Are you also feeling overwhelmed with the amount of information you are exposed to? Not only the work environment, but also your social media footprint affect the size of data you have to deal with, every single day. I very often find myself struggling to control my desire in feeding my intellectual curiosity and as a result, get lost through the big deep infinite ocean of data. I eventually figured out that the only way to manage this, is to define a personal strategy to create a narrow band of flow, say a tiny little rich river, which is connected to the ocean of data, and feeds me with what I need and more importantly can use. I think the organizations are no different than individuals in this sense. Either you manage the way you populate, handle, sort, and analyze the big data wisely or you get lost.
But, what exactly is big data? Big data is defined by the European Commission (EC) as “large volume of different types of data produced with high velocity from a high number of various types of sources”. In different definitions we observe the following “V”s being used as aspects of big data and should be taken into account while the organizations define their strategies:
• Volume: refers to the amount of data (e.g. terabytes or exabytes)
• Velocity: is the speed of information generated and how fast the data is processed
• Variety: represents the variation of data format (structured: traditional numeric/text information versus unstructured: social media postings)
• Value: cost of data generation as well as transformation of big data into valuable new insights, solutions and decisions
• Veracity: uncertainty due to incompleteness, approximations and inconsistencies
• Validity: is the question if the data is valid for the problem
What should be the right strategy?
Data is indeed great, and research supports that the use of big data would certainly improve the quality of decision making, processes, services and products. Nobody wants to miss the opportunity of making the right decision to flourish. Yet, most companies are after collecting data without a certain set of objectives. And some are complaining about the size of data to be managed, and wandering around the big circle of actions, without doing anything valuable. Neither of the two approaches could be considered as “the strategy”.
The right strategy defines what data you need, how to make it available and accessible, where to store it and more importantly how the data supports the objectives of the organization. Companies and fucntions should focus on the most critical and the most value-adding data while designing their master plan.
Big data is a challenge for audit functions too.
What does this mean for the audit organizations? If one raises the question on where the auditors spend most of their efforts, the single best answer would be the “data”. From preparation to writing reports, from manufacturing floor assessment to management reviews, all they do is mining, finding and analysing data in order to gauge the risk for the operation. It was never an easy task, but with all the new requirements, technologies, networks and applications, a huge volume of data is being generated every single day of operation. It is true that it has never been this complicated and difficult to manage even during an on-site audit. Introducing remote audits as an integral part of the overall assessment makes it even more complex.
For most global organizations, particularly growing inorganically with acquisitions, it is practically impossible to be connected to all operations, to get any data with a single click from a PC. The structure of the company with its affiliates also affects the overall data management strategy of the company. Suppliers, as being complete different entities, are adding another thick layer of complexity to the entire equation.
Is it possible to overcome the challenges?
There will always be challenges and here are a few suggestions that could help audit functions to overcome some:
1. Have the list of critical set of data required for each type of assessment:
• What: define the data required together with the other data correlated
• Why: define why you need it, which objectives of the company or the function are to be met
• Where: define where the data is stored
• Who: define who is accountable
• How: define how the data is to be retrieved (could be manual or via a software)
2. Ensure the reliability and use of the critical data:
• Do not estimate that the data generated is always reliable. Define ways to cross check the critical data using different sources (i.e. machine performance records, lab tests, line controls)
• Understand how the data is to be used for continuous improvement within the operation
3. Frame your digital transformation for the right size:
• Define where your function is, in terms of having access to the required set of data and/or ability in making a sensible analysis using those. The right and effective digital transformation would help the function make an effective and easy correlation between all data linked (i.e. sanitation records, product testing results, air quality monitoring results)
• Plan your digital transformation simple, by focusing on the most critical data, rather than trying to make it a bigger and more complex exercise
• Define the investment -both on hardware and software – for the project
• Work with legal affairs to sort out issues/challenges regarding confidentiality, GDPR etc.
• Work with IT department on the security and correct storage of data
• Prepare your project plan together with milestones and have the right talent to manage it.
This is probably the most difficult task as it involves many different aspects and functions.
There is no silver bullet to make the digital transformation fast and easy. However it is for certain that the audit organizations who arm their auditors with right tools to analyse the most critical data in the best way possible, will witness an uplift in productivity and engagement in the long run. Here lies the secret: Are you willing to increase the perceived value of your function? Then be the king of the data you manage.
By Tülay Kahraman
15 June, 2020
