It’s a falsehood for any company today to claim limited data. Even the largest of organizations have only a quarter of their generated data stored in a centralized relational database format. That doesn’t mean they have limited datasets. There are numerous data silos all across the organization that can be accessed if one puts in the effort. Not just that, for every byte of accessed tangible data, there also exists an equal amount of dark data that is of surprising value and can be put to great use!
Constraint #2: Analytics doesn’t work on unstructured data:
Truth: It is estimated that 80% of the data inside an enterprise is unstructured and this percentage is only growing. Technology has grown by leaps and bounds and today, we have the unstructured data analytics tools and technologies to parse and make sense of the data to add to the insights so far not accessed. Unstructured data management has never been this easier!
Constraint #3: Public data is not dependable
Truth: Today, the internet is a treasure trove of great, credible and current information about your environment, target markets, competition, consumers and so on. Governments are mandating more information transparency for itself and all organizations. Corporates understand web is the first choice of data access and are getting more current and informative with data in their web properties. Businesses can tap into this to gain market and consumer insights at an unprecedented scale than ever in the past.
Constraint #4: Analytics solves only a few business problems
Truth: There are a rapidly growing number of examples illustrating how every aspect of the business is being disrupted by the use of analytics and ML across every industry. Entire sectors of start-ups are coming up in every niche area using the data available and providing analytics-based insights. It’s nothing but just an analytics constraint mindset that has held back certain industries from exploring further than others.
So much for the myths. Now, what are some creative solutions?
Look outwards for data sources
90% of the data on the internet came about in the last two years and is doubling every year now. This would mean, with the right unstructured data analytics, you can turn them into dollars. There are tons of credible and relevant information flowing in daily – financial reports, regulatory filings, research data, news sources, social media and so forth giving insights about the industry, competition, target markets, and consumer interests which can be game-changing. Find them, and reel them in!
Embrace big data complexity
Yes, there are challenges when dealing with different media formats, data types, unstructured content, multiple sources, credibility, and quality. However, with big data becoming mainstream and not just a buzzword, technology has kept pace to solve them. Now, every aspect of this complexity can be controlled and brought to bear with the standards of enterprise quality, predictability, governance, and compliance. Even highly regulated industries have been able to successfully navigate this landscape.
Think broad, think big
Scour the entire enterprise. Encourage every department to think about their data assets and how they can bring in analytics, machine learning, and re-engineer their processes. There are numerous examples out there for every use case. As a business, re-imagine what a start-up armed with your organization’s data & experience can build – and make that happen internally.
Some nuggets from our experience – A case study from a traditional industry
A banking customer of ours with card and credit operations always had challenges with the small businesses risk profiling.
Their traditional approach had limitations, which in turn forced them to shift focus away from that market segment. However, taking up a bold approach by tracking public data footprint including government filings, social media, and other web presence covering more than 160 sources – we were able to create a much better credit profiling with day to day tracking of trends which helped double their penetration into that market within a couple of years.
They re-engineered the entire operation, right from discovering, onboarding and their business models to fit in the new data. This was truly a digital transformation for the business and it was thanks to their ability to find data from unexpected sources and re-engineering their entire processes using the analytics value-add.
At Xtract.io, we work with 80+ customers ranging from Fortune 500 to start-ups across diverse domains solving similar challenges. For more than 15 years, we’ve specialized in data collection from the web, unstructured data management, and delivering insights. We have a repository of 100+ bots that are currently running and solving challenges around finding the right web data sources, mapping data from external and internal databases, cleansing and preparing data, building analytical insights on top of the data and so on.
Our Worxtream platform orchestrates these bots and the data sources to put together a workflow that is custom-built for your business needs. We design customized solutions and can even put together a working POC for you to test drive your solution before you commit.
We would be happy to host a discussion on your challenges and are willing to do a no-strings-attached, free consultation on what solutions can work for you. Reach out to us here and we promise it will be a time well spent.
