Silos Are No Place to Store Big Data

Stephen DeAngelis

March 05, 2020

“Organizational silos are without a doubt the most widespread managerial structure,” writes Bertrand Moingeon (@bertandmoingeon), a Professor of Strategic Management at HEC Paris, “even though all management textbooks warn against them. This is true for all kind of organizations, be they businesses, public bodies or non-profit organizations.”[1] The staff at the American Management Association (AMA) agrees with Moingeon’s assessment. They write, “Today’s decentralized, team-oriented organizations would seem to have made the so-called silo mentality less likely, but that just isn’t so. In many corporations, battles over decisions, finances, resources and, most important, power and authority are fought as bitterly as any street gang rumbles over territory or turf.”[2] Power and authority are often associated with knowledge — “knowledge is power” — and knowledge is often locked up in data. As a result, data in many organizations is stored in silos associated with the organizations managerial structure. A 2019 survey conducted by big data firm Syncsort found, “68% of respondents said their data analytics efforts are hampered by data siloing.”[3]

Breaking organizational silos

Numerous business analysts have suggested businesses organized around Industrial Age principles need to transform to meet the needs of the Digital Age. Part of that transformation requires breaking out of silos. “However, Moingeon notes, “for the large majority of organizations, managing by silos remain the default form of management. … In those organizations, managers devote a significant amount of energy hoarding knowledge.” When trying to undertake a digital transformation, he notes, “There is no magic wand solution, but there are concrete initiatives that can be taken to move in the right direction.” The AMA staff suggests eight steps companies can take. They are:

Step 1. Close communication gaps. Bolster communication and freely share more information.

Step 2. Be assertive. If you don’t think you’re getting the information you need or being heard by those needing to hear you, don’t let the situation boil.

Step 3. Reward cooperative behavior. The AMA staff notes, “Too many companies talk about collaboration yet reward only for individual achievement. You engender the behavior you positively reinforce.”

Step 4. Encourage innovation. Change is never easy and change champions are often required to implement innovative concepts.

Step 5. Create a culture of collaboration. “As a first step, the AMA staff writes, “open communication — in person, on paper and online — can lead to shared information and keep the seeds of turfdoms from sprouting.”

Step 6. Clarify responsibilities. According to the AMA staff, “You want your people to understand their roles. You also want them to understand the roles of others. But you also have to make clear everyone’s biggest responsibility — to delight the customer and gain market share for the company by competing with the real corporate enemy — the competition.”

Step 7. Find opportunities for cross-functional initiatives. Innovation and advancement often takes place at the intersection of disciplines. The AMA staff notes, “Encourage teams from different areas of an organization to work together. Find opportunities for managers and other employees in the organization to work in cross-functional teams.”

Step 8. Enter white spaces cautiously. The AMA staff writes, “There may be areas of the business that represent opportunities for revenue generation that no one has yet to enter. Rather than trying to take the territory without notifying other potential occupants of the white space, meet with them to get buy-in for your intervention. Better yet, agree to leverage the white space together.”

If organizational silos can’t be broken, the siloed data problem (i.e., data effectively denied to other areas of an organization) is likely to remain.

Eliminating data silos

“The original purpose of a data silo,” writes Keith D. Foote, “was to keep secrets. … A data silo is ostensibly meant to keep private information from the eyes of those who do not need to know. Unfortunately, information that is needed by others may also stored in the data silo. In the worst case scenario, a silo becomes a dumping ground for data that ‘might be’ useful sometime in the future, and then sits there, never used.”[4] Keeping data from those who need it is the last thing a modern digital enterprise needs. Ed Thompson, CTO and co-founder at Matillion, explains, “Every business needs to be data-driven to be competitive, and the best businesses discipline themselves to bring the best possible data to every decision they make — that is where the data integration problem starts. The answers are all there in those different systems, but it’s simply not ready to be used for decision making. Nowhere near.”[5] He suggests two important steps towards eliminating data silos in businesses. They are:

Step 1: Collect all of the data into one cloudy place. Thompson notes, “The software industry has never been able to standardize its data models and while the past 40 years have been littered with attempts … the dominance of some of the SaaS vendors is at least ensuring a largely open approach across the board. At the same time, it has never been easier or cheaper to store all the sources of data and harmonize them into data sets that anyone can understand. There are plenty of tools to choose from that can vastly simplify this task.” Syncsort Enterprises CTO Tendü Yoğurtçu agrees the cloud environment is the place to start. “With the gravity of data shifting,” he stated, “organizations are trying to take advantage of the cloud’s elasticity and gain the ability to analyze and deliver trusted data into application pipelines as quickly as possible. These are the precursors to improving data accessibility and taking advantage of the emerging technologies, like machine learning and streaming analytics, that will help deliver more value out of data.”[6]

Step 2: Transform data to get the most meaningful insights for your business — and, make sure everyone can do this. Thompson writes, “It’s critically important to make sure the data and the ability to work with it is accessible across an organization. Sure, some data might be used for critical management reports that the business relies on powered by centrally managed [extract, transform, load (ETL) processes], but far more of it is most useful for everyday tactical decisions. The ability to transform that data should be a skill that is available right across an organization. Every department should have access to the best visualization and business intelligence made possible by a simple yet powerful data transformation capability.”

Thompson concludes, “Dealing with those data silos is not nearly as painful as you might think. There are a large number of extract and load tools that can centralize your data. Forget these as they only solve half of your data silo problems.” The other half of the problem is leveraging a cognitive computing platform that can make sense of the data and improve an organization’s decision-making. Swamini Kulkarni explains, “Cognitive computing systems are used to find solutions to complex situations where answers are uncertain or ambiguous, using computerized models that simulate the human cognition process.”[7] Many business decision must be made in uncertain or ambiguous situations. Bain analysts, Michael C. Mankins and Lori Sherer (), assert if you can improve a company’s decision making you can dramatically improve its bottom line. They explain, “The best way to understand any company’s operations is to view them as a series of decisions.”[8] They add, “We know from extensive research that decisions matter — a lot. Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.”

[1] Bertrand Moingeon, “Transversal management: how to break out organizational silos,” LinkedIn, 1 April 2017.
[2] Staff, “Breaking Out of Silos,” American Management Association, 24 January 2019.
[3] Brandon Vigliarolo, “Big data adoption exploding, but companies struggle to extract meaningful information,” TechRepublic, 19 March 2019.
[4] Keith D. Foote, “A Brief History of Data Silos,” Dataversity, 21 November 2019.
[5] Ed Thompson, “When Data-Driven Meets Data Silos: Let the Fun Really Begin,” insideBIGDATA, 8 September 2019.
[6] Vigliarolo, op. cit.
[7] Swamini Kulkarni, “Cognitive Computing Is Not Hype: It Is A Must-Have For Organisations,” Compare the Cloud, 24 July 2019.
[8] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.