5 Data Actions for 2018

5 Data Actions for 2018

5 Data Actions for 2018

My thoughts on data strategy, infrastructure and integration, governance, and culture — which I believe will impact organisations in 2018. Last year was the year of technology, and I think in 2018 the key trends will be more strategic in nature than technical.


  1. Everyone Needs Data Strategy



Traditionally departments have built information systems independently to fulfil their own needs. This resulted in siloed data across the organisation, data quality issues, and inconsistency in insights.

Technology is promising to resolve all these issues, but evaluating and buying analytics technologies has become very difficult. With technologies advancing: how do you know which tools will provide you with the insights you need? I know it sounds very simple, there are many organisations that lead data projects with a “technology first” principle – investing in technology before understanding what the business wants to achieve. This makes the situation even more complicated.

Ask yourself these questions: What are you trying to achieve from a business perspective: what are your goals and measures, what are the decisions you need to make, what are your key business questions that you’re dying to know the answers to?  Creating a data strategy will support these questions and more.

An achievable and well-defined data strategy will help you decide how you will use your data to improve decision making, streamline business operations or monetise it.  Data strategy includes the critical business questions you need answered, how you will collect, store and manage data, the analytics tools and supporting infrastructure you require, and the skills you need in your organisation.  Your strategy is the “why” and “what”, and the roadmap is the “how” you are going to execute.  Lastly, your strategy isn’t the status quo, it will evolve with your ongoing business needs and technology advancements.


  1. Data integration becomes more efficient



According to Experian, 66% of companies lack a centralised approach to data, with data siloes being one of the most common issues.  Currently, business data from the different silos is sequenced through many different platforms from data lakes to data warehouses, which can be time consuming and expensive to store. Data engineers spend about 60 – 70% of their time prepping and bringing data together through the Extract Transform Load (ETL) process. As the data is being transferred through the different platforms, it can often be prone to errors, and if a job fails can take hours for data to arrive at its final destination in the data warehouse.  If failures exist in the ETL process, it leads to corrupt data going into analytics applications, which results in end users receiving errors in their dashboards leading to bad decision making.

What would real-time and error free insights mean for your business?  One trend in 2018 we will see and hear more of is Unified Data Management (UDM), which supports the movement of data between different platforms without the complex ETL processes, and allows users to analyse their data in a range of outputs, such as dashboards or machine learning.  It reduces data latency, dependency on limited storage capacity, enables speed of design and development of analytics products across teams, and supports data integrity, security and lineage across the organisation and its platforms.


  1. Culture change is crucial for data projects to succeed



A year ago, Gartner estimated that 60% of big data projects fail. According to Gartner analyst Nick Heudecker‏ in November 2017, Gartner was “too conservative” with its 60% estimate. The real failure rate? “Closer to 85 percent.” In other words, abandon hope all ye who enter here, especially because “The problem isn’t technology,” Heudecker said. “It’s you.” Or otherwise culture! Most organisations still struggle with establishing a culture, let alone the notion of a “data-driven” one.  If 2017 was the year of technology, there are a few things that you can do to get away from being the 85% statistic.  So what can you do to address this issue?

Cultural change in the era of data is a clear business problem, and needs to be addressed by the data strategy.  If you are considering creating a data strategy, then there are some fundamental things that you can do.  1) Make sure you are impressing upon the CEO that she needs to lead by example, and if she is becoming more data driven, then others will follow suit.  2) Create a change team, that deals with organisational alignment and communication. 3) Identify who your key stakeholders are and get them onside as data champions from the various departments.  4) Identify “quick wins” that demonstrate value early in the project, as it will stamp out those who are going to derail the project.  5) Make sure business and technical teams are aligned in their approach and not at loggerheads with each other, another critical barrier to successful adoption of data projects. Transformation requires a considered approach, and if you can continuously identify the critical organisational issues, and address them head on your project won’t be another statistic.


  1. Data governance climbs up the food chain



$3.1 trillion, IBM’s estimate of the yearly cost of poor quality data, in the US alone.  Data governance still gets the backseat.  But, not in 2018 with GDPR, data spread across internal systems and the cloud, and privacy issues being scrutinised, it’s time for data governance to go up the food chain.  Organisations will need to implement three aspects of data governance: 1) Deploying a common data model and common business definitions across the organisation.  Not doing so will end up in sloppy insights being presented, and bad decisions being made. 2) Identifying data stewards and implementing a centralised data governance hub will be key for 2018.  The stewardship role is important because it ultimately manages the convergence of policy and technology, ensuring tight controls are in place.  3) Data lineage processes of knowing how data is stored, managed, cleansed, where it came from, who it was shared with, how it has or will be analysed etc., will provide the context for sound governance and compliance. If you don’t apply the internal discipline and coordinate efforts across the organisation, your competitor will end up crushing you, because their data will ultimately be better.


  1. Data monetisation strategies kick into gear



Often overlooked and misunderstood or thought of as something rather sinister.  You need to rethink this in 2018, as monetisation of data will lead to the creation of new data products internally and externally, providing new revenue streams which companies may not have considered.  In 2017, I spoke at conferences, about this topic and how organisations need to think about their data as one of the most valuable assets. Don’t you want to start increasing the value of your business through leveraging your data and monetising it?  Most of the top companies such as Google, Facebook, Uber etc. are all doing this creating value for their customers and partners.  The data sharing economy is something to look out for in 2018.  But going back to the basics if you aren’t a Google or a Facebook, what can you do to start implementing data monetisation strategies?

My top four data monetisation pointers for you are: 1) Understand the key pains addressed by your data or possible analytics products you could provide to your supply chain – consumers, partners, suppliers etc. (internal and external).  2) Create an inventory of your data – where is it, who owns it, how unique is it, is it granular enough, is it reliable i.e. good data quality etc.  3) Make sure you think about the relevant security / privacy / regulatory rules before using it for commercialisation purposes as you don’t want to be fined big money. 4) Ensure you look at processes, skills and the culture of your organisation as data monetisation doesn’t just happen by giving people tools and data.  2018 needs to be the year of a sound data monetization strategy, where your organisations is committed to getting their data in order and making the right investments to support revenue goals.

That wraps up my views of the data trends and outlook for 2018.  Organisations are still struggling with their data, getting value from it, monetising it, and generating new products and services from it. How will you succeed with your data in 2018?