12 Dec Roadblocks Adopting Supply Chain Analytics
What are the roadblocks in adopting supply chain analytics? In our previous post on the Supply Chain Technology Top 10 we already touched upon some of the major challenges to adopt new technologies. In this Insight, we will focus on the roadblocks that companies face when adopting these new supply chain technologies.
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(1) Digitization of the supply chain and enabling a platform for collaboration, (2) Visibility, real-time information and demand sensing, and (3) Advanced Analytics and BI capability. As said we used the excellent work by Gartner (2019a, 2019b), Furr&Shipilov, (2019), Butner, K, (2018), McCrea, B., (2019) to compose a list of technologies and cases that we then used in our interviews with our clients. Basically, to get an idea on which initiatives are being adopted and tested given the maturity of the company. So, with digitization, data and analytics at the heart of these new technologies what is holding them back to adopt these new technologies? What needs to be solved first?
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Culture is Key
One of the biggest hurdles faced by supply chain leadership is clearly overcoming cultural challenges. And although Data literacy (skills, data, people) is the top internal roadblock. The only way to tackle this problem is first to face the cultural challenge. So, resistance to accept change is one of the key issues we came across. Data literacy problems is a top priority and calls for commonality of shared language, skilled people, fluency with data, analytics and data driven decision-making across the organization.
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The need for a data strategy
A third problem that needs to be a priority is having a clear data /digitization strategy. Many executives are definitely familiar with the concept of data-driven thinking but still many companies fail to have clear view on data, ownership and value. They struggle with what it really means in practice. What are the benefits of adopting a data-driven culture within our organization? Well, a data-driven culture is not just a belief that data are an issue for someone else in the company, a data specialist or perhaps IT. There still is a perception that a data specialist, perhaps a clever graduate, should be parachuted into an organization to advise on how to work wonders with data.
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Deep dive Data Literacy
The results show that data driven decision making is gaining a foothold within all parts of the supply chain but there are still some major roadblocks in becoming a data driven company. Lack of skills, data quality and leadership lack understanding are at the top. Perhaps most importantly, the output echoes a critical point that data advocates make repeatedly: it is not just about the data. Much attention is paid to the need to recruit skilled data specialists, an issue we address in the next post. Yet a data-driven culture cannot be built on a few experts. It requires buy-in across the organization, which in turn requires educating employees about the power of data and empowering them through training..
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Some final remarks
We see in almost all the research on this topic that Culture and Data literacy are two of the main roadblocks in becoming a data driven company. Secondly, seeing data as an asset is a popular idea, but scarcity standards, unfamiliarity with business models and a lack of skills, people and experience, still prevent supply chain leaders from driving real value from data.
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Sources
- Gartner (2019a), Hype Cycle for Supply Chain Planning Technologies, Published 29 October 2019 – ID G00463637Gartner (2019b), Gartner Identifies Top 10 Data and Analytics Technology Trends for 2019, Published February 2019.
- Furr, N., Shipilov, A., (2019), Digital Doesn’t Have to Be Disruptive, The beste results can com from adaptation rather than reinvention, Harvard Business Review, July-August, 2019.
- Butner, K, (2018), New Rules for a New Decade, a vision for smarter supply chain management, IBM Institute for Business Value, ibm.com/iibv
- LaValle, S., E.Lesser, R. Shockley, M.S.Hopkins, N.Kruschwitz, (2011), Big Data, Analytics and the Path From Insights to Value, MIT SLoan Management Review, Winter 201, Vol.52, No.2
- Mahajan, S., S.Saha, A.Macias, (2017), Analytics: Laying the foundation for supply chain digital transformation, The Hacket Group.
- Gartner, (2019), Gartner Identifies Top 10 Data and Analytics Technology Trends for 2019 (https://www.gartner.com/en/newsroom/press-releases/2019-02-18-gartner-identifies-top-10-data-and-analytics-technolo)
- McCrea, B., (2019), 2019 Top 20 supply chain software suppliers, https://www.supplychain247.com/article/2019_top_20_supply_chain_software_suppliers/technology
WEF, (2017), Impact of the Fourth Industrial Revolution on Supply Chains