Getting Your Data Straight

A guide for managers and business owners.

‘Big data’ is all the rage right now. It is one of those phrases that has for a number of years enjoyed a comfortable coast along the upper echelons of the ‘buzz word top 40’ — but with good reason: data is rapidly cementing itself as a new asset class, and thus should be treated as such. Also, in lieu of the recent data scandals of 2018 (Facebook, MyHeritage, Aadhaar) it is becoming increasingly apparent that there needs to be a greater consensus with regards to data quality, and data security.

Luckily, there exists entire bodies of knowledge pertaining to Physical Asset Management, Quality, and Risk — each of which can now be harnessed and adapted to aid in the management of our more elusive friends: data — and the information gleaned from it.

An Influx of Data

Over 90% of the data that has ever existed in the entirety of human history has been generated in just the last 2 years — and this blazingly rapid development shows no signs of slowing down; according to the Economist, nearly 2MB of data will be created per person every second by the year 2020.

When looking at the leadership of Fortune 500 companies — about three in five leaders believe that failure to become data-driven could well lead to obsolescence. It is thus becoming common knowledge that analyzing your company’s data will indeed become core in staying competitive.

Two Layers

It needs to be understood that the world is increasingly being divided into two layers — a physical layer, and a digital one; we are also increasingly interacting with proxies for the physical layer rather than the interacting with it directly, as in the past. This is particularly true in the Asset Management (AM) industry when dealing with large companies — each with numerous and valuable physical assets.

The all-too-familiar physical layer is the actual physical world. It is your infrastructure, factories, machines, and devices — and of course, your people; it is what 50 years ago, you would need to manage directly — through observation and chain-of-command.

The digital layer is made up of data and information. It is your IT and financial systems, your protocols and machine data, your web and social media presence; it is a digital footprint containing all information that the physical layer can provide — and as digitalization and hyper-connectivity advance, so this layer grows too.

The World is Being Divided into Two Layers

The proxies through which the physical layer is progressively being managed are numerous, they can be your SCADA systems, your Internet of Things admin portals, your ERP systems, and Business Intelligence Dashboards — to name a few.

What is important — though — is to realize that all of these proxies, through which the physical layer is to be managed, depend on your data. It is extremely important to get your data straight — because, with bad data, your link to the physical world falters, and it is easy for organizations to be flung into the domain of chaos and disorder. Within this domain, decisions are made based on information that is often incorrect — and the decisions themselves result in actions which are filtered down through a complex, bureaucratic game of broken telephone.

The Collision of Industries

The present is the time in which the above-mentioned layers provide the backdrop against which whole industries collide and converge. Industry disruption is by-and-large an outcome of the evolution of both key technologies, and consumer behavior — with this behavior often as a result of the change of the technological landscape. Key technological disruption, in a broad sense, creates convergence nodes between industries that were previously confined to their own segment.

The first sectors to experience this convergence were technology, media, and telecoms: we have now become used to watching movies and TV series through telecommunications companies and buying books and music through technology companies.

Today, new waves of industry convergence are becoming apparent. Here at Gaussian, we believe these to be the two, most notable ones:

  1. The convergence of Health Care, Consumer Products, Insurance
  2. The convergence of Utilities, The Built-Space, Transportation, and Telecommunications
The Next Wave of Industry Collision

In South Africa, we are already seeing the first wave unfold before us with the likes of Discovery and Momentum (two local insurance providers) beginning to make use of various smart devices to monitor customers’ health and tie data into their offerings.

The second wave is the one in which we at Gaussian, are most interested — this is the wave that will enable the increased adoption of the ’smart city’; it is the wave in which physical assets really meet their intangible counterparts; it is the wave where utilities begin to rethink and transform their operations to make use of real-time data; it is the wave of outage management, distributed power, and advanced asset management. And all of this is made possible through the use of data.

So this data better be right.

The Horrors of Silo’d Data Integration

We were involved in a project for a coal mine recently; we were asked to analyze their data — and help them make better decisions with it. What we found was that the mine was collecting data from various sources — and storing it in different places:

  • Their finance data was stored in SAP (their Enterprise Resource Planning, or ERP, system)
  • Their transactional data was stored in their Computerised Maintenance Management System (CMMS)
  • The results from their oil analyses were store in various Excel spreadsheets
  • Their master data was stored in a separate, self-hosted database
  • Their safety incident data was stored in their safety incident application

Integrating this data is similar to American, an Italian, a Frenchman, a Spaniard, and a Swede; each with different and valuable knowledge; sitting down and trying to play trivial pursuit. They all speak different languages. Collaboration is difficult.

Siloed Data Can Prove an Immense Challenge for Organizations Wishing to Make Use of Data Analytics

In the same way, integrating data from various sources is tedious, time-consuming, and sometimes downright impossible! There is more often than not lots of duplicate information; each source refers to things (employees, assets, dates) by different names or in different formats; and much of the data ends up going unused.

If the above scenario sounds eerily similar to your own company, you are not alone! This is (unfortunately) the case for many medium-large organizations; ensuring data quality isn’t a walk in the park.

ISO 8000, a global standard for data quality and exchange, provides solutions to these kinds of problems.

The Importance of Standards

Standards are published documents that establish specifications and procedures, they help to describe protocols that improve compatibility and interoperability. Most standards are designed for use in contracts, so that people doing business with each other can ensure that they are ‘on the same page’, so to speak.

As a standard is globally adopted, it serves to vastly reduce costs and create improvements in international trade — to stand any sort of chance of being globally adopted, however, the standard itself has to be of a certain quality. The quality of standards depends mainly on two factors, namely:

  1. The expertise and reputation of the domain experts that developed it
  2. The process used to establish consensus

Probably the largest and most well-known standards organization is the International Organisation for Standardisation or ISO; this is an independent, non-governmental organization with a membership of 163 national standards bodies. As they mention on their website, ISO was founded with the idea of answering a fundamental question: “What is the best way of doing this?”.

ISO started with the more obvious things such as weights and other measurements but has over the last 50 years developed into a family of standards that cover everything from the clothes we wear to the Wi-Fi networks over which we video chat.

But the standards that we are most interested in — and that top-management should be interested in too — are ISO’s suite of management system standards. These standards provide clear definitions of the ways in which organizations should manage the inter-related parts of their businesses, so as to achieve their goals. There are several ISO management system standards, several of which are listed below:

  • ISO 45001 | Occupational Health and Safety Management
  • ISO 14001 | Environmental Management
  • ISO 9001 | Quality Management
  • ISO 55000 | Asset Management
  • ISO 8000–61 | Data Quality Management
  • ISO 31000 | Risk Management

As we are zeroing in on data, ISO 8000 — the standard for Data Quality and Exchange — is of most relevance. Through the implementation of the principles found in these documents, an organization can ensure the continual upkeep of quality, portable data — data that is application independent, and that is useful for making both strategic and operational decisions.

The Need for an Integrated Management System (IMS)

What is interesting — and worth consideration — is the fact that as industries merge and new industries arise, so to do the lines separating these standards become ever more blurry. In addition to this, the above-mentioned management standards are actually extremely similar. Each and every one of these standards share a plan-do-check-act structure and have similar requirements such as:

  • Documented systems
  • Control documents and records
  • Training
  • Internal auditing
  • Corrective/preventative action
  • Management reviews

The point here is this: organizations need to incorporate an integrated management system, that above all allows the making of data-driven decisions, both operational and strategic.

There is an Increasing Need for a Data-Driven, Integrated Management System

The benefits of an integrated management system cannot be overstated. Your organization will experience increased efficiency, effectiveness and cost reductions; whilst minimizing disruption caused by needing several annual audits. An IMS allows a management team to rely upon one system to deliver their organization’s objectives; it allows them to pull together their systems and processes and ensure they are working as a single unit with unified objectives.

The future belongs to those that can adapt; the shapeshifters, early-adopters, and creatives; those that can create organizations which pull all of these things together and unify them. But above all, the future belongs to those who plan for it.

We will soon be releasing a 6-part blog series, detailing the process of developing a Data-Driven Integrated Management System. Stay posted @ Gaussian Engineering, Asset and Data Management Specialists.

Getting Your Data Straight was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

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